diff --git a/python/src/main.cpp b/python/src/main.cpp index 6f99a193b..cb538112b 100644 --- a/python/src/main.cpp +++ b/python/src/main.cpp @@ -23,8 +23,7 @@ PYBIND11_MODULE(kp, m) { py::module_ np = py::module_::import("numpy"); - - py::enum_(m, "TensorTypes", DOC(kp, Tensor, TensorTypes)) + py::enum_(m, "TensorTypes") .value("device", kp::Tensor::TensorTypes::eDevice, "Tensor holding data in GPU memory.") .value("host", kp::Tensor::TensorTypes::eHost, "Tensor used for CPU visible GPU data.") .value("storage", kp::Tensor::TensorTypes::eStorage, "Tensor with host visible gpu memory.") @@ -53,20 +52,28 @@ PYBIND11_MODULE(kp, m) { py::arg("sources"), py::arg("files") = std::vector(), py::arg("entryPoint") = "main", py::arg("definitions") = std::vector>() ); #endif // KOMPUTE_DISABLE_SHADER_UTILS + py::class_>(m, "OpBase"); + + py::class_>(m, "OpTensorSyncDevice") + .def(py::init>&>()); + + py::class_>(m, "OpTensorSyncLocal") + .def(py::init>&>()); + + py::class_>(m, "OpTensorCopy") + .def(py::init>&>()); + + py::class_>(m, "OpAlgoDispatch") + .def(py::init&, bool>()); + + py::class_>(m, "Algorithm") + .def("get_tensors", &kp::Algorithm::getTensors) + .def("destroy", &kp::Algorithm::destroy) + .def("get_spec_consts", &kp::Algorithm::getSpecializationConstants) + .def("get_push_consts", &kp::Algorithm::getPushConstants) + .def("is_init", &kp::Algorithm::isInit); + py::class_>(m, "Tensor", DOC(kp, Tensor)) - .def(py::init( - [np](const py::array_t data, kp::Tensor::TensorTypes tensor_type) { - const py::array_t flatdata = np.attr("ravel")(data); - const py::buffer_info info = flatdata.request(); - const float* ptr = (float*) info.ptr; - return std::unique_ptr( - new kp::Tensor(std::vector(ptr, ptr+flatdata.size()), tensor_type) - ); - }), - "Construct Tensor with an array as initial data and an optional kp.TensorType (default:device).", - py::arg("data"), - py::arg("tensor_type") = kp::Tensor::TensorTypes::eDevice - ) .def("data", &kp::Tensor::data, DOC(kp, Tensor, data)) .def("numpy", [](kp::Tensor& self) { return py::array(self.data().size(), self.data().data()); @@ -108,218 +115,47 @@ PYBIND11_MODULE(kp, m) { .def("map_data_from_host", &kp::Tensor::mapDataFromHostMemory, "Maps data into GPU memory from tensor local data.") .def("map_data_into_host", &kp::Tensor::mapDataIntoHostMemory, "Maps data from GPU memory into tensor local data."); - py::class_>(m, "Sequence") - .def("init", &kp::Sequence::init, DOC(kp, Sequence, init)) - - // record - .def("begin", &kp::Sequence::begin, DOC(kp, Sequence, begin)) - .def("end", &kp::Sequence::end, DOC(kp, Sequence, end)) - - // eval - .def("eval", &kp::Sequence::eval, DOC(kp, Sequence, eval)) - .def("eval_async", &kp::Sequence::evalAsync, DOC(kp, Sequence, evalAsync)) - .def("eval_await", &kp::Sequence::evalAwait, DOC(kp, Sequence, evalAwait)) - - // status - .def("is_running", &kp::Sequence::isRunning, DOC(kp, Sequence, isRunning)) - .def("is_rec", &kp::Sequence::isRecording, DOC(kp, Sequence, isRecording)) - .def("is_init", &kp::Sequence::isInit, DOC(kp, Sequence, isInit)) - - // record - .def("record_tensor_copy", &kp::Sequence::record, DOC(kp, Sequence, record)) - .def("record_tensor_sync_device", &kp::Sequence::record, - "Records operation to sync tensor from local memory to GPU memory") - .def("record_tensor_sync_local", &kp::Sequence::record, - "Records operation to sync tensor(s) from GPU memory to local memory") - .def("record_algo_file", &kp::Sequence::record< - kp::OpAlgoCreate, - const std::string&, - kp::Workgroup, - kp::Constants>, - "Records an operation using a custom shader provided from a shader path", - py::arg("tensors"), py::arg("data"), py::arg("workgroup") = kp::Workgroup(), py::arg("constants") = kp::Constants() ) - .def("record_algo_data", [](kp::Sequence &self, - std::vector> tensors, - py::bytes &bytes, - kp::Workgroup workgroup, - kp::Constants constants) -> bool { - // Bytes have to be converted into std::vector - py::buffer_info info(py::buffer(bytes).request()); - const char *data = reinterpret_cast(info.ptr); - size_t length = static_cast(info.size); - return self.record( - tensors, std::vector((uint32_t*)data, (uint32_t*)(data + length)), workgroup, constants); - }, - "Records an operation using a custom shader provided as spirv bytes", - py::arg("tensors"), py::arg("bytes"), py::arg("workgroup") = kp::Workgroup(), py::arg("constants") = kp::Constants() ); + .def("record", [](kp::Sequence& self, std::shared_ptr op) { return self.record(op); }) + .def("eval", [](kp::Sequence& self) { return self.eval(); }) + .def("eval", [](kp::Sequence& self, std::shared_ptr op) { return self.eval(op); }) + .def("eval_async", [](kp::Sequence& self) { return self.eval(); }) + .def("eval_async", [](kp::Sequence& self, std::shared_ptr op) { return self.evalAsync(op); }) + .def("eval_await", [](kp::Sequence& self) { return self.evalAwait(); }) + .def("eval_await", [](kp::Sequence& self, uint32_t wait) { return self.evalAwait(wait); }) + .def("is_recording", &kp::Sequence::isRecording) + .def("is_running", &kp::Sequence::isRunning) + .def("is_init", &kp::Sequence::isInit) + .def("clear", &kp::Sequence::clear) + .def("destroy", &kp::Sequence::destroy); - - py::class_(m, "Manager") - .def(py::init(), "Default initializer uses device 0 and first compute compatible GPU queueFamily") - .def(py::init( - [](uint32_t physicalDeviceIndex) { - return std::unique_ptr(new kp::Manager(physicalDeviceIndex)); - }), "Manager initialiser can provide specified device index but will use first compute compatible GPU queueFamily") - .def(py::init( - [](uint32_t physicalDeviceIndex, const std::vector& familyQueueIndices) { - return std::unique_ptr(new kp::Manager(physicalDeviceIndex, familyQueueIndices)); - }), "Manager initialiser can provide specified device and array of GPU queueFamilies to load.") - .def("sequence", &kp::Manager::sequence, - py::arg("name") = "", py::arg("queueIndex") = 0, "Get or create a sequence with specific name and specified index of available queues") - .def("tensor", &kp::Manager::tensor, - py::arg("data"), py::arg("tensorType") = kp::Tensor::TensorTypes::eDevice, py::arg("syncDataToGPU") = true, - "Build and initialise tensor") - .def("rebuild", py::overload_cast>, bool>(&kp::Manager::rebuild), - py::arg("tensors"), py::arg("syncDataToGPU") = true, - "Build and initialise list of tensors") - .def("rebuild", py::overload_cast, bool>(&kp::Manager::rebuild), - py::arg("tensor"), py::arg("syncDataToGPU") = true, - "Build and initialise tensor") - .def("destroy", py::overload_cast>(&kp::Manager::destroy), - py::arg("tensor"), DOC(kp, Manager, destroy)) - .def("destroy", py::overload_cast>>(&kp::Manager::destroy), - py::arg("tensors"), DOC(kp, Manager, destroy, 2)) - .def("destroy", py::overload_cast>>(&kp::Manager::destroy), - py::arg("sequences"), DOC(kp, Manager, destroy, 3)) - .def("destroy", py::overload_cast>(&kp::Manager::destroy), - py::arg("sequence"), DOC(kp, Manager, destroy, 4)) - .def("destroy", py::overload_cast(&kp::Manager::destroy), - py::arg("sequenceName"), DOC(kp, Manager, destroy, 5)) - .def("destroy", py::overload_cast&>(&kp::Manager::destroy), - py::arg("sequenceNames"), DOC(kp, Manager, destroy, 6)) - // temporary backwards compatibility - .def("eval_tensor_create_def",[](kp::Manager& self, std::vector> tensors, bool syncDataToGPU) -> void { - kp_error("IMPORTANT: eval_tensor_create_def is depricated! Please use Manager.rebuild instead as function will be removed soon."); - self.rebuild(tensors, syncDataToGPU); - }, - py::arg("tensors"), py::arg("syncDataToGPU") = true, - "Temporary backwards compatibility for tensor creation function which will be removed in the next version.") - - // Await functions - .def("eval_await", &kp::Manager::evalOpAwait, - py::arg("sequenceName"), py::arg("waitFor") = UINT64_MAX, - "Awaits for asynchronous operation on a named Sequence") - .def("eval_await_def", &kp::Manager::evalOpAwaitDefault, - py::arg("waitFor") = UINT64_MAX, "Awaits for asynchronous operation on the last anonymous Sequence created") - - // eval default - .def("eval_tensor_copy_def", &kp::Manager::evalOpDefault, - "Evaluates operation to copy one tensor to one or many tensors with new anonymous Sequence") - .def("eval_tensor_sync_device_def", &kp::Manager::evalOpDefault, - "Evaluates operation to sync tensor from local memory to GPU memory with new anonymous Sequence") - .def("eval_tensor_sync_local_def", &kp::Manager::evalOpDefault, - "Evaluates operation to sync tensor(s) from GPU memory to local memory with new anonymous Sequence") - .def("eval_algo_file_def", &kp::Manager::evalOpDefault< - kp::OpAlgoCreate, - const std::string&, - kp::Workgroup, - kp::Constants>, - "Evaluates an operation using a custom shader provided from a shader path with new anonymous Sequence", - py::arg("tensors"), py::arg("data"), py::arg("workgroup") = kp::Workgroup(), py::arg("constants") = kp::Constants() ) - .def("eval_algo_data_def", [](kp::Manager &self, - std::vector> tensors, - py::bytes &bytes, - kp::Workgroup workgroup, - kp::Constants constants) { - // Bytes have to be converted into std::vector - py::buffer_info info(py::buffer(bytes).request()); - const char *data = reinterpret_cast(info.ptr); - size_t length = static_cast(info.size); - self.evalOpDefault( - tensors, std::vector((uint32_t*)data, (uint32_t*)(data + length)), workgroup, constants); + py::class_>(m, "Manager") + .def(py::init()) + .def(py::init()) + .def(py::init&>()) + .def("sequence", &kp::Manager::sequence, py::arg("queueIndex") = 0) + .def("tensor", [np](kp::Manager& self, + const py::array_t data, + kp::Tensor::TensorTypes tensor_type) { + const py::array_t flatdata = np.attr("ravel")(data); + const py::buffer_info info = flatdata.request(); + const float* ptr = (float*) info.ptr; + return self.tensor(std::vector(ptr, ptr+flatdata.size()), tensor_type); }, - "Evaluates an operation using a custom shader provided as spirv bytes with new anonymous Sequence", - py::arg("tensors"), py::arg("bytes"), py::arg("workgroup") = kp::Workgroup(), py::arg("constants") = kp::Constants() ) - - // eval - .def("eval_tensor_copy", &kp::Manager::evalOp, - "Evaluates operation to copy one tensor to one or many tensors with explicitly named Sequence") - .def("eval_tensor_sync_device", &kp::Manager::evalOp, - "Evaluates operation to sync tensor from local memory to GPU memory with explicitly named Sequence") - .def("eval_tensor_sync_local", &kp::Manager::evalOp, - "Evaluates operation to sync tensor(s) from GPU memory to local memory with explicitly named Sequence") - .def("eval_algo_file", &kp::Manager::evalOp< - kp::OpAlgoCreate, - const std::string&, - kp::Workgroup, - kp::Constants>, - "Evaluates an operation using a custom shader provided from a shader path with explicitly named Sequence", - py::arg("tensors"), py::arg("sequence_name"), py::arg("data"),py::arg("workgroup") = kp::Workgroup(), py::arg("constants") = kp::Constants() ) - .def("eval_algo_data", [](kp::Manager &self, - std::vector> tensors, - std::string sequenceName, - py::bytes &bytes, - kp::Workgroup workgroup, - kp::Constants constants) { - // Bytes have to be converted into std::vector - py::buffer_info info(py::buffer(bytes).request()); - const char *data = reinterpret_cast(info.ptr); - size_t length = static_cast(info.size); - self.evalOp( - tensors, sequenceName, std::vector((uint32_t*)data, (uint32_t*)(data + length)), workgroup, constants); - }, - "Evaluates an operation using a custom shader provided as spirv bytes with explicitly named Sequence", - py::arg("tensors"), py::arg("sequence_name"), py::arg("bytes"), py::arg("workgroup") = kp::Workgroup(), py::arg("constants") = kp::Constants() ) - - // eval async default - .def("eval_async_tensor_copy_def", &kp::Manager::evalOpAsyncDefault, - "Evaluates asynchronously operation to copy one tensor to one or many tensors with anonymous Sequence") - .def("eval_async_tensor_sync_device_def", &kp::Manager::evalOpAsyncDefault, - "Evaluates asynchronously operation to sync tensor from local memory to GPU memory with anonymous Sequence") - .def("eval_async_tensor_sync_local_def", &kp::Manager::evalOpAsyncDefault, - "Evaluates asynchronously operation to sync tensor(s) from GPU memory to local memory with anonymous Sequence") - .def("eval_async_algo_file_def", &kp::Manager::evalOpAsyncDefault< - kp::OpAlgoCreate, - const std::string&, - kp::Workgroup, - kp::Constants>, - "Evaluates asynchronously an operation using a custom shader provided from a shader path with anonymous Sequence", - py::arg("tensors"), py::arg("data"), py::arg("workgroup") = kp::Workgroup(), py::arg("constants") = kp::Constants() ) - .def("eval_async_algo_data_def", [](kp::Manager &self, - std::vector> tensors, - py::bytes &bytes, - kp::Workgroup workgroup, - kp::Constants constants) { - // Bytes have to be converted into std::vector - py::buffer_info info(py::buffer(bytes).request()); - const char *data = reinterpret_cast(info.ptr); - size_t length = static_cast(info.size); - self.evalOpAsyncDefault( - tensors, std::vector((uint32_t*)data, (uint32_t*)(data + length)), workgroup, constants); - }, - "Evaluates asynchronously an operation using a custom shader provided as raw string or spirv bytes with anonymous Sequence", - py::arg("tensors"), py::arg("bytes"), py::arg("workgroup") = kp::Workgroup(), py::arg("constants") = kp::Constants() ) - - // eval async - .def("eval_async_tensor_copy", &kp::Manager::evalOpAsync, - "Evaluates asynchronously operation to copy one tensor to one or many tensors with explicitly named Sequence") - .def("eval_async_tensor_sync_device", &kp::Manager::evalOpAsync, - "Evaluates asynchronously operation to sync tensor from local memory to GPU memory with explicitly named Sequence") - .def("eval_async_tensor_sync_local", &kp::Manager::evalOpAsync, - "Evaluates asynchronously operation to sync tensor(s) from GPU memory to local memory with explicitly named Sequence") - .def("eval_async_algo_file", &kp::Manager::evalOpAsync< - kp::OpAlgoCreate, - const std::string&, - kp::Workgroup, - kp::Constants>, - "Evaluates asynchronously an operation using a custom shader provided from a shader path with explicitly named Sequence", - py::arg("tensors"), py::arg("sequence_name"), py::arg("data"), py::arg("workgroup") = kp::Workgroup(), py::arg("constants") = kp::Constants() ) - .def("eval_async_algo_data", [](kp::Manager &self, - std::vector> tensors, - std::string sequenceName, - py::bytes &bytes, - kp::Workgroup workgroup, - kp::Constants constants) { - // Bytes have to be converted into std::vector - py::buffer_info info(py::buffer(bytes).request()); - const char *data = reinterpret_cast(info.ptr); - size_t length = static_cast(info.size); - self.evalOpAsync( - tensors, sequenceName, std::vector((uint32_t*)data, (uint32_t*)(data + length)), workgroup, constants); - }, - "Evaluates asynchronously an operation using a custom shader provided as raw string or spirv bytes with explicitly named Sequence", - py::arg("tensors"), py::arg("sequence_name"), py::arg("bytes"), py::arg("workgroup") = kp::Workgroup(), py::arg("constants") = kp::Constants() ); + "Tensor initialisation function with data and tensor type", + py::arg("data"), py::arg("tensor_type") = kp::Tensor::TensorTypes::eDevice) + .def("algorithm", [](kp::Manager& self, + const std::vector>& tensors, + const py::bytes& spirv, + const kp::Workgroup& workgroup = {}, + const kp::Constants& spec_consts = {}, + const kp::Constants& push_consts = {}) { + py::buffer_info info(py::buffer(spirv).request()); + const char *data = reinterpret_cast(info.ptr); + size_t length = static_cast(info.size); + std::vector spirvVec((uint32_t*)data, (uint32_t*)(data + length)); + return self.algorithm(tensors, spirvVec, workgroup, spec_consts, push_consts); + }); #ifdef VERSION_INFO m.attr("__version__") = VERSION_INFO; diff --git a/python/test/test_kompute.py b/python/test/test_kompute.py index 2ba4d4868..e923c6393 100644 --- a/python/test/test_kompute.py +++ b/python/test/test_kompute.py @@ -7,25 +7,26 @@ import pyshader as ps DIRNAME = os.path.dirname(os.path.abspath(__file__)) -def test_opalgobase_file(): - """ - Test basic OpMult operation - """ - - tensor_in_a = kp.Tensor([2, 2, 2]) - tensor_in_b = kp.Tensor([1, 2, 3]) - tensor_out = kp.Tensor([0, 0, 0]) - - mgr = kp.Manager() - mgr.rebuild([tensor_in_a, tensor_in_b, tensor_out]) - - shader_path = os.path.join(DIRNAME, "../../shaders/glsl/opmult.comp.spv") - - mgr.eval_algo_file_def([tensor_in_a, tensor_in_b, tensor_out], shader_path) - - mgr.eval_tensor_sync_local_def([tensor_out]) - - assert tensor_out.data() == [2.0, 4.0, 6.0] +# TODO: Add example with file +#def test_opalgobase_file(): +# """ +# Test basic OpMult operation +# """ +# +# tensor_in_a = kp.Tensor([2, 2, 2]) +# tensor_in_b = kp.Tensor([1, 2, 3]) +# tensor_out = kp.Tensor([0, 0, 0]) +# +# mgr = kp.Manager() +# mgr.rebuild([tensor_in_a, tensor_in_b, tensor_out]) +# +# shader_path = os.path.join(DIRNAME, "../../shaders/glsl/opmult.comp.spv") +# +# mgr.eval_algo_file_def([tensor_in_a, tensor_in_b, tensor_out], shader_path) +# +# mgr.eval_tensor_sync_local_def([tensor_out]) +# +# assert tensor_out.data() == [2.0, 4.0, 6.0] @@ -48,18 +49,23 @@ void main() } """ - tensor_in_a = kp.Tensor([2, 2, 2]) - tensor_in_b = kp.Tensor([1, 2, 3]) - tensor_out = kp.Tensor([0, 0, 0]) - - mgr = kp.Manager() - mgr.rebuild([tensor_in_a, tensor_in_b, tensor_out]) - spirv = kp.Shader.compile_source(shader) - mgr.eval_algo_data_def([tensor_in_a, tensor_in_b, tensor_out], spirv) + mgr = kp.Manager() - mgr.eval_tensor_sync_local_def([tensor_out]) + tensor_in_a = mgr.tensor([2, 2, 2]) + tensor_in_b = mgr.tensor([1, 2, 3]) + tensor_out = mgr.tensor([0, 0, 0]) + + params = [tensor_in_a, tensor_in_b, tensor_out] + + algo = mgr.algorithm(params, spirv) + + (mgr.sequence() + .record(kp.OpTensorSyncLocal(params)) + .record(kp.OpAlgoDispatch(algo)) + .record(kp.OpTensorSyncDevice(params)) + .eval()) assert tensor_out.data() == [2.0, 4.0, 6.0] @@ -67,36 +73,53 @@ def test_sequence(): """ Test basic OpAlgoBase operation """ - mgr = kp.Manager(0, [2]) - tensor_in_a = kp.Tensor([2, 2, 2]) - tensor_in_b = kp.Tensor([1, 2, 3]) - tensor_out = kp.Tensor([0, 0, 0]) + shader = """ + #version 450 + layout(set = 0, binding = 0) buffer tensorLhs {float valuesLhs[];}; + layout(set = 0, binding = 1) buffer tensorRhs {float valuesRhs[];}; + layout(set = 0, binding = 2) buffer tensorOutput { float valuesOutput[];}; + layout (local_size_x = 1, local_size_y = 1, local_size_z = 1) in; - mgr.rebuild([tensor_in_a, tensor_in_b, tensor_out]) + void main() + { + uint index = gl_GlobalInvocationID.x; + valuesOutput[index] = valuesLhs[index] * valuesRhs[index]; + } + """ - shader_path = os.path.abspath(os.path.join(DIRNAME, "../../shaders/glsl/opmult.comp.spv")) - mgr.eval_async_algo_file_def([tensor_in_a, tensor_in_b, tensor_out], shader_path) + spirv = kp.Shader.compile_source(shader) - mgr.eval_await_def() + mgr = kp.Manager(0) - seq = mgr.sequence("op") - seq.begin() - seq.record_tensor_sync_local([tensor_in_a]) - seq.record_tensor_sync_local([tensor_in_b]) - seq.record_tensor_sync_local([tensor_out]) - seq.end() - seq.eval() + tensor_in_a = mgr.tensor([2, 2, 2]) + tensor_in_b = mgr.tensor([1, 2, 3]) + tensor_out = mgr.tensor([0, 0, 0]) - mgr.destroy("op") + params = [tensor_in_a, tensor_in_b, tensor_out] - assert seq.is_init() == False + algo = mgr.algorithm(params, spirv) + + sq = mgr.sequence() + + sq.record(kp.OpTensorSyncLocal(params)) + sq.record(kp.OpAlgoDispatch(algo)) + sq.record(kp.OpTensorSyncDevice(params)) + + sq.eval() + + assert sq.is_init() == True + + sq.destroy() + + assert sq.is_init() == False assert tensor_out.data() == [2.0, 4.0, 6.0] assert np.all(tensor_out.numpy() == [2.0, 4.0, 6.0]) - mgr.destroy(tensor_in_a) - mgr.destroy([tensor_in_b, tensor_out]) + tensor_in_a.destroy() + tensor_in_b.destroy() + tensor_out.destroy() assert tensor_in_a.is_init() == False assert tensor_in_b.is_init() == False @@ -105,10 +128,8 @@ def test_sequence(): def test_workgroup(): mgr = kp.Manager(0) - tensor_a = kp.Tensor(np.zeros([16,8])) - tensor_b = kp.Tensor(np.zeros([16,8])) - - mgr.rebuild([tensor_a, tensor_b]) + tensor_a = mgr.tensor(np.zeros([16,8])) + tensor_b = mgr.tensor(np.zeros([16,8])) @ps.python2shader def compute_shader_wg(gl_idx=("input", "GlobalInvocationId", ps.ivec3), @@ -120,17 +141,15 @@ def test_workgroup(): data1[i] = f32(gl_idx.x) data2[i] = f32(gl_idx.y) - seq = mgr.sequence("new") - seq.begin() - seq.record_algo_data([tensor_a, tensor_b], compute_shader_wg.to_spirv(), workgroup=(16,8,1)) - seq.end() - seq.eval() + algo = mgr.algorithm([tensor_a, tensor_b], compute_shader_wg.to_spirv(), (16,8,1), [], []) - mgr.destroy(seq) + (mgr.sequence() + .record(kp.OpTensorSyncDevice([tensor_a, tensor_b])) + .record(kp.OpAlgoDispatch(algo)) + .record(kp.OpAlgoTensorSyncLocal([tensor_a, tensor_b])) + .eval()) - assert seq.is_init() == False - - mgr.eval_tensor_sync_local_def([tensor_a, tensor_b]) + assert sq.is_init() == False print(tensor_a.numpy()) print(tensor_b.numpy()) @@ -138,32 +157,3 @@ def test_workgroup(): assert np.all(tensor_a.numpy() == np.stack([np.arange(16)]*8, axis=1).ravel()) assert np.all(tensor_b.numpy() == np.stack([np.arange(8)]*16, axis=0).ravel()) - mgr.destroy([tensor_a, tensor_b]) - - assert tensor_a.is_init() == False - assert tensor_b.is_init() == False - - -def test_tensor_rebuild_backwards_compat(): - """ - Test basic OpMult operation - """ - - tensor_in_a = kp.Tensor([2, 2, 2]) - tensor_in_b = kp.Tensor([1, 2, 3]) - tensor_out = kp.Tensor([0, 0, 0]) - - mgr = kp.Manager() - - mgr.eval_tensor_create_def([tensor_in_a, tensor_in_b, tensor_out]) - - shader_path = os.path.abspath(os.path.join(DIRNAME, "../../shaders/glsl/opmult.comp.spv")) - mgr.eval_async_algo_file_def([tensor_in_a, tensor_in_b, tensor_out], shader_path) - mgr.eval_await_def() - - mgr.eval_tensor_sync_local_def([tensor_out]) - - assert tensor_out.data() == [2.0, 4.0, 6.0] - assert np.all(tensor_out.numpy() == [2.0, 4.0, 6.0]) - - diff --git a/shaders/glsl/logisticregression.comp.spv b/shaders/glsl/logisticregression.comp.spv index 2f6883dac..f68cb431d 100755 Binary files a/shaders/glsl/logisticregression.comp.spv and b/shaders/glsl/logisticregression.comp.spv differ diff --git a/shaders/glsl/opmult.comp.spv b/shaders/glsl/opmult.comp.spv index 63eea751b..4ad5057d2 100755 Binary files a/shaders/glsl/opmult.comp.spv and b/shaders/glsl/opmult.comp.spv differ diff --git a/single_include/AggregateHeaders.cpp b/single_include/AggregateHeaders.cpp index d47892cf1..23372873b 100644 --- a/single_include/AggregateHeaders.cpp +++ b/single_include/AggregateHeaders.cpp @@ -1,15 +1,15 @@ #pragma once -#include "kompute/Core.hpp" -#include "kompute/Shader.hpp" #include "kompute/shaders/shaderopmult.hpp" #include "kompute/shaders/shaderlogisticregression.hpp" -#include "kompute/Manager.hpp" -#include "kompute/Sequence.hpp" +#include "kompute/Core.hpp" +#include "kompute/Shader.hpp" +#include "kompute/Tensor.hpp" +#include "kompute/Algorithm.hpp" #include "kompute/operations/OpBase.hpp" #include "kompute/operations/OpMult.hpp" #include "kompute/operations/OpTensorCopy.hpp" #include "kompute/operations/OpTensorSyncDevice.hpp" #include "kompute/operations/OpTensorSyncLocal.hpp" #include "kompute/operations/OpAlgoDispatch.hpp" -#include "kompute/Algorithm.hpp" -#include "kompute/Tensor.hpp" +#include "kompute/Sequence.hpp" +#include "kompute/Manager.hpp" diff --git a/single_include/kompute/Kompute.hpp b/single_include/kompute/Kompute.hpp index 79bc6e1b4..b1d278081 100755 --- a/single_include/kompute/Kompute.hpp +++ b/single_include/kompute/Kompute.hpp @@ -1,1863 +1,1861 @@ -#pragma once - -#if VK_USE_PLATFORM_ANDROID_KHR -#include -#include -// VK_NO_PROTOTYPES required before vulkan import but after wrapper.hpp -#undef VK_NO_PROTOTYPES -static const char* KOMPUTE_LOG_TAG = "KomputeLog"; -#endif - -#include - -#include - -// Typedefs to simplify interaction with core types -namespace kp { -typedef std::array Workgroup; -typedef std::vector Constants; -} - -// Must be after vulkan is included -#ifndef KOMPUTE_VK_API_VERSION -#ifndef KOMPUTE_VK_API_MAJOR_VERSION -#define KOMPUTE_VK_API_MAJOR_VERSION 1 -#endif // KOMPUTE_VK_API_MAJOR_VERSION -#ifndef KOMPUTE_VK_API_MINOR_VERSION -#define KOMPUTE_VK_API_MINOR_VERSION 1 -#endif // KOMPUTE_VK_API_MINOR_VERSION -#define KOMPUTE_VK_API_VERSION \ - VK_MAKE_VERSION( \ - KOMPUTE_VK_API_MAJOR_VERSION, KOMPUTE_VK_API_MINOR_VERSION, 0) -#endif // KOMPUTE_VK_API_VERSION - -// SPDLOG_ACTIVE_LEVEL must be defined before spdlog.h import -#ifndef SPDLOG_ACTIVE_LEVEL -#if DEBUG -#define SPDLOG_ACTIVE_LEVEL SPDLOG_LEVEL_DEBUG -#else -#define SPDLOG_ACTIVE_LEVEL SPDLOG_LEVEL_INFO -#endif -#endif - -#if defined(KOMPUTE_BUILD_PYTHON) -#include -namespace py = pybind11; -// from python/src/main.cpp -extern py::object kp_debug, kp_info, kp_warning, kp_error; -#endif - -#ifndef KOMPUTE_LOG_OVERRIDE -#if KOMPUTE_ENABLE_SPDLOG -#include -#define KP_LOG_DEBUG(...) SPDLOG_DEBUG(__VA_ARGS__) -#define KP_LOG_INFO(...) SPDLOG_INFO(__VA_ARGS__) -#define KP_LOG_WARN(...) SPDLOG_WARN(__VA_ARGS__) -#define KP_LOG_ERROR(...) SPDLOG_ERROR(__VA_ARGS__) -#else -#include -#if SPDLOG_ACTIVE_LEVEL > 1 -#define KP_LOG_DEBUG(...) -#else -#if defined(VK_USE_PLATFORM_ANDROID_KHR) -#define KP_LOG_DEBUG(...) \ - ((void)__android_log_print(ANDROID_LOG_DEBUG, KOMPUTE_LOG_TAG, fmt::format(__VA_ARGS__))) -#elif defined(KOMPUTE_BUILD_PYTHON) -#define KP_LOG_DEBUG(...) kp_debug(fmt::format(__VA_ARGS__)) -#else -#define KP_LOG_DEBUG(...) fmt::print("[{} {}] [debug] [{}:{}] {}\n", __DATE__, __TIME__, __FILE__, __LINE__, fmt::format(__VA_ARGS__)) -#endif // VK_USE_PLATFORM_ANDROID_KHR -#endif // SPDLOG_ACTIVE_LEVEL > 1 - -#if SPDLOG_ACTIVE_LEVEL > 2 -#define KP_LOG_INFO(...) -#else -#if defined(VK_USE_PLATFORM_ANDROID_KHR) -#define KP_LOG_INFO(...) \ - ((void)__android_log_print(ANDROID_LOG_INFO, KOMPUTE_LOG_TAG, fmt::format(__VA_ARGS__))) -#elif defined(KOMPUTE_BUILD_PYTHON) -#define KP_LOG_INFO(...) kp_info(fmt::format(__VA_ARGS__)) -#else -#define KP_LOG_INFO(...) fmt::print("[{} {}] [debug] [{}:{}] {}\n", __DATE__, __TIME__, __FILE__, __LINE__, fmt::format(__VA_ARGS__)) -#endif // VK_USE_PLATFORM_ANDROID_KHR -#endif // SPDLOG_ACTIVE_LEVEL > 2 - -#if SPDLOG_ACTIVE_LEVEL > 3 -#define KP_LOG_WARN(...) -#else -#if defined(VK_USE_PLATFORM_ANDROID_KHR) -#define KP_LOG_WARN(...) \ - ((void)__android_log_print(ANDROID_LOG_WARN, KOMPUTE_LOG_TAG, fmt::format(__VA_ARGS__))) -#elif defined(KOMPUTE_BUILD_PYTHON) -#define KP_LOG_WARN(...) kp_warning(fmt::format(__VA_ARGS__)) -#else -#define KP_LOG_WARN(...) fmt::print("[{} {}] [debug] [{}:{}] {}\n", __DATE__, __TIME__, __FILE__, __LINE__, fmt::format(__VA_ARGS__)) -#endif // VK_USE_PLATFORM_ANDROID_KHR -#endif // SPDLOG_ACTIVE_LEVEL > 3 - -#if SPDLOG_ACTIVE_LEVEL > 4 -#define KP_LOG_ERROR(...) -#else -#if defined(VK_USE_PLATFORM_ANDROID_KHR) -#define KP_LOG_ERROR(...) \ - ((void)__android_log_print(ANDROID_LOG_ERROR, KOMPUTE_LOG_TAG, fmt::format(__VA_ARGS__))) -#elif defined(KOMPUTE_BUILD_PYTHON) -#define KP_LOG_ERROR(...) kp_error(fmt::format(__VA_ARGS__)) -#else -#define KP_LOG_ERROR(...) fmt::print("[{} {}] [debug] [{}:{}] {}\n", __DATE__, __TIME__, __FILE__, __LINE__, fmt::format(__VA_ARGS__)) -#endif // VK_USE_PLATFORM_ANDROID_KHR -#endif // SPDLOG_ACTIVE_LEVEL > 4 -#endif // KOMPUTE_SPDLOG_ENABLED -#endif // KOMPUTE_LOG_OVERRIDE - -#if !defined(KOMPUTE_DISABLE_SHADER_UTILS) || !KOMPUTE_DISABLE_SHADER_UTILS -#include -#include - -#include -#include -#include - -namespace kp { - -// The default resource limit for the GLSL compiler, can be overwritten -// Has been adobted by: -// https://github.com/KhronosGroup/glslang/blob/master/StandAlone/ResourceLimits.cpp -const TBuiltInResource defaultResource = { -/* .MaxLights = */ 0, -/* .MaxClipPlanes = */ 0, -/* .MaxTextureUnits = */ 0, -/* .MaxTextureCoords = */ 0, -/* .MaxVertexAttribs = */ 64, -/* .MaxVertexUniformComponents = */ 4096, -/* .MaxVaryingFloats = */ 64, -/* .MaxVertexTextureImageUnits = */ 0, -/* .MaxCombinedTextureImageUnits = */ 0, -/* .MaxTextureImageUnits = */ 0, -/* .MaxFragmentUniformComponents = */ 0, -/* .MaxDrawBuffers = */ 0, -/* .MaxVertexUniformVectors = */ 128, -/* .MaxVaryingVectors = */ 8, -/* .MaxFragmentUniformVectors = */ 0, -/* .MaxVertexOutputVectors = */ 16, -/* .MaxFragmentInputVectors = */ 0, -/* .MinProgramTexelOffset = */ -8, -/* .MaxProgramTexelOffset = */ 7, -/* .MaxClipDistances = */ 8, -/* .MaxComputeWorkGroupCountX = */ 65535, -/* .MaxComputeWorkGroupCountY = */ 65535, -/* .MaxComputeWorkGroupCountZ = */ 65535, -/* .MaxComputeWorkGroupSizeX = */ 1024, -/* .MaxComputeWorkGroupSizeY = */ 1024, -/* .MaxComputeWorkGroupSizeZ = */ 64, -/* .MaxComputeUniformComponents = */ 1024, -/* .MaxComputeTextureImageUnits = */ 16, -/* .MaxComputeImageUniforms = */ 8, -/* .MaxComputeAtomicCounters = */ 8, -/* .MaxComputeAtomicCounterBuffers = */ 1, -/* .MaxVaryingComponents = */ 60, -/* .MaxVertexOutputComponents = */ 64, -/* .MaxGeometryInputComponents = */ 64, -/* .MaxGeometryOutputComponents = */ 128, -/* .MaxFragmentInputComponents = */ 0, -/* .MaxImageUnits = */ 0, -/* .MaxCombinedImageUnitsAndFragmentOutputs = */ 0, -/* .MaxCombinedShaderOutputResources = */ 8, -/* .MaxImageSamples = */ 0, -/* .MaxVertexImageUniforms = */ 0, -/* .MaxTessControlImageUniforms = */ 0, -/* .MaxTessEvaluationImageUniforms = */ 0, -/* .MaxGeometryImageUniforms = */ 0, -/* .MaxFragmentImageUniforms = */ 0, -/* .MaxCombinedImageUniforms = */ 0, -/* .MaxGeometryTextureImageUnits = */ 0, -/* .MaxGeometryOutputVertices = */ 256, -/* .MaxGeometryTotalOutputComponents = */ 1024, -/* .MaxGeometryUniformComponents = */ 1024, -/* .MaxGeometryVaryingComponents = */ 64, -/* .MaxTessControlInputComponents = */ 128, -/* .MaxTessControlOutputComponents = */ 128, -/* .MaxTessControlTextureImageUnits = */ 0, -/* .MaxTessControlUniformComponents = */ 1024, -/* .MaxTessControlTotalOutputComponents = */ 4096, -/* .MaxTessEvaluationInputComponents = */ 128, -/* .MaxTessEvaluationOutputComponents = */ 128, -/* .MaxTessEvaluationTextureImageUnits = */ 16, -/* .MaxTessEvaluationUniformComponents = */ 1024, -/* .MaxTessPatchComponents = */ 120, -/* .MaxPatchVertices = */ 32, -/* .MaxTessGenLevel = */ 64, -/* .MaxViewports = */ 16, -/* .MaxVertexAtomicCounters = */ 0, -/* .MaxTessControlAtomicCounters = */ 0, -/* .MaxTessEvaluationAtomicCounters = */ 0, -/* .MaxGeometryAtomicCounters = */ 0, -/* .MaxFragmentAtomicCounters = */ 0, -/* .MaxCombinedAtomicCounters = */ 8, -/* .MaxAtomicCounterBindings = */ 1, -/* .MaxVertexAtomicCounterBuffers = */ 0, -/* .MaxTessControlAtomicCounterBuffers = */ 0, -/* .MaxTessEvaluationAtomicCounterBuffers = */ 0, -/* .MaxGeometryAtomicCounterBuffers = */ 0, -/* .MaxFragmentAtomicCounterBuffers = */ 0, -/* .MaxCombinedAtomicCounterBuffers = */ 1, -/* .MaxAtomicCounterBufferSize = */ 16384, -/* .MaxTransformFeedbackBuffers = */ 4, -/* .MaxTransformFeedbackInterleavedComponents = */ 64, -/* .MaxCullDistances = */ 8, -/* .MaxCombinedClipAndCullDistances = */ 8, -/* .MaxSamples = */ 4, -/* .maxMeshOutputVerticesNV = */ 256, -/* .maxMeshOutputPrimitivesNV = */ 512, -/* .maxMeshWorkGroupSizeX_NV = */ 32, -/* .maxMeshWorkGroupSizeY_NV = */ 1, -/* .maxMeshWorkGroupSizeZ_NV = */ 1, -/* .maxTaskWorkGroupSizeX_NV = */ 32, -/* .maxTaskWorkGroupSizeY_NV = */ 1, -/* .maxTaskWorkGroupSizeZ_NV = */ 1, -/* .maxMeshViewCountNV = */ 4, -/* .maxDualSourceDrawBuffersEXT = */ 1, - -/* .limits = */ { - /* .nonInductiveForLoops = */ 1, - /* .whileLoops = */ 1, - /* .doWhileLoops = */ 1, - /* .generalUniformIndexing = */ 1, - /* .generalAttributeMatrixVectorIndexing = */ 1, - /* .generalVaryingIndexing = */ 1, - /* .generalSamplerIndexing = */ 1, - /* .generalVariableIndexing = */ 1, - /* .generalConstantMatrixVectorIndexing = */ 1, -}}; - -/** - Shader utily class with functions to compile and process glsl files. -*/ -class Shader { -public: - /** - * Compile multiple sources with optional filenames. Currently this function - * uses the glslang C++ interface which is not thread safe so this funciton - * should not be called from multiple threads concurrently. If you have a - * online shader processing multithreading use-case that can't use offline - * compilation please open an issue. - * - * @param sources A list of raw glsl shaders in string format - * @param files A list of file names respective to each of the sources - * @param entryPoint The function name to use as entry point - * @param definitions List of pairs containing key value definitions - * @param resourcesLimit A list that contains the resource limits for the GLSL compiler - * @return The compiled SPIR-V binary in unsigned int32 format - */ - static std::vector compile_sources( - const std::vector& sources, - const std::vector& files = {}, - const std::string& entryPoint = "main", - std::vector> definitions = {}, - const TBuiltInResource& resources = defaultResource); - - /** - * Compile a single glslang source from string value. Currently this function - * uses the glslang C++ interface which is not thread safe so this funciton - * should not be called from multiple threads concurrently. If you have a - * online shader processing multithreading use-case that can't use offline - * compilation please open an issue. - * - * @param source An individual raw glsl shader in string format - * @param entryPoint The function name to use as entry point - * @param definitions List of pairs containing key value definitions - * @param resourcesLimit A list that contains the resource limits for the GLSL compiler - * @return The compiled SPIR-V binary in unsigned int32 format - */ - static std::vector compile_source( - const std::string& source, - const std::string& entryPoint = "main", - std::vector> definitions = {}, - const TBuiltInResource& resources = defaultResource); - -}; - -} -#endif // DKOMPUTE_DISABLE_SHADER_UTILS - -/* - THIS FILE HAS BEEN AUTOMATICALLY GENERATED - DO NOT EDIT - - --- - - Copyright 2020 The Institute for Ethical AI & Machine Learning - - Licensed under the Apache License, Version 2.0 (the "License"); - you may not use this file except in compliance with the License. - You may obtain a copy of the License at - - http://www.apache.org/licenses/LICENSE-2.0 - - Unless required by applicable law or agreed to in writing, software - distributed under the License is distributed on an "AS IS" BASIS, - WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - See the License for the specific language governing permissions and - limitations under the License. -*/ - -#ifndef SHADEROP_SHADEROPMULT_HPP -#define SHADEROP_SHADEROPMULT_HPP - -namespace kp { -namespace shader_data { -static const unsigned char shaders_glsl_opmult_comp_spv[] = { - 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0a, 0x00, 0x08, 0x00, - 0x2e, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, - 0x01, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, - 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, - 0x00, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x03, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x01, 0x00, 0x00, 0x00, 0x0f, 0x00, 0x06, 0x00, 0x05, 0x00, 0x00, 0x00, - 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0x26, 0x00, 0x00, 0x00, 0x41, 0x00, 0x06, 0x00, 0x1d, 0x00, 0x00, 0x00, - 0x28, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x16, 0x00, 0x00, 0x00, - 0x17, 0x00, 0x00, 0x00, 0x3e, 0x00, 0x03, 0x00, 0x28, 0x00, 0x00, 0x00, - 0x27, 0x00, 0x00, 0x00, 0xfd, 0x00, 0x01, 0x00, 0x38, 0x00, 0x01, 0x00 -}; -static const unsigned int shaders_glsl_opmult_comp_spv_len = 1464; -} -} -#endif // define SHADEROP_SHADEROPMULT_HPP - -/* - THIS FILE HAS BEEN AUTOMATICALLY GENERATED - DO NOT EDIT - - --- - - Copyright 2020 The Institute for Ethical AI & Machine Learning - - Licensed under the Apache License, Version 2.0 (the "License"); - you may not use this file except in compliance with the License. - You may obtain a copy of the License at - - http://www.apache.org/licenses/LICENSE-2.0 - - Unless required by applicable law or agreed to in writing, software - distributed under the License is distributed on an "AS IS" BASIS, - WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - See the License for the specific language governing permissions and - limitations under the License. -*/ - -#ifndef SHADEROP_SHADERLOGISTICREGRESSION_HPP -#define SHADEROP_SHADERLOGISTICREGRESSION_HPP - -namespace kp { -namespace shader_data { -static const unsigned char shaders_glsl_logisticregression_comp_spv[] = { - 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0a, 0x00, 0x08, 0x00, - 0xae, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, - 0x01, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, - 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, - 0x00, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x03, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x01, 0x00, 0x00, 0x00, 0x0f, 0x00, 0x06, 0x00, 0x05, 0x00, 0x00, 0x00, - 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, 0x00, 0x00, 0x00, 0x00, - 0x41, 0x00, 0x00, 0x00, 0x10, 0x00, 0x06, 0x00, 0x04, 0x00, 0x00, 0x00, - 0x11, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, - 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, - 0xc2, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, - 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-#include -#include - -namespace kp { - -/** - * Structured data used in GPU operations. - * - * Tensors are the base building block in Kompute to perform operations across - * GPUs. Each tensor would have a respective Vulkan memory and buffer, which - * would be used to store their respective data. The tensors can be used for GPU - * data storage or transfer. - */ -class Tensor -{ - public: - /** - * Type for tensors created: Device allows memory to be transferred from - * staging buffers. Staging are host memory visible. Storage are device - * visible but are not set up to transfer or receive data (only for shader - * storage). - */ - enum class TensorTypes - { - eDevice = 0, ///< Type is device memory, source and destination - eHost = 1, ///< Type is host memory, source and destination - eStorage = 2, ///< Type is Device memory (only) - }; - - /** - * Default constructor with data provided which would be used to create the - * respective vulkan buffer and memory. - * - * @param data Non-zero-sized vector of data that will be used by the - * tensor - * @param tensorType Type for the tensor which is of type TensorTypes - */ - Tensor(std::shared_ptr physicalDevice, - std::shared_ptr device, - const std::vector& data, - const TensorTypes& tensorType = TensorTypes::eDevice); - - /** - * Destructor which is in charge of freeing vulkan resources unless they - * have been provided externally. - */ - ~Tensor(); - - /** - * Initialiser which calls the initialisation for all the respective tensors - * as well as creates the respective staging tensors. The staging tensors - * would only be created for the tensors of type TensorType::eDevice as - * otherwise there is no need to copy from host memory. - */ - void rebuild(const std::vector& data, - TensorTypes tensorType = TensorTypes::eDevice); - - /** - * Destroys and frees the GPU resources which include the buffer and memory. - */ - void destroy(); - - bool isInit(); - - /** - * Returns the vector of data currently contained by the Tensor. It is - * important to ensure that there is no out-of-sync data with the GPU - * memory. - * - * @return Reference to vector of elements representing the data in the - * tensor. - */ - std::vector& data(); - /** - * Overrides the subscript operator to expose the underlying data's - * subscript operator which in this case would be its underlying - * vector's. - * - * @param i The index where the element will be returned from. - * @return Returns the element in the position requested. - */ - float& operator[](int index); - /** - * Returns the size/magnitude of the Tensor, which will be the total number - * of elements across all dimensions - * - * @return Unsigned integer representing the total number of elements - */ - uint32_t size(); - - /** - * Retrieve the tensor type of the Tensor - * - * @return Tensor type of tensor - */ - TensorTypes tensorType(); - - /** - * Sets / resets the vector data of the tensor. This function does not - * perform any copies into GPU memory and is only performed on the host. - */ - void setData(const std::vector& data); - - /** - * Records a copy from the memory of the tensor provided to the current - * thensor. This is intended to pass memory into a processing, to perform - * a staging buffer transfer, or to gather output (between others). - * - * @param commandBuffer Vulkan Command Buffer to record the commands into - * @param copyFromTensor Tensor to copy the data from - * @param createBarrier Whether to create a barrier that ensures the data is - * copied before further operations. Default is true. - */ - void recordCopyFrom(std::shared_ptr commandBuffer, - std::shared_ptr copyFromTensor, - bool createBarrier); - - /** - * Records a copy from the internal staging memory to the device memory - * using an optional barrier to wait for the operation. This function would - * only be relevant for kp::Tensors of type eDevice. - * - * @param commandBuffer Vulkan Command Buffer to record the commands into - * @param createBarrier Whether to create a barrier that ensures the data is - * copied before further operations. Default is true. - */ - void recordCopyFromStagingToDevice( - std::shared_ptr commandBuffer, - bool createBarrier); - - /** - * Records a copy from the internal device memory to the staging memory - * using an optional barrier to wait for the operation. This function would - * only be relevant for kp::Tensors of type eDevice. - * - * @param commandBuffer Vulkan Command Buffer to record the commands into - * @param createBarrier Whether to create a barrier that ensures the data is - * copied before further operations. Default is true. - */ - void recordCopyFromDeviceToStaging( - std::shared_ptr commandBuffer, - bool createBarrier); - - /** - * Records the buffer memory barrier into the command buffer which - * ensures that relevant data transfers are carried out correctly. - * - * @param commandBuffer Vulkan Command Buffer to record the commands into - * @param srcAccessMask Access flags for source access mask - * @param dstAccessMask Access flags for destination access mask - * @param scrStageMask Pipeline stage flags for source stage mask - * @param dstStageMask Pipeline stage flags for destination stage mask - */ - void recordBufferMemoryBarrier( - std::shared_ptr commandBuffer, - vk::AccessFlagBits srcAccessMask, - vk::AccessFlagBits dstAccessMask, - vk::PipelineStageFlagBits srcStageMask, - vk::PipelineStageFlagBits dstStageMask); - - /** - * Constructs a vulkan descriptor buffer info which can be used to specify - * and reference the underlying buffer component of the tensor without - * exposing it. - * - * @return Descriptor buffer info with own buffer - */ - vk::DescriptorBufferInfo constructDescriptorBufferInfo(); - /** - * Maps data from the Host Visible GPU memory into the data vector. It - * requires the Tensor to be of staging type for it to work. - */ - void mapDataFromHostMemory(); - /** - * Maps data from the data vector into the Host Visible GPU memory. It - * requires the tensor to be of staging type for it to work. - */ - void mapDataIntoHostMemory(); - - private: - // -------------- NEVER OWNED RESOURCES - std::shared_ptr mPhysicalDevice; - std::shared_ptr mDevice; - - // -------------- OPTIONALLY OWNED RESOURCES - std::shared_ptr mPrimaryBuffer; - bool mFreePrimaryBuffer = false; - std::shared_ptr mStagingBuffer; - bool mFreeStagingBuffer = false; - std::shared_ptr mPrimaryMemory; - bool mFreePrimaryMemory = false; - std::shared_ptr mStagingMemory; - bool mFreeStagingMemory = false; - - // -------------- ALWAYS OWNED RESOURCES - std::vector mData; - - TensorTypes mTensorType = TensorTypes::eDevice; - - void allocateMemoryCreateGPUResources(); // Creates the vulkan buffer - void createBuffer(std::shared_ptr buffer, - vk::BufferUsageFlags bufferUsageFlags); - void allocateBindMemory(std::shared_ptr buffer, - std::shared_ptr memory, - vk::MemoryPropertyFlags memoryPropertyFlags); - void copyBuffer(std::shared_ptr commandBuffer, - std::shared_ptr bufferFrom, - std::shared_ptr bufferTo, - vk::DeviceSize bufferSize, - vk::BufferCopy copyRegion, - bool createBarrier); - - // Private util functions - vk::BufferUsageFlags getPrimaryBufferUsageFlags(); - vk::MemoryPropertyFlags getPrimaryMemoryPropertyFlags(); - vk::BufferUsageFlags getStagingBufferUsageFlags(); - vk::MemoryPropertyFlags getStagingMemoryPropertyFlags(); - uint64_t memorySize(); -}; - -} // End namespace kp - -namespace kp { - -/** - Abstraction for compute shaders that are run on top of tensors grouped via - ParameterGroups (which group descriptorsets) -*/ -class Algorithm -{ -public: - - /** - * Default constructor for Algorithm - * - * @param device The Vulkan device to use for creating resources - * @param commandBuffer The vulkan command buffer to bind the pipeline and - * shaders - */ - Algorithm( - std::shared_ptr device, - const std::vector>& tensors = {}, - const std::vector& spirv = {}, - const Workgroup& workgroup = {}, - const Constants& specializationConstants = {}, - const Constants& pushConstants = {}); - - /** - * Initialiser for the shader data provided to the algorithm as well as - * tensor parameters that will be used in shader. - * - * @param shaderFileData The bytes in spir-v format of the shader - * @tensorParams The Tensors to be used in the Algorithm / shader for - * @specalizationInstalces The specialization parameters to pass to the function - * processing - */ - void rebuild( - const std::vector>& tensors = {}, - const std::vector& spirv = {}, - const Workgroup& workgroup = {}, - const Constants& specializationConstants = {}, - const Constants& pushConstants = {}); - - /** - * Destructor for Algorithm which is responsible for freeing and desroying - * respective pipelines and owned parameter groups. - */ - ~Algorithm(); - - /** - * Records the dispatch function with the provided template parameters or - * alternatively using the size of the tensor by default. - * - * @param x Layout X dispatch value - * @param y Layout Y dispatch value - * @param z Layout Z dispatch value - */ - void recordDispatch(std::shared_ptr commandBuffer); - - bool isInit(); - - void setWorkgroup(const Workgroup& workgroup, uint32_t minSize = 1); - - const Workgroup& getWorkgroup(); - const Constants& getSpecializationConstants(); - const Constants& getPushConstants(); - const std::vector>& getTensors(); - - void destroy(); - -private: - // -------------- NEVER OWNED RESOURCES - std::shared_ptr mDevice; - std::vector> mTensors; - - // -------------- OPTIONALLY OWNED RESOURCES - std::shared_ptr mDescriptorSetLayout; - bool mFreeDescriptorSetLayout = false; - std::shared_ptr mDescriptorPool; - bool mFreeDescriptorPool = false; - std::shared_ptr mDescriptorSet; - bool mFreeDescriptorSet = false; - std::shared_ptr mShaderModule; - bool mFreeShaderModule = false; - std::shared_ptr mPipelineLayout; - bool mFreePipelineLayout = false; - std::shared_ptr mPipelineCache; - bool mFreePipelineCache = false; - std::shared_ptr mPipeline; - bool mFreePipeline = false; - - // -------------- ALWAYS OWNED RESOURCES - std::vector mSpirv; - Constants mSpecializationConstants; - Constants mPushConstants; - Workgroup mWorkgroup; - - bool mIsInit; - - // Create util functions - void createShaderModule(); - void createPipeline(); - - // Parameters - void createParameters(); -}; - -} // End namespace kp - -namespace kp { - -/** - * Base Operation which provides the high level interface that Kompute - * operations implement in order to perform a set of actions in the GPU. - * - * Operations can perform actions on tensors, and optionally can also own an - * Algorithm with respective parameters. kp::Operations with kp::Algorithms - * would inherit from kp::OpBaseAlgo. - */ -class OpBase -{ - public: - - /** - * Default destructor for OpBase class. This OpBase destructor class should - * always be called to destroy and free owned resources unless it is - * intended to destroy the resources in the parent class. - */ - virtual ~OpBase() - { - KP_LOG_DEBUG("Kompute OpBase destructor started"); - } - - /** - * The record function is intended to only send a record command or run - * commands that are expected to record operations that are to be submitted - * as a batch into the GPU. - */ - virtual void record(std::shared_ptr commandBuffer) = 0; - - /** - * Pre eval is called before the Sequence has called eval and submitted the commands to - * the GPU for processing, and can be used to perform any per-eval setup steps - * required as the computation iteration begins. It's worth noting that - * there are situations where eval can be called multiple times, so the - * resources that are created should be idempotent in case it's called multiple - * times in a row. - */ - virtual void preEval() = 0; - - /** - * Post eval is called after the Sequence has called eval and submitted the commands to - * the GPU for processing, and can be used to perform any tear-down steps - * required as the computation iteration finishes. It's worth noting that - * there are situations where eval can be called multiple times, so the - * resources that are destroyed should not require a re-init unless explicitly - * provided by the user. - */ - virtual void postEval() = 0; -}; - -} // End namespace kp - -namespace kp { - -/** - * Container of operations that can be sent to GPU as batch - */ -class Sequence: public std::enable_shared_from_this -{ - public: - /** - * Main constructor for sequence which requires core vulkan components to - * generate all dependent resources. - * - * @param physicalDevice Vulkan physical device - * @param device Vulkan logical device - * @param computeQueue Vulkan compute queue - * @param queueIndex Vulkan compute queue index in device - */ - Sequence(std::shared_ptr physicalDevice, - std::shared_ptr device, - std::shared_ptr computeQueue, - uint32_t queueIndex); - /** - * Destructor for sequence which is responsible for cleaning all subsequent - * owned operations. - */ - ~Sequence(); - - /** - */ - std::shared_ptr record(std::shared_ptr op); - - /** - * Record function for operation to be added to the GPU queue in batch. This - * template requires classes to be derived from the OpBase class. This - * function also requires the Sequence to be recording, otherwise it will - * not be able to add the operation. - * - * @param tensors Vector of tensors to use for the operation - * @param TArgs Template parameters that are used to initialise operation - * which allows for extensible configurations on initialisation. - */ - template - std::shared_ptr - record(std::vector> tensors, TArgs&&... params) - { - KP_LOG_DEBUG("Kompute Sequence record function started"); - - static_assert(std::is_base_of::value, - "Kompute Sequence record(...) template only valid with " - "OpBase derived classes"); - - KP_LOG_DEBUG("Kompute Sequence creating OpBase derived class instance"); - std::shared_ptr op{ - new T(tensors, std::forward(params)...) }; - - return this->record(op); - } - template - std::shared_ptr - record(std::shared_ptr algorithm, TArgs&&... params) - { - KP_LOG_DEBUG("Kompute Sequence record function started"); - - static_assert(std::is_base_of::value, - "Kompute Sequence record(...) template only valid with " - "OpBase derived classes"); - - KP_LOG_DEBUG("Kompute Sequence creating OpBase derived class instance"); - std::shared_ptr op{ - new T(algorithm, std::forward(params)...) }; - - return this->record(op); - } - - /** - * Eval sends all the recorded and stored operations in the vector of - * operations into the gpu as a submit job with a barrier. - * - * @return shared_ptr of the Sequence class itself - */ - std::shared_ptr eval(); - - std::shared_ptr eval(std::shared_ptr op); - - /** - * Eval sends all the recorded and stored operations in the vector of - * operations into the gpu as a submit job with a barrier. - * - * @return shared_ptr of the Sequence class itself - */ - // TODO: Aim to have only a single function with tensors/algorithm - template - std::shared_ptr - eval(std::vector> tensors, TArgs&&... params) - { - KP_LOG_DEBUG("Kompute Sequence record function started"); - - static_assert(std::is_base_of::value, - "Kompute Sequence record(...) template only valid with " - "OpBase derived classes"); - - KP_LOG_DEBUG("Kompute Sequence creating OpBase derived class instance"); - std::shared_ptr op{ - new T(tensors, std::forward(params)...) }; - - // TODO: Aim to be able to handle errors when returning without throw except - return this->eval(op); - } - // Needded as otherise can't use initialiser list - template - std::shared_ptr - eval(std::shared_ptr algorithm, TArgs&&... params) - { - KP_LOG_DEBUG("Kompute Sequence record function started"); - - static_assert(std::is_base_of::value, - "Kompute Sequence record(...) template only valid with " - "OpBase derived classes"); - - KP_LOG_DEBUG("Kompute Sequence creating OpBase derived class instance"); - std::shared_ptr op{ - new T(algorithm, std::forward(params)...) }; - - return this->eval(op); - } - - /** - * Eval Async sends all the recorded and stored operations in the vector of - * operations into the gpu as a submit job with a barrier. EvalAwait() must - * be called after to ensure the sequence is terminated correctly. - * - * @return Boolean stating whether execution was successful. - */ - std::shared_ptr evalAsync(); - std::shared_ptr evalAsync(std::shared_ptr op); - - /** - * Eval sends all the recorded and stored operations in the vector of - * operations into the gpu as a submit job with a barrier. - * - * @return shared_ptr of the Sequence class itself - */ - template - std::shared_ptr - evalAsync(std::vector> tensors, TArgs&&... params) - { - KP_LOG_DEBUG("Kompute Sequence record function started"); - - static_assert(std::is_base_of::value, - "Kompute Sequence record(...) template only valid with " - "OpBase derived classes"); - - KP_LOG_DEBUG("Kompute Sequence creating OpBase derived class instance"); - std::shared_ptr op{ - new T(tensors, std::forward(params)...) }; - - return this->evalAsync(op); - } - // Needed as otherwise it's not possible to use initializer lists - template - std::shared_ptr - evalAsync(std::shared_ptr algorithm, TArgs&&... params) - { - KP_LOG_DEBUG("Kompute Sequence record function started"); - - static_assert(std::is_base_of::value, - "Kompute Sequence record(...) template only valid with " - "OpBase derived classes"); - - KP_LOG_DEBUG("Kompute Sequence creating OpBase derived class instance"); - std::shared_ptr op{ - new T(algorithm, std::forward(params)...) }; - - return this->evalAsync(op); - } - - /** - * Eval Await waits for the fence to finish processing and then once it - * finishes, it runs the postEval of all operations. - * - * @param waitFor Number of milliseconds to wait before timing out. - * @return Boolean stating whether execution was successful. - */ - std::shared_ptr evalAwait(uint64_t waitFor = UINT64_MAX); - - /** - * Clear function clears all operations currently recorded and starts recording again. - */ - void clear(); - - /** - * Begins recording commands for commands to be submitted into the command - * buffer. - * - * @return Boolean stating whether execution was successful. - */ - void begin(); - - /** - * Ends the recording and stops recording commands when the record command - * is sent. - * - * @return Boolean stating whether execution was successful. - */ - void end(); - - /** - * Returns true if the sequence is currently in recording activated. - * - * @return Boolean stating if recording ongoing. - */ - bool isRecording(); - - bool isInit(); - - /** - * Returns true if the sequence is currently running - mostly used for async - * workloads. - * - * @return Boolean stating if currently running. - */ - bool isRunning(); - - /** - * Destroys and frees the GPU resources which include the buffer and memory - * and sets the sequence as init=False. - */ - void destroy(); - - private: - // -------------- NEVER OWNED RESOURCES - std::shared_ptr mPhysicalDevice = nullptr; - std::shared_ptr mDevice = nullptr; - std::shared_ptr mComputeQueue = nullptr; - uint32_t mQueueIndex = -1; - - // -------------- OPTIONALLY OWNED RESOURCES - std::shared_ptr mCommandPool = nullptr; - bool mFreeCommandPool = false; - std::shared_ptr mCommandBuffer = nullptr; - bool mFreeCommandBuffer = false; - - // -------------- ALWAYS OWNED RESOURCES - vk::Fence mFence; - std::vector> mOperations; - - // State - bool mRecording = false; - bool mIsRunning = false; - - // Create functions - void createCommandPool(); - void createCommandBuffer(); -}; - -} // End namespace kp - -namespace kp { - -/** - Operation that syncs tensor's device by mapping local data into the device memory. For TensorTypes::eDevice it will use a record operation for the memory to be syncd into GPU memory which means that the operation will be done in sync with GPU commands. For TensorTypes::eStaging it will only map the data into host memory which will happen during preEval before the recorded commands are dispatched. This operation won't have any effect on TensorTypes::eStaging. -*/ -class OpTensorSyncDevice : public OpBase -{ - public: - /** - * Default constructor with parameters that provides the core vulkan resources and the tensors that will be used in the operation. The tensos provided cannot be of type TensorTypes::eStorage. - * - * @param physicalDevice Vulkan physical device used to find device queues - * @param device Vulkan logical device for passing to Algorithm - * @param commandBuffer Vulkan Command Buffer to record commands into - * @param tensors Tensors that will be used to create in operation. - */ - OpTensorSyncDevice(const std::vector>& tensors); - - /** - * Default destructor. This class does not manage memory so it won't be expecting the parent to perform a release. - */ - ~OpTensorSyncDevice() override; - - /** - * For device tensors, it records the copy command for the tensor to copy the data from its staging to device memory. - */ - void record(std::shared_ptr commandBuffer) override; - - /** - * Does not perform any preEval commands. - */ - virtual void preEval() override; - - /** - * Does not perform any postEval commands. - */ - virtual void postEval() override; - - private: - // -------------- ALWAYS OWNED RESOURCES - std::vector> mTensors; -}; - -} // End namespace kp - -#define KP_DEFAULT_SESSION "DEFAULT" - -namespace kp { - -/** - Base orchestrator which creates and manages device and child components -*/ -class Manager -{ - public: - /** - Base constructor and default used which creates the base resources - including choosing the device 0 by default. - */ - Manager(); - - /** - * Similar to base constructor but allows the user to provide the device - * they would like to create the resources on. - * - * @param physicalDeviceIndex The index of the physical device to use - * @param manageResources (Optional) Whether to manage the memory of the - * resources created and destroy when the manager is destroyed. - * @param familyQueueIndices (Optional) List of queue indices to add for - * explicit allocation - * @param totalQueues The total number of compute queues to create. - */ - Manager(uint32_t physicalDeviceIndex, - const std::vector& familyQueueIndices = {}); - - /** - * Manager constructor which allows your own vulkan application to integrate - * with the vulkan kompute use. - * - * @param instance Vulkan compute instance to base this application - * @param physicalDevice Vulkan physical device to use for application - * @param device Vulkan logical device to use for all base resources - * @param physicalDeviceIndex Index for vulkan physical device used - */ - Manager(std::shared_ptr instance, - std::shared_ptr physicalDevice, - std::shared_ptr device); - - /** - * Manager destructor which would ensure all owned resources are destroyed - * unless explicitly stated that resources should not be destroyed or freed. - */ - ~Manager(); - - /** - * Get or create a managed Sequence that will be contained by this manager. - * If the named sequence does not currently exist, it would be created and - * initialised. - * - * @param sequenceName The name for the named sequence to be retrieved or - * created - * @param queueIndex The queue to use from the available queues - * @return Shared pointer to the manager owned sequence resource - */ - std::shared_ptr sequence(uint32_t queueIndex = 0); - - /** - * Function that simplifies the common workflow of tensor creation and - * initialization. It will take the constructor parameters for a Tensor - * and will will us it to create a new Tensor and then create it. The - * tensor memory will then be managed and owned by the manager. - * - * @param data The data to initialize the tensor with - * @param tensorType The type of tensor to initialize - * @param syncDataToGPU Whether to sync the data to GPU memory - * @returns Initialized Tensor with memory Syncd to GPU device - */ - std::shared_ptr tensor( - const std::vector& data, - Tensor::TensorTypes tensorType = Tensor::TensorTypes::eDevice, - bool syncDataToGPU = true); - - std::shared_ptr algorithm( - const std::vector>& tensors = {}, - const std::vector& spirv = {}, - const Workgroup& workgroup = {}, - const Constants& specializationConstants = {}, - const Constants& pushConstants = {}); - - void destroy(); - void clear(); - - private: - // -------------- OPTIONALLY OWNED RESOURCES - std::shared_ptr mInstance = nullptr; - bool mFreeInstance = false; - std::shared_ptr mPhysicalDevice = nullptr; - std::shared_ptr mDevice = nullptr; - bool mFreeDevice = false; - - // -------------- ALWAYS OWNED RESOURCES - std::vector> mManagedTensors; - std::vector> mManagedSequences; - std::vector> mManagedAlgorithms; - - std::vector mComputeQueueFamilyIndices; - std::vector> mComputeQueues; - - bool mManageResources = false; - -#if DEBUG -#ifndef KOMPUTE_DISABLE_VK_DEBUG_LAYERS - vk::DebugReportCallbackEXT mDebugReportCallback; - vk::DispatchLoaderDynamic mDebugDispatcher; -#endif -#endif - - // Create functions - void createInstance(); - void createDevice(const std::vector& familyQueueIndices = {}, uint32_t hysicalDeviceIndex = 0); -}; - -} // End namespace kp - -#include - -namespace kp { - -/** - * Operation that provides a general abstraction that simplifies the use of - * algorithm and parameter components which can be used with shaders. - * By default it enables the user to provide a dynamic number of tensors - * which are then passed as inputs. - */ -class OpAlgoDispatch : public OpBase -{ - public: - - OpAlgoDispatch(const std::shared_ptr& algorithm, bool skipAlgoInit = false); - - /** - * Default destructor, which is in charge of destroying the algorithm - * components but does not destroy the underlying tensors - */ - virtual ~OpAlgoDispatch() override; - - /** - * This records the commands that are to be sent to the GPU. This includes - * the barriers that ensure the memory has been copied before going in and - * out of the shader, as well as the dispatch operation that sends the - * shader processing to the gpu. This function also records the GPU memory - * copy of the output data for the staging buffer so it can be read by the - * host. - */ - virtual void record(std::shared_ptr commandBuffer) override; - - /** - * Does not perform any preEval commands. - */ - virtual void preEval() override; - - /** - * Executes after the recorded commands are submitted, and performs a copy - * of the GPU Device memory into the staging buffer so the output data can - * be retrieved. - */ - virtual void postEval() override; - -private: - // -------------- ALWAYS OWNED RESOURCES - std::shared_ptr mAlgorithm; -}; - -} // End namespace kp - -namespace kp { - -/** - * Operation that performs multiplication on two tensors and outpus on third - * tensor. - */ -class OpMult : public OpAlgoDispatch -{ - public: - - /** - * Default constructor with parameters that provides the bare minimum - * requirements for the operations to be able to create and manage their - * sub-components. - * - * @param physicalDevice Vulkan physical device used to find device queues - * @param device Vulkan logical device for passing to Algorithm - * @param commandBuffer Vulkan Command Buffer to record commands into - * @param tensors Tensors that are to be used in this operation - * @param komputeWorkgroup Optional parameter to specify the layout for processing - */ - OpMult(std::vector> tensors, std::shared_ptr algorithm) - : OpAlgoDispatch(algorithm, true) - { - KP_LOG_DEBUG("Kompute OpMult constructor with params"); - - if (tensors.size() != 3) { - throw std::runtime_error("Kompute OpMult expected 3 tensors but got " + tensors.size()); - } - - std::vector spirv( - (uint32_t*)shader_data::shaders_glsl_opmult_comp_spv, - (uint32_t*)(shader_data::shaders_glsl_opmult_comp_spv + - kp::shader_data::shaders_glsl_opmult_comp_spv_len)); - - algorithm->rebuild(tensors, spirv); - } - - /** - * Default destructor, which is in charge of destroying the algorithm - * components but does not destroy the underlying tensors - */ - virtual ~OpMult() override { - KP_LOG_DEBUG("Kompute OpMult destructor started"); - } -}; - -} // End namespace kp - -namespace kp { - -/** - Operation that copies the data from the first tensor to the rest of the tensors provided, using a record command for all the vectors. This operation does not own/manage the memory of the tensors passed to it. The operation must only receive tensors of type -*/ -class OpTensorCopy : public OpBase -{ - public: - /** - * Default constructor with parameters that provides the core vulkan resources and the tensors that will be used in the operation. - * - * @param physicalDevice Vulkan physical device used to find device queues - * @param device Vulkan logical device for passing to Algorithm - * @param commandBuffer Vulkan Command Buffer to record commands into - * @param tensors Tensors that will be used to create in operation. - */ - OpTensorCopy(const std::vector>& tensors); - - /** - * Default destructor. This class does not manage memory so it won't be expecting the parent to perform a release. - */ - ~OpTensorCopy() override; - - /** - * Records the copy commands from the first tensor into all the other tensors provided. Also optionally records a barrier. - */ - void record(std::shared_ptr commandBuffer) override; - - /** - * Does not perform any preEval commands. - */ - virtual void preEval() override; - - /** - * Copies the local vectors for all the tensors to sync the data with the gpu. - */ - virtual void postEval() override; - - private: - // -------------- ALWAYS OWNED RESOURCES - std::vector> mTensors; -}; - -} // End namespace kp - -namespace kp { - -/** - Operation that syncs tensor's local memory by mapping device data into the local CPU memory. For TensorTypes::eDevice it will use a record operation for the memory to be syncd into GPU memory which means that the operation will be done in sync with GPU commands. For TensorTypes::eStaging it will only map the data into host memory which will happen during preEval before the recorded commands are dispatched. This operation won't have any effect on TensorTypes::eStaging. -*/ -class OpTensorSyncLocal : public OpBase -{ - public: - /** - * Default constructor with parameters that provides the core vulkan resources and the tensors that will be used in the operation. The tensors provided cannot be of type TensorTypes::eStorage. - * - * @param physicalDevice Vulkan physical device used to find device queues - * @param device Vulkan logical device for passing to Algorithm - * @param commandBuffer Vulkan Command Buffer to record commands into - * @param tensors Tensors that will be used to create in operation. - */ - OpTensorSyncLocal(const std::vector>& tensors); - - /** - * Default destructor. This class does not manage memory so it won't be expecting the parent to perform a release. - */ - ~OpTensorSyncLocal() override; - - /** - * For device tensors, it records the copy command for the tensor to copy the data from its device to staging memory. - */ - void record(std::shared_ptr commandBuffer) override; - - /** - * Does not perform any preEval commands. - */ - virtual void preEval() override; - - /** - * For host tensors it performs the map command from the host memory into local memory. - */ - virtual void postEval() override; - - private: - // -------------- ALWAYS OWNED RESOURCES - std::vector> mTensors; -}; - -} // End namespace kp +#pragma once +/* + THIS FILE HAS BEEN AUTOMATICALLY GENERATED - DO NOT EDIT + + --- + + Copyright 2020 The Institute for Ethical AI & Machine Learning + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. +*/ + +#ifndef SHADEROP_SHADEROPMULT_HPP +#define SHADEROP_SHADEROPMULT_HPP + +namespace kp { +namespace shader_data { +static const unsigned char shaders_glsl_opmult_comp_spv[] = { + 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x08, 0x00, 0x08, 0x00, + 0x2e, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0x01, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, + 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, + 0x00, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x03, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x01, 0x00, 0x00, 0x00, 0x0f, 0x00, 0x06, 0x00, 0x05, 0x00, 0x00, 0x00, + 0x04, 0x00, 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the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. +*/ + +#ifndef SHADEROP_SHADERLOGISTICREGRESSION_HPP +#define SHADEROP_SHADERLOGISTICREGRESSION_HPP + +namespace kp { +namespace shader_data { +static const unsigned char shaders_glsl_logisticregression_comp_spv[] = { + 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x08, 0x00, 0x08, 0x00, + 0xae, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0x01, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, + 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, + 0x00, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x03, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x01, 0x00, 0x00, 0x00, 0x0f, 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0x00, + 0x36, 0x00, 0x00, 0x00, 0x81, 0x00, 0x05, 0x00, 0x06, 0x00, 0x00, 0x00, + 0x38, 0x00, 0x00, 0x00, 0x31, 0x00, 0x00, 0x00, 0x37, 0x00, 0x00, 0x00, + 0x7f, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x39, 0x00, 0x00, 0x00, + 0x38, 0x00, 0x00, 0x00, 0xfe, 0x00, 0x02, 0x00, 0x39, 0x00, 0x00, 0x00, + 0x38, 0x00, 0x01, 0x00 +}; +static const unsigned int shaders_glsl_logisticregression_comp_spv_len = 4816; +} +} +#endif // define SHADEROP_SHADERLOGISTICREGRESSION_HPP + +#if VK_USE_PLATFORM_ANDROID_KHR +#include +#include +// VK_NO_PROTOTYPES required before vulkan import but after wrapper.hpp +#undef VK_NO_PROTOTYPES +static const char* KOMPUTE_LOG_TAG = "KomputeLog"; +#endif + +#include + +#include + +// Typedefs to simplify interaction with core types +namespace kp { +typedef std::array Workgroup; +typedef std::vector Constants; +} + +// Must be after vulkan is included +#ifndef KOMPUTE_VK_API_VERSION +#ifndef KOMPUTE_VK_API_MAJOR_VERSION +#define KOMPUTE_VK_API_MAJOR_VERSION 1 +#endif // KOMPUTE_VK_API_MAJOR_VERSION +#ifndef KOMPUTE_VK_API_MINOR_VERSION +#define KOMPUTE_VK_API_MINOR_VERSION 1 +#endif // KOMPUTE_VK_API_MINOR_VERSION +#define KOMPUTE_VK_API_VERSION \ + VK_MAKE_VERSION( \ + KOMPUTE_VK_API_MAJOR_VERSION, KOMPUTE_VK_API_MINOR_VERSION, 0) +#endif // KOMPUTE_VK_API_VERSION + +// SPDLOG_ACTIVE_LEVEL must be defined before spdlog.h import +#ifndef SPDLOG_ACTIVE_LEVEL +#if DEBUG +#define SPDLOG_ACTIVE_LEVEL SPDLOG_LEVEL_DEBUG +#else +#define SPDLOG_ACTIVE_LEVEL SPDLOG_LEVEL_INFO +#endif +#endif + +#if defined(KOMPUTE_BUILD_PYTHON) +#include +namespace py = pybind11; +// from python/src/main.cpp +extern py::object kp_debug, kp_info, kp_warning, kp_error; +#endif + +#ifndef KOMPUTE_LOG_OVERRIDE +#if KOMPUTE_ENABLE_SPDLOG +#include +#define KP_LOG_DEBUG(...) SPDLOG_DEBUG(__VA_ARGS__) +#define KP_LOG_INFO(...) SPDLOG_INFO(__VA_ARGS__) +#define KP_LOG_WARN(...) SPDLOG_WARN(__VA_ARGS__) +#define KP_LOG_ERROR(...) SPDLOG_ERROR(__VA_ARGS__) +#else +#include +#if SPDLOG_ACTIVE_LEVEL > 1 +#define KP_LOG_DEBUG(...) +#else +#if defined(VK_USE_PLATFORM_ANDROID_KHR) +#define KP_LOG_DEBUG(...) \ + ((void)__android_log_print(ANDROID_LOG_DEBUG, KOMPUTE_LOG_TAG, fmt::format(__VA_ARGS__))) +#elif defined(KOMPUTE_BUILD_PYTHON) +#define KP_LOG_DEBUG(...) kp_debug(fmt::format(__VA_ARGS__)) +#else +#define KP_LOG_DEBUG(...) fmt::print("[{} {}] [debug] [{}:{}] {}\n", __DATE__, __TIME__, __FILE__, __LINE__, fmt::format(__VA_ARGS__)) +#endif // VK_USE_PLATFORM_ANDROID_KHR +#endif // SPDLOG_ACTIVE_LEVEL > 1 + +#if SPDLOG_ACTIVE_LEVEL > 2 +#define KP_LOG_INFO(...) +#else +#if defined(VK_USE_PLATFORM_ANDROID_KHR) +#define KP_LOG_INFO(...) \ + ((void)__android_log_print(ANDROID_LOG_INFO, KOMPUTE_LOG_TAG, fmt::format(__VA_ARGS__))) +#elif defined(KOMPUTE_BUILD_PYTHON) +#define KP_LOG_INFO(...) kp_info(fmt::format(__VA_ARGS__)) +#else +#define KP_LOG_INFO(...) fmt::print("[{} {}] [debug] [{}:{}] {}\n", __DATE__, __TIME__, __FILE__, __LINE__, fmt::format(__VA_ARGS__)) +#endif // VK_USE_PLATFORM_ANDROID_KHR +#endif // SPDLOG_ACTIVE_LEVEL > 2 + +#if SPDLOG_ACTIVE_LEVEL > 3 +#define KP_LOG_WARN(...) +#else +#if defined(VK_USE_PLATFORM_ANDROID_KHR) +#define KP_LOG_WARN(...) \ + ((void)__android_log_print(ANDROID_LOG_WARN, KOMPUTE_LOG_TAG, fmt::format(__VA_ARGS__))) +#elif defined(KOMPUTE_BUILD_PYTHON) +#define KP_LOG_WARN(...) kp_warning(fmt::format(__VA_ARGS__)) +#else +#define KP_LOG_WARN(...) fmt::print("[{} {}] [debug] [{}:{}] {}\n", __DATE__, __TIME__, __FILE__, __LINE__, fmt::format(__VA_ARGS__)) +#endif // VK_USE_PLATFORM_ANDROID_KHR +#endif // SPDLOG_ACTIVE_LEVEL > 3 + +#if SPDLOG_ACTIVE_LEVEL > 4 +#define KP_LOG_ERROR(...) +#else +#if defined(VK_USE_PLATFORM_ANDROID_KHR) +#define KP_LOG_ERROR(...) \ + ((void)__android_log_print(ANDROID_LOG_ERROR, KOMPUTE_LOG_TAG, fmt::format(__VA_ARGS__))) +#elif defined(KOMPUTE_BUILD_PYTHON) +#define KP_LOG_ERROR(...) kp_error(fmt::format(__VA_ARGS__)) +#else +#define KP_LOG_ERROR(...) fmt::print("[{} {}] [debug] [{}:{}] {}\n", __DATE__, __TIME__, __FILE__, __LINE__, fmt::format(__VA_ARGS__)) +#endif // VK_USE_PLATFORM_ANDROID_KHR +#endif // SPDLOG_ACTIVE_LEVEL > 4 +#endif // KOMPUTE_SPDLOG_ENABLED +#endif // KOMPUTE_LOG_OVERRIDE + +#if !defined(KOMPUTE_DISABLE_SHADER_UTILS) || !KOMPUTE_DISABLE_SHADER_UTILS +#include +#include + +#include +#include +#include + +namespace kp { + +// The default resource limit for the GLSL compiler, can be overwritten +// Has been adobted by: +// https://github.com/KhronosGroup/glslang/blob/master/StandAlone/ResourceLimits.cpp +const TBuiltInResource defaultResource = { +/* .MaxLights = */ 0, +/* .MaxClipPlanes = */ 0, +/* .MaxTextureUnits = */ 0, +/* .MaxTextureCoords = */ 0, +/* .MaxVertexAttribs = */ 64, +/* .MaxVertexUniformComponents = */ 4096, +/* .MaxVaryingFloats = */ 64, +/* .MaxVertexTextureImageUnits = */ 0, +/* .MaxCombinedTextureImageUnits = */ 0, +/* .MaxTextureImageUnits = */ 0, +/* .MaxFragmentUniformComponents = */ 0, +/* .MaxDrawBuffers = */ 0, +/* .MaxVertexUniformVectors = */ 128, +/* .MaxVaryingVectors = */ 8, +/* .MaxFragmentUniformVectors = */ 0, +/* .MaxVertexOutputVectors = */ 16, +/* .MaxFragmentInputVectors = */ 0, +/* .MinProgramTexelOffset = */ -8, +/* .MaxProgramTexelOffset = */ 7, +/* .MaxClipDistances = */ 8, +/* .MaxComputeWorkGroupCountX = */ 65535, +/* .MaxComputeWorkGroupCountY = */ 65535, +/* .MaxComputeWorkGroupCountZ = */ 65535, +/* .MaxComputeWorkGroupSizeX = */ 1024, +/* .MaxComputeWorkGroupSizeY = */ 1024, +/* .MaxComputeWorkGroupSizeZ = */ 64, +/* .MaxComputeUniformComponents = */ 1024, +/* .MaxComputeTextureImageUnits = */ 16, +/* .MaxComputeImageUniforms = */ 8, +/* .MaxComputeAtomicCounters = */ 8, +/* .MaxComputeAtomicCounterBuffers = */ 1, +/* .MaxVaryingComponents = */ 60, +/* .MaxVertexOutputComponents = */ 64, +/* .MaxGeometryInputComponents = */ 64, +/* .MaxGeometryOutputComponents = */ 128, +/* .MaxFragmentInputComponents = */ 0, +/* .MaxImageUnits = */ 0, +/* .MaxCombinedImageUnitsAndFragmentOutputs = */ 0, +/* .MaxCombinedShaderOutputResources = */ 8, +/* .MaxImageSamples = */ 0, +/* .MaxVertexImageUniforms = */ 0, +/* .MaxTessControlImageUniforms = */ 0, +/* .MaxTessEvaluationImageUniforms = */ 0, +/* .MaxGeometryImageUniforms = */ 0, +/* .MaxFragmentImageUniforms = */ 0, +/* .MaxCombinedImageUniforms = */ 0, +/* .MaxGeometryTextureImageUnits = */ 0, +/* .MaxGeometryOutputVertices = */ 256, +/* .MaxGeometryTotalOutputComponents = */ 1024, +/* .MaxGeometryUniformComponents = */ 1024, +/* .MaxGeometryVaryingComponents = */ 64, +/* .MaxTessControlInputComponents = */ 128, +/* .MaxTessControlOutputComponents = */ 128, +/* .MaxTessControlTextureImageUnits = */ 0, +/* .MaxTessControlUniformComponents = */ 1024, +/* .MaxTessControlTotalOutputComponents = */ 4096, +/* .MaxTessEvaluationInputComponents = */ 128, +/* .MaxTessEvaluationOutputComponents = */ 128, +/* .MaxTessEvaluationTextureImageUnits = */ 16, +/* .MaxTessEvaluationUniformComponents = */ 1024, +/* .MaxTessPatchComponents = */ 120, +/* .MaxPatchVertices = */ 32, +/* .MaxTessGenLevel = */ 64, +/* .MaxViewports = */ 16, +/* .MaxVertexAtomicCounters = */ 0, +/* .MaxTessControlAtomicCounters = */ 0, +/* .MaxTessEvaluationAtomicCounters = */ 0, +/* .MaxGeometryAtomicCounters = */ 0, +/* .MaxFragmentAtomicCounters = */ 0, +/* .MaxCombinedAtomicCounters = */ 8, +/* .MaxAtomicCounterBindings = */ 1, +/* .MaxVertexAtomicCounterBuffers = */ 0, +/* .MaxTessControlAtomicCounterBuffers = */ 0, +/* .MaxTessEvaluationAtomicCounterBuffers = */ 0, +/* .MaxGeometryAtomicCounterBuffers = */ 0, +/* .MaxFragmentAtomicCounterBuffers = */ 0, +/* .MaxCombinedAtomicCounterBuffers = */ 1, +/* .MaxAtomicCounterBufferSize = */ 16384, +/* .MaxTransformFeedbackBuffers = */ 4, +/* .MaxTransformFeedbackInterleavedComponents = */ 64, +/* .MaxCullDistances = */ 8, +/* .MaxCombinedClipAndCullDistances = */ 8, +/* .MaxSamples = */ 4, +/* .maxMeshOutputVerticesNV = */ 256, +/* .maxMeshOutputPrimitivesNV = */ 512, +/* .maxMeshWorkGroupSizeX_NV = */ 32, +/* .maxMeshWorkGroupSizeY_NV = */ 1, +/* .maxMeshWorkGroupSizeZ_NV = */ 1, +/* .maxTaskWorkGroupSizeX_NV = */ 32, +/* .maxTaskWorkGroupSizeY_NV = */ 1, +/* .maxTaskWorkGroupSizeZ_NV = */ 1, +/* .maxMeshViewCountNV = */ 4, +/* .maxDualSourceDrawBuffersEXT = */ 1, + +/* .limits = */ { + /* .nonInductiveForLoops = */ 1, + /* .whileLoops = */ 1, + /* .doWhileLoops = */ 1, + /* .generalUniformIndexing = */ 1, + /* .generalAttributeMatrixVectorIndexing = */ 1, + /* .generalVaryingIndexing = */ 1, + /* .generalSamplerIndexing = */ 1, + /* .generalVariableIndexing = */ 1, + /* .generalConstantMatrixVectorIndexing = */ 1, +}}; + +/** + Shader utily class with functions to compile and process glsl files. +*/ +class Shader { +public: + /** + * Compile multiple sources with optional filenames. Currently this function + * uses the glslang C++ interface which is not thread safe so this funciton + * should not be called from multiple threads concurrently. If you have a + * online shader processing multithreading use-case that can't use offline + * compilation please open an issue. + * + * @param sources A list of raw glsl shaders in string format + * @param files A list of file names respective to each of the sources + * @param entryPoint The function name to use as entry point + * @param definitions List of pairs containing key value definitions + * @param resourcesLimit A list that contains the resource limits for the GLSL compiler + * @return The compiled SPIR-V binary in unsigned int32 format + */ + static std::vector compile_sources( + const std::vector& sources, + const std::vector& files = {}, + const std::string& entryPoint = "main", + std::vector> definitions = {}, + const TBuiltInResource& resources = defaultResource); + + /** + * Compile a single glslang source from string value. Currently this function + * uses the glslang C++ interface which is not thread safe so this funciton + * should not be called from multiple threads concurrently. If you have a + * online shader processing multithreading use-case that can't use offline + * compilation please open an issue. + * + * @param source An individual raw glsl shader in string format + * @param entryPoint The function name to use as entry point + * @param definitions List of pairs containing key value definitions + * @param resourcesLimit A list that contains the resource limits for the GLSL compiler + * @return The compiled SPIR-V binary in unsigned int32 format + */ + static std::vector compile_source( + const std::string& source, + const std::string& entryPoint = "main", + std::vector> definitions = {}, + const TBuiltInResource& resources = defaultResource); + +}; + +} +#endif // DKOMPUTE_DISABLE_SHADER_UTILS + +namespace kp { + +/** + * Structured data used in GPU operations. + * + * Tensors are the base building block in Kompute to perform operations across + * GPUs. Each tensor would have a respective Vulkan memory and buffer, which + * would be used to store their respective data. The tensors can be used for GPU + * data storage or transfer. + */ +class Tensor +{ + public: + /** + * Type for tensors created: Device allows memory to be transferred from + * staging buffers. Staging are host memory visible. Storage are device + * visible but are not set up to transfer or receive data (only for shader + * storage). + */ + enum class TensorTypes + { + eDevice = 0, ///< Type is device memory, source and destination + eHost = 1, ///< Type is host memory, source and destination + eStorage = 2, ///< Type is Device memory (only) + }; + + /** + * Default constructor with data provided which would be used to create the + * respective vulkan buffer and memory. + * + * @param data Non-zero-sized vector of data that will be used by the + * tensor + * @param tensorType Type for the tensor which is of type TensorTypes + */ + Tensor(std::shared_ptr physicalDevice, + std::shared_ptr device, + const std::vector& data, + const TensorTypes& tensorType = TensorTypes::eDevice); + + /** + * Destructor which is in charge of freeing vulkan resources unless they + * have been provided externally. + */ + ~Tensor(); + + /** + * Initialiser which calls the initialisation for all the respective tensors + * as well as creates the respective staging tensors. The staging tensors + * would only be created for the tensors of type TensorType::eDevice as + * otherwise there is no need to copy from host memory. + */ + void rebuild(const std::vector& data, + TensorTypes tensorType = TensorTypes::eDevice); + + /** + * Destroys and frees the GPU resources which include the buffer and memory. + */ + void destroy(); + + bool isInit(); + + /** + * Returns the vector of data currently contained by the Tensor. It is + * important to ensure that there is no out-of-sync data with the GPU + * memory. + * + * @return Reference to vector of elements representing the data in the + * tensor. + */ + std::vector& data(); + /** + * Overrides the subscript operator to expose the underlying data's + * subscript operator which in this case would be its underlying + * vector's. + * + * @param i The index where the element will be returned from. + * @return Returns the element in the position requested. + */ + float& operator[](int index); + /** + * Returns the size/magnitude of the Tensor, which will be the total number + * of elements across all dimensions + * + * @return Unsigned integer representing the total number of elements + */ + uint32_t size(); + + /** + * Retrieve the tensor type of the Tensor + * + * @return Tensor type of tensor + */ + TensorTypes tensorType(); + + /** + * Sets / resets the vector data of the tensor. This function does not + * perform any copies into GPU memory and is only performed on the host. + */ + void setData(const std::vector& data); + + /** + * Records a copy from the memory of the tensor provided to the current + * thensor. This is intended to pass memory into a processing, to perform + * a staging buffer transfer, or to gather output (between others). + * + * @param commandBuffer Vulkan Command Buffer to record the commands into + * @param copyFromTensor Tensor to copy the data from + * @param createBarrier Whether to create a barrier that ensures the data is + * copied before further operations. Default is true. + */ + void recordCopyFrom(std::shared_ptr commandBuffer, + std::shared_ptr copyFromTensor, + bool createBarrier); + + /** + * Records a copy from the internal staging memory to the device memory + * using an optional barrier to wait for the operation. This function would + * only be relevant for kp::Tensors of type eDevice. + * + * @param commandBuffer Vulkan Command Buffer to record the commands into + * @param createBarrier Whether to create a barrier that ensures the data is + * copied before further operations. Default is true. + */ + void recordCopyFromStagingToDevice( + std::shared_ptr commandBuffer, + bool createBarrier); + + /** + * Records a copy from the internal device memory to the staging memory + * using an optional barrier to wait for the operation. This function would + * only be relevant for kp::Tensors of type eDevice. + * + * @param commandBuffer Vulkan Command Buffer to record the commands into + * @param createBarrier Whether to create a barrier that ensures the data is + * copied before further operations. Default is true. + */ + void recordCopyFromDeviceToStaging( + std::shared_ptr commandBuffer, + bool createBarrier); + + /** + * Records the buffer memory barrier into the command buffer which + * ensures that relevant data transfers are carried out correctly. + * + * @param commandBuffer Vulkan Command Buffer to record the commands into + * @param srcAccessMask Access flags for source access mask + * @param dstAccessMask Access flags for destination access mask + * @param scrStageMask Pipeline stage flags for source stage mask + * @param dstStageMask Pipeline stage flags for destination stage mask + */ + void recordBufferMemoryBarrier( + std::shared_ptr commandBuffer, + vk::AccessFlagBits srcAccessMask, + vk::AccessFlagBits dstAccessMask, + vk::PipelineStageFlagBits srcStageMask, + vk::PipelineStageFlagBits dstStageMask); + + /** + * Constructs a vulkan descriptor buffer info which can be used to specify + * and reference the underlying buffer component of the tensor without + * exposing it. + * + * @return Descriptor buffer info with own buffer + */ + vk::DescriptorBufferInfo constructDescriptorBufferInfo(); + /** + * Maps data from the Host Visible GPU memory into the data vector. It + * requires the Tensor to be of staging type for it to work. + */ + void mapDataFromHostMemory(); + /** + * Maps data from the data vector into the Host Visible GPU memory. It + * requires the tensor to be of staging type for it to work. + */ + void mapDataIntoHostMemory(); + + private: + // -------------- NEVER OWNED RESOURCES + std::shared_ptr mPhysicalDevice; + std::shared_ptr mDevice; + + // -------------- OPTIONALLY OWNED RESOURCES + std::shared_ptr mPrimaryBuffer; + bool mFreePrimaryBuffer = false; + std::shared_ptr mStagingBuffer; + bool mFreeStagingBuffer = false; + std::shared_ptr mPrimaryMemory; + bool mFreePrimaryMemory = false; + std::shared_ptr mStagingMemory; + bool mFreeStagingMemory = false; + + // -------------- ALWAYS OWNED RESOURCES + std::vector mData; + + TensorTypes mTensorType = TensorTypes::eDevice; + + void allocateMemoryCreateGPUResources(); // Creates the vulkan buffer + void createBuffer(std::shared_ptr buffer, + vk::BufferUsageFlags bufferUsageFlags); + void allocateBindMemory(std::shared_ptr buffer, + std::shared_ptr memory, + vk::MemoryPropertyFlags memoryPropertyFlags); + void copyBuffer(std::shared_ptr commandBuffer, + std::shared_ptr bufferFrom, + std::shared_ptr bufferTo, + vk::DeviceSize bufferSize, + vk::BufferCopy copyRegion, + bool createBarrier); + + // Private util functions + vk::BufferUsageFlags getPrimaryBufferUsageFlags(); + vk::MemoryPropertyFlags getPrimaryMemoryPropertyFlags(); + vk::BufferUsageFlags getStagingBufferUsageFlags(); + vk::MemoryPropertyFlags getStagingMemoryPropertyFlags(); + uint64_t memorySize(); +}; + +} // End namespace kp + +namespace kp { + +/** + Abstraction for compute shaders that are run on top of tensors grouped via + ParameterGroups (which group descriptorsets) +*/ +class Algorithm +{ +public: + + /** + * Default constructor for Algorithm + * + * @param device The Vulkan device to use for creating resources + * @param commandBuffer The vulkan command buffer to bind the pipeline and + * shaders + */ + Algorithm( + std::shared_ptr device, + const std::vector>& tensors = {}, + const std::vector& spirv = {}, + const Workgroup& workgroup = {}, + const Constants& specializationConstants = {}, + const Constants& pushConstants = {}); + + /** + * Initialiser for the shader data provided to the algorithm as well as + * tensor parameters that will be used in shader. + * + * @param shaderFileData The bytes in spir-v format of the shader + * @tensorParams The Tensors to be used in the Algorithm / shader for + * @specalizationInstalces The specialization parameters to pass to the function + * processing + */ + void rebuild( + const std::vector>& tensors = {}, + const std::vector& spirv = {}, + const Workgroup& workgroup = {}, + const Constants& specializationConstants = {}, + const Constants& pushConstants = {}); + + /** + * Destructor for Algorithm which is responsible for freeing and desroying + * respective pipelines and owned parameter groups. + */ + ~Algorithm(); + + /** + * Records the dispatch function with the provided template parameters or + * alternatively using the size of the tensor by default. + * + * @param x Layout X dispatch value + * @param y Layout Y dispatch value + * @param z Layout Z dispatch value + */ + void recordDispatch(std::shared_ptr commandBuffer); + + bool isInit(); + + void setWorkgroup(const Workgroup& workgroup, uint32_t minSize = 1); + + const Workgroup& getWorkgroup(); + const Constants& getSpecializationConstants(); + const Constants& getPushConstants(); + const std::vector>& getTensors(); + + void destroy(); + +private: + // -------------- NEVER OWNED RESOURCES + std::shared_ptr mDevice; + std::vector> mTensors; + + // -------------- OPTIONALLY OWNED RESOURCES + std::shared_ptr mDescriptorSetLayout; + bool mFreeDescriptorSetLayout = false; + std::shared_ptr mDescriptorPool; + bool mFreeDescriptorPool = false; + std::shared_ptr mDescriptorSet; + bool mFreeDescriptorSet = false; + std::shared_ptr mShaderModule; + bool mFreeShaderModule = false; + std::shared_ptr mPipelineLayout; + bool mFreePipelineLayout = false; + std::shared_ptr mPipelineCache; + bool mFreePipelineCache = false; + std::shared_ptr mPipeline; + bool mFreePipeline = false; + + // -------------- ALWAYS OWNED RESOURCES + std::vector mSpirv; + Constants mSpecializationConstants; + Constants mPushConstants; + Workgroup mWorkgroup; + + bool mIsInit; + + // Create util functions + void createShaderModule(); + void createPipeline(); + + // Parameters + void createParameters(); +}; + +} // End namespace kp + +namespace kp { + +/** + * Base Operation which provides the high level interface that Kompute + * operations implement in order to perform a set of actions in the GPU. + * + * Operations can perform actions on tensors, and optionally can also own an + * Algorithm with respective parameters. kp::Operations with kp::Algorithms + * would inherit from kp::OpBaseAlgo. + */ +class OpBase +{ + public: + + /** + * Default destructor for OpBase class. This OpBase destructor class should + * always be called to destroy and free owned resources unless it is + * intended to destroy the resources in the parent class. + */ + virtual ~OpBase() + { + KP_LOG_DEBUG("Kompute OpBase destructor started"); + } + + /** + * The record function is intended to only send a record command or run + * commands that are expected to record operations that are to be submitted + * as a batch into the GPU. + */ + virtual void record(std::shared_ptr commandBuffer) = 0; + + /** + * Pre eval is called before the Sequence has called eval and submitted the commands to + * the GPU for processing, and can be used to perform any per-eval setup steps + * required as the computation iteration begins. It's worth noting that + * there are situations where eval can be called multiple times, so the + * resources that are created should be idempotent in case it's called multiple + * times in a row. + */ + virtual void preEval() = 0; + + /** + * Post eval is called after the Sequence has called eval and submitted the commands to + * the GPU for processing, and can be used to perform any tear-down steps + * required as the computation iteration finishes. It's worth noting that + * there are situations where eval can be called multiple times, so the + * resources that are destroyed should not require a re-init unless explicitly + * provided by the user. + */ + virtual void postEval() = 0; +}; + +} // End namespace kp + +#include + +namespace kp { + +/** + * Operation that provides a general abstraction that simplifies the use of + * algorithm and parameter components which can be used with shaders. + * By default it enables the user to provide a dynamic number of tensors + * which are then passed as inputs. + */ +class OpAlgoDispatch : public OpBase +{ + public: + + OpAlgoDispatch(const std::shared_ptr& algorithm, bool skipAlgoCheck = false); + + /** + * Default destructor, which is in charge of destroying the algorithm + * components but does not destroy the underlying tensors + */ + virtual ~OpAlgoDispatch() override; + + /** + * This records the commands that are to be sent to the GPU. This includes + * the barriers that ensure the memory has been copied before going in and + * out of the shader, as well as the dispatch operation that sends the + * shader processing to the gpu. This function also records the GPU memory + * copy of the output data for the staging buffer so it can be read by the + * host. + */ + virtual void record(std::shared_ptr commandBuffer) override; + + /** + * Does not perform any preEval commands. + */ + virtual void preEval() override; + + /** + * Executes after the recorded commands are submitted, and performs a copy + * of the GPU Device memory into the staging buffer so the output data can + * be retrieved. + */ + virtual void postEval() override; + +private: + // -------------- ALWAYS OWNED RESOURCES + std::shared_ptr mAlgorithm; +}; + +} // End namespace kp + +namespace kp { + +/** + * Operation that performs multiplication on two tensors and outpus on third + * tensor. + */ +class OpMult : public OpAlgoDispatch +{ + public: + + /** + * Default constructor with parameters that provides the bare minimum + * requirements for the operations to be able to create and manage their + * sub-components. + * + * @param physicalDevice Vulkan physical device used to find device queues + * @param device Vulkan logical device for passing to Algorithm + * @param commandBuffer Vulkan Command Buffer to record commands into + * @param tensors Tensors that are to be used in this operation + * @param komputeWorkgroup Optional parameter to specify the layout for processing + */ + OpMult(std::vector> tensors, std::shared_ptr algorithm) + : OpAlgoDispatch(algorithm, true) + { + KP_LOG_DEBUG("Kompute OpMult constructor with params"); + + if (tensors.size() != 3) { + throw std::runtime_error("Kompute OpMult expected 3 tensors but got " + tensors.size()); + } + + std::vector spirv( + (uint32_t*)shader_data::shaders_glsl_opmult_comp_spv, + (uint32_t*)(shader_data::shaders_glsl_opmult_comp_spv + + kp::shader_data::shaders_glsl_opmult_comp_spv_len)); + + algorithm->rebuild(tensors, spirv); + } + + /** + * Default destructor, which is in charge of destroying the algorithm + * components but does not destroy the underlying tensors + */ + virtual ~OpMult() override { + KP_LOG_DEBUG("Kompute OpMult destructor started"); + } +}; + +} // End namespace kp + +namespace kp { + +/** + Operation that copies the data from the first tensor to the rest of the tensors provided, using a record command for all the vectors. This operation does not own/manage the memory of the tensors passed to it. The operation must only receive tensors of type +*/ +class OpTensorCopy : public OpBase +{ + public: + /** + * Default constructor with parameters that provides the core vulkan resources and the tensors that will be used in the operation. + * + * @param physicalDevice Vulkan physical device used to find device queues + * @param device Vulkan logical device for passing to Algorithm + * @param commandBuffer Vulkan Command Buffer to record commands into + * @param tensors Tensors that will be used to create in operation. + */ + OpTensorCopy(const std::vector>& tensors); + + /** + * Default destructor. This class does not manage memory so it won't be expecting the parent to perform a release. + */ + ~OpTensorCopy() override; + + /** + * Records the copy commands from the first tensor into all the other tensors provided. Also optionally records a barrier. + */ + void record(std::shared_ptr commandBuffer) override; + + /** + * Does not perform any preEval commands. + */ + virtual void preEval() override; + + /** + * Copies the local vectors for all the tensors to sync the data with the gpu. + */ + virtual void postEval() override; + + private: + // -------------- ALWAYS OWNED RESOURCES + std::vector> mTensors; +}; + +} // End namespace kp + +namespace kp { + +/** + Operation that syncs tensor's device by mapping local data into the device memory. For TensorTypes::eDevice it will use a record operation for the memory to be syncd into GPU memory which means that the operation will be done in sync with GPU commands. For TensorTypes::eStaging it will only map the data into host memory which will happen during preEval before the recorded commands are dispatched. This operation won't have any effect on TensorTypes::eStaging. +*/ +class OpTensorSyncDevice : public OpBase +{ + public: + /** + * Default constructor with parameters that provides the core vulkan resources and the tensors that will be used in the operation. The tensos provided cannot be of type TensorTypes::eStorage. + * + * @param physicalDevice Vulkan physical device used to find device queues + * @param device Vulkan logical device for passing to Algorithm + * @param commandBuffer Vulkan Command Buffer to record commands into + * @param tensors Tensors that will be used to create in operation. + */ + OpTensorSyncDevice(const std::vector>& tensors); + + /** + * Default destructor. This class does not manage memory so it won't be expecting the parent to perform a release. + */ + ~OpTensorSyncDevice() override; + + /** + * For device tensors, it records the copy command for the tensor to copy the data from its staging to device memory. + */ + void record(std::shared_ptr commandBuffer) override; + + /** + * Does not perform any preEval commands. + */ + virtual void preEval() override; + + /** + * Does not perform any postEval commands. + */ + virtual void postEval() override; + + private: + // -------------- ALWAYS OWNED RESOURCES + std::vector> mTensors; +}; + +} // End namespace kp + +namespace kp { + +/** + Operation that syncs tensor's local memory by mapping device data into the local CPU memory. For TensorTypes::eDevice it will use a record operation for the memory to be syncd into GPU memory which means that the operation will be done in sync with GPU commands. For TensorTypes::eStaging it will only map the data into host memory which will happen during preEval before the recorded commands are dispatched. This operation won't have any effect on TensorTypes::eStaging. +*/ +class OpTensorSyncLocal : public OpBase +{ + public: + /** + * Default constructor with parameters that provides the core vulkan resources and the tensors that will be used in the operation. The tensors provided cannot be of type TensorTypes::eStorage. + * + * @param physicalDevice Vulkan physical device used to find device queues + * @param device Vulkan logical device for passing to Algorithm + * @param commandBuffer Vulkan Command Buffer to record commands into + * @param tensors Tensors that will be used to create in operation. + */ + OpTensorSyncLocal(const std::vector>& tensors); + + /** + * Default destructor. This class does not manage memory so it won't be expecting the parent to perform a release. + */ + ~OpTensorSyncLocal() override; + + /** + * For device tensors, it records the copy command for the tensor to copy the data from its device to staging memory. + */ + void record(std::shared_ptr commandBuffer) override; + + /** + * Does not perform any preEval commands. + */ + virtual void preEval() override; + + /** + * For host tensors it performs the map command from the host memory into local memory. + */ + virtual void postEval() override; + + private: + // -------------- ALWAYS OWNED RESOURCES + std::vector> mTensors; +}; + +} // End namespace kp + +namespace kp { + +/** + * Container of operations that can be sent to GPU as batch + */ +class Sequence: public std::enable_shared_from_this +{ + public: + /** + * Main constructor for sequence which requires core vulkan components to + * generate all dependent resources. + * + * @param physicalDevice Vulkan physical device + * @param device Vulkan logical device + * @param computeQueue Vulkan compute queue + * @param queueIndex Vulkan compute queue index in device + */ + Sequence(std::shared_ptr physicalDevice, + std::shared_ptr device, + std::shared_ptr computeQueue, + uint32_t queueIndex); + /** + * Destructor for sequence which is responsible for cleaning all subsequent + * owned operations. + */ + ~Sequence(); + + /** + */ + std::shared_ptr record(std::shared_ptr op); + + /** + * Record function for operation to be added to the GPU queue in batch. This + * template requires classes to be derived from the OpBase class. This + * function also requires the Sequence to be recording, otherwise it will + * not be able to add the operation. + * + * @param tensors Vector of tensors to use for the operation + * @param TArgs Template parameters that are used to initialise operation + * which allows for extensible configurations on initialisation. + */ + template + std::shared_ptr + record(std::vector> tensors, TArgs&&... params) + { + KP_LOG_DEBUG("Kompute Sequence record function started"); + + static_assert(std::is_base_of::value, + "Kompute Sequence record(...) template only valid with " + "OpBase derived classes"); + + KP_LOG_DEBUG("Kompute Sequence creating OpBase derived class instance"); + std::shared_ptr op{ + new T(tensors, std::forward(params)...) }; + + return this->record(op); + } + template + std::shared_ptr + record(std::shared_ptr algorithm, TArgs&&... params) + { + KP_LOG_DEBUG("Kompute Sequence record function started"); + + static_assert(std::is_base_of::value, + "Kompute Sequence record(...) template only valid with " + "OpBase derived classes"); + + KP_LOG_DEBUG("Kompute Sequence creating OpBase derived class instance"); + std::shared_ptr op{ + new T(algorithm, std::forward(params)...) }; + + return this->record(op); + } + + /** + * Eval sends all the recorded and stored operations in the vector of + * operations into the gpu as a submit job with a barrier. + * + * @return shared_ptr of the Sequence class itself + */ + std::shared_ptr eval(); + + std::shared_ptr eval(std::shared_ptr op); + + /** + * Eval sends all the recorded and stored operations in the vector of + * operations into the gpu as a submit job with a barrier. + * + * @return shared_ptr of the Sequence class itself + */ + // TODO: Aim to have only a single function with tensors/algorithm + template + std::shared_ptr + eval(std::vector> tensors, TArgs&&... params) + { + KP_LOG_DEBUG("Kompute Sequence record function started"); + + static_assert(std::is_base_of::value, + "Kompute Sequence record(...) template only valid with " + "OpBase derived classes"); + + KP_LOG_DEBUG("Kompute Sequence creating OpBase derived class instance"); + std::shared_ptr op{ + new T(tensors, std::forward(params)...) }; + + // TODO: Aim to be able to handle errors when returning without throw except + return this->eval(op); + } + // Needded as otherise can't use initialiser list + template + std::shared_ptr + eval(std::shared_ptr algorithm, TArgs&&... params) + { + KP_LOG_DEBUG("Kompute Sequence record function started"); + + static_assert(std::is_base_of::value, + "Kompute Sequence record(...) template only valid with " + "OpBase derived classes"); + + KP_LOG_DEBUG("Kompute Sequence creating OpBase derived class instance"); + std::shared_ptr op{ + new T(algorithm, std::forward(params)...) }; + + return this->eval(op); + } + + /** + * Eval Async sends all the recorded and stored operations in the vector of + * operations into the gpu as a submit job with a barrier. EvalAwait() must + * be called after to ensure the sequence is terminated correctly. + * + * @return Boolean stating whether execution was successful. + */ + std::shared_ptr evalAsync(); + std::shared_ptr evalAsync(std::shared_ptr op); + + /** + * Eval sends all the recorded and stored operations in the vector of + * operations into the gpu as a submit job with a barrier. + * + * @return shared_ptr of the Sequence class itself + */ + template + std::shared_ptr + evalAsync(std::vector> tensors, TArgs&&... params) + { + KP_LOG_DEBUG("Kompute Sequence record function started"); + + static_assert(std::is_base_of::value, + "Kompute Sequence record(...) template only valid with " + "OpBase derived classes"); + + KP_LOG_DEBUG("Kompute Sequence creating OpBase derived class instance"); + std::shared_ptr op{ + new T(tensors, std::forward(params)...) }; + + return this->evalAsync(op); + } + // Needed as otherwise it's not possible to use initializer lists + template + std::shared_ptr + evalAsync(std::shared_ptr algorithm, TArgs&&... params) + { + KP_LOG_DEBUG("Kompute Sequence record function started"); + + static_assert(std::is_base_of::value, + "Kompute Sequence record(...) template only valid with " + "OpBase derived classes"); + + KP_LOG_DEBUG("Kompute Sequence creating OpBase derived class instance"); + std::shared_ptr op{ + new T(algorithm, std::forward(params)...) }; + + return this->evalAsync(op); + } + + /** + * Eval Await waits for the fence to finish processing and then once it + * finishes, it runs the postEval of all operations. + * + * @param waitFor Number of milliseconds to wait before timing out. + * @return Boolean stating whether execution was successful. + */ + std::shared_ptr evalAwait(uint64_t waitFor = UINT64_MAX); + + /** + * Clear function clears all operations currently recorded and starts recording again. + */ + void clear(); + + /** + * Begins recording commands for commands to be submitted into the command + * buffer. + * + * @return Boolean stating whether execution was successful. + */ + void begin(); + + /** + * Ends the recording and stops recording commands when the record command + * is sent. + * + * @return Boolean stating whether execution was successful. + */ + void end(); + + /** + * Returns true if the sequence is currently in recording activated. + * + * @return Boolean stating if recording ongoing. + */ + bool isRecording(); + + bool isInit(); + + /** + * Returns true if the sequence is currently running - mostly used for async + * workloads. + * + * @return Boolean stating if currently running. + */ + bool isRunning(); + + /** + * Destroys and frees the GPU resources which include the buffer and memory + * and sets the sequence as init=False. + */ + void destroy(); + + private: + // -------------- NEVER OWNED RESOURCES + std::shared_ptr mPhysicalDevice = nullptr; + std::shared_ptr mDevice = nullptr; + std::shared_ptr mComputeQueue = nullptr; + uint32_t mQueueIndex = -1; + + // -------------- OPTIONALLY OWNED RESOURCES + std::shared_ptr mCommandPool = nullptr; + bool mFreeCommandPool = false; + std::shared_ptr mCommandBuffer = nullptr; + bool mFreeCommandBuffer = false; + + // -------------- ALWAYS OWNED RESOURCES + vk::Fence mFence; + std::vector> mOperations; + + // State + bool mRecording = false; + bool mIsRunning = false; + + // Create functions + void createCommandPool(); + void createCommandBuffer(); +}; + +} // End namespace kp + +#include +#include + +#define KP_DEFAULT_SESSION "DEFAULT" + +namespace kp { + +/** + Base orchestrator which creates and manages device and child components +*/ +class Manager +{ + public: + /** + Base constructor and default used which creates the base resources + including choosing the device 0 by default. + */ + Manager(); + + /** + * Similar to base constructor but allows the user to provide the device + * they would like to create the resources on. + * + * @param physicalDeviceIndex The index of the physical device to use + * @param manageResources (Optional) Whether to manage the memory of the + * resources created and destroy when the manager is destroyed. + * @param familyQueueIndices (Optional) List of queue indices to add for + * explicit allocation + * @param totalQueues The total number of compute queues to create. + */ + Manager(uint32_t physicalDeviceIndex, + const std::vector& familyQueueIndices = {}); + + /** + * Manager constructor which allows your own vulkan application to integrate + * with the vulkan kompute use. + * + * @param instance Vulkan compute instance to base this application + * @param physicalDevice Vulkan physical device to use for application + * @param device Vulkan logical device to use for all base resources + * @param physicalDeviceIndex Index for vulkan physical device used + */ + Manager(std::shared_ptr instance, + std::shared_ptr physicalDevice, + std::shared_ptr device); + + /** + * Manager destructor which would ensure all owned resources are destroyed + * unless explicitly stated that resources should not be destroyed or freed. + */ + ~Manager(); + + /** + * Get or create a managed Sequence that will be contained by this manager. + * If the named sequence does not currently exist, it would be created and + * initialised. + * + * @param sequenceName The name for the named sequence to be retrieved or + * created + * @param queueIndex The queue to use from the available queues + * @return Shared pointer to the manager owned sequence resource + */ + std::shared_ptr sequence(uint32_t queueIndex = 0); + + /** + * Function that simplifies the common workflow of tensor creation and + * initialization. It will take the constructor parameters for a Tensor + * and will will us it to create a new Tensor and then create it. The + * tensor memory will then be managed and owned by the manager. + * + * @param data The data to initialize the tensor with + * @param tensorType The type of tensor to initialize + * @param syncDataToGPU Whether to sync the data to GPU memory + * @returns Initialized Tensor with memory Syncd to GPU device + */ + std::shared_ptr tensor( + const std::vector& data, + Tensor::TensorTypes tensorType = Tensor::TensorTypes::eDevice); + + std::shared_ptr algorithm( + const std::vector>& tensors = {}, + const std::vector& spirv = {}, + const Workgroup& workgroup = {}, + const Constants& specializationConstants = {}, + const Constants& pushConstants = {}); + + void destroy(); + void clear(); + + private: + // -------------- OPTIONALLY OWNED RESOURCES + std::shared_ptr mInstance = nullptr; + bool mFreeInstance = false; + std::shared_ptr mPhysicalDevice = nullptr; + std::shared_ptr mDevice = nullptr; + bool mFreeDevice = false; + + // -------------- ALWAYS OWNED RESOURCES + std::vector> mManagedTensors; + std::vector> mManagedSequences; + std::vector> mManagedAlgorithms; + + std::vector mComputeQueueFamilyIndices; + std::vector> mComputeQueues; + + bool mManageResources = false; + +#if DEBUG +#ifndef KOMPUTE_DISABLE_VK_DEBUG_LAYERS + vk::DebugReportCallbackEXT mDebugReportCallback; + vk::DispatchLoaderDynamic mDebugDispatcher; +#endif +#endif + + // Create functions + void createInstance(); + void createDevice(const std::vector& familyQueueIndices = {}, uint32_t hysicalDeviceIndex = 0); +}; + +} // End namespace kp diff --git a/src/Algorithm.cpp b/src/Algorithm.cpp index 6215dd090..4e532e269 100644 --- a/src/Algorithm.cpp +++ b/src/Algorithm.cpp @@ -126,16 +126,19 @@ Algorithm::destroy() { this->mShaderModule = nullptr; } - if (this->mFreeDescriptorSet) { - KP_LOG_DEBUG("Kompute Algorithm Freeing Descriptor Set"); - if (!this->mDescriptorSet) { - KP_LOG_WARN( - "Kompute Algorithm Error requested to free descriptor set"); - } - this->mDevice->freeDescriptorSets( - *this->mDescriptorPool, 1, this->mDescriptorSet.get()); - this->mDescriptorSet = nullptr; - } + // We don't call freeDescriptorSet as the descriptor pool is not created with + // VK_DESCRIPTOR_POOL_CREATE_FREE_DESCRIPTOR_SET_BIT more at + // (https://www.khronos.org/registry/vulkan/specs/1.0/html/vkspec.html#VUID-vkFreeDescriptorSets-descriptorPool-00312)) + //if (this->mFreeDescriptorSet) { + // KP_LOG_DEBUG("Kompute Algorithm Freeing Descriptor Set"); + // if (!this->mDescriptorSet) { + // KP_LOG_WARN( + // "Kompute Algorithm Error requested to free descriptor set"); + // } + // this->mDevice->freeDescriptorSets( + // *this->mDescriptorPool, 1, this->mDescriptorSet.get()); + // this->mDescriptorSet = nullptr; + //} if (this->mFreeDescriptorSetLayout) { KP_LOG_DEBUG("Kompute Algorithm Destroying Descriptor Set Layout"); diff --git a/src/Manager.cpp b/src/Manager.cpp index ea152f1a8..92ffaea9c 100644 --- a/src/Manager.cpp +++ b/src/Manager.cpp @@ -346,8 +346,7 @@ Manager::createDevice(const std::vector& familyQueueIndices, uint32_t std::shared_ptr Manager::tensor( const std::vector& data, - Tensor::TensorTypes tensorType, - bool syncDataToGPU) + Tensor::TensorTypes tensorType) { KP_LOG_DEBUG("Kompute Manager tensor creation triggered"); diff --git a/src/include/kompute/Manager.hpp b/src/include/kompute/Manager.hpp index 0e97f12fa..f963d5f5a 100644 --- a/src/include/kompute/Manager.hpp +++ b/src/include/kompute/Manager.hpp @@ -7,8 +7,6 @@ #include "kompute/Sequence.hpp" -#include "kompute/operations/OpTensorSyncDevice.hpp" - #define KP_DEFAULT_SESSION "DEFAULT" namespace kp { @@ -83,8 +81,7 @@ class Manager */ std::shared_ptr tensor( const std::vector& data, - Tensor::TensorTypes tensorType = Tensor::TensorTypes::eDevice, - bool syncDataToGPU = true); + Tensor::TensorTypes tensorType = Tensor::TensorTypes::eDevice); std::shared_ptr algorithm( const std::vector>& tensors = {}, diff --git a/src/include/kompute/operations/OpAlgoDispatch.hpp b/src/include/kompute/operations/OpAlgoDispatch.hpp index e61c3166d..d80c6bd91 100644 --- a/src/include/kompute/operations/OpAlgoDispatch.hpp +++ b/src/include/kompute/operations/OpAlgoDispatch.hpp @@ -17,7 +17,7 @@ class OpAlgoDispatch : public OpBase { public: - OpAlgoDispatch(const std::shared_ptr& algorithm, bool skipAlgoInit = false); + OpAlgoDispatch(const std::shared_ptr& algorithm, bool skipAlgoCheck = false); /** * Default destructor, which is in charge of destroying the algorithm diff --git a/src/include/kompute/shaders/shaderlogisticregression.hpp b/src/include/kompute/shaders/shaderlogisticregression.hpp index f456ac1cf..5293a3593 100755 --- a/src/include/kompute/shaders/shaderlogisticregression.hpp +++ b/src/include/kompute/shaders/shaderlogisticregression.hpp @@ -23,411 +23,411 @@ namespace kp { namespace shader_data { -static const unsigned char shaders_glsl_logisticregression_comp_spv[] = { - 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0a, 0x00, 0x08, 0x00, - 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unsigned char shaders_glsl_opmult_comp_spv[] = { - 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0a, 0x00, 0x08, 0x00, - 0x2e, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, - 0x01, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, - 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, - 0x00, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x03, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x01, 0x00, 0x00, 0x00, 0x0f, 0x00, 0x06, 0x00, 0x05, 0x00, 0x00, 0x00, - 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, 0x00, 0x00, 0x00, 0x00, - 0x0b, 0x00, 0x00, 0x00, 0x10, 0x00, 0x06, 0x00, 0x04, 0x00, 0x00, 0x00, - 0x11, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, - 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, - 0xc2, 0x01, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, - 0x6d, 0x61, 0x69, 0x6e, 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x04, 0x00, - 0x08, 0x00, 0x00, 0x00, 0x69, 0x6e, 0x64, 0x65, 0x78, 0x00, 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a/test/compiled_shaders_include/kompute_test/shaders/shadertest_op_custom_shader.hpp +++ b/test/compiled_shaders_include/kompute_test/shaders/shadertest_op_custom_shader.hpp @@ -23,101 +23,101 @@ namespace kp { namespace shader_data { -static const unsigned char test_shaders_glsl_test_op_custom_shader_comp_spv[] = { - 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0a, 0x00, 0x08, 0x00, - 0x27, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, - 0x01, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, - 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, - 0x00, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x03, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x01, 0x00, 0x00, 0x00, 0x0f, 0x00, 0x06, 0x00, 0x05, 0x00, 0x00, 0x00, - 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, 0x00, 0x00, 0x00, 0x00, - 0x0b, 0x00, 0x00, 0x00, 0x10, 0x00, 0x06, 0x00, 0x04, 0x00, 0x00, 0x00, - 0x11, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, - 0x01, 0x00, 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0x00, 0x00, 0x23, 0x00, 0x00, 0x00, 0xfd, 0x00, 0x01, 0x00, - 0x38, 0x00, 0x01, 0x00 -}; -static const unsigned int test_shaders_glsl_test_op_custom_shader_comp_spv_len = 1096; +static const unsigned char test_shaders_glsl_test_op_custom_shader_comp_spv[] = { + 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x08, 0x00, 0x08, 0x00, + 0x27, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, + 0x01, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, + 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, + 0x00, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x03, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x01, 0x00, 0x00, 0x00, 0x0f, 0x00, 0x06, 0x00, 0x05, 0x00, 0x00, 0x00, + 0x04, 0x00, 0x00, 0x00, 0x6d, 0x61, 0x69, 0x6e, 0x00, 0x00, 0x00, 0x00, + 0x0b, 0x00, 0x00, 0x00, 0x10, 0x00, 0x06, 0x00, 0x04, 0x00, 0x00, 0x00, + 0x11, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, + 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x03, 0x00, 0x02, 0x00, 0x00, 0x00, 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0x38, 0x00, 0x01, 0x00 +}; +static const unsigned int test_shaders_glsl_test_op_custom_shader_comp_spv_len = 1096; } } #endif // define SHADEROP_SHADERTEST_OP_CUSTOM_SHADER_HPP diff --git a/test/compiled_shaders_include/kompute_test/shaders/shadertest_workgroup.hpp b/test/compiled_shaders_include/kompute_test/shaders/shadertest_workgroup.hpp index 15d623478..4b0bc4572 100755 --- a/test/compiled_shaders_include/kompute_test/shaders/shadertest_workgroup.hpp +++ b/test/compiled_shaders_include/kompute_test/shaders/shadertest_workgroup.hpp @@ -23,126 +23,126 @@ namespace kp { namespace shader_data { -static const unsigned char test_shaders_glsl_test_workgroup_comp_spv[] = { - 0x03, 0x02, 0x23, 0x07, 0x00, 0x00, 0x01, 0x00, 0x0a, 0x00, 0x08, 0x00, - 0x30, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x11, 0x00, 0x02, 0x00, - 0x01, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00, - 0x47, 0x4c, 0x53, 0x4c, 0x2e, 0x73, 0x74, 0x64, 0x2e, 0x34, 0x35, 0x30, - 0x00, 0x00, 0x00, 0x00, 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0x2d, 0x00, 0x00, 0x00, 0xfd, 0x00, 0x01, 0x00, + 0x38, 0x00, 0x01, 0x00 +}; +static const unsigned int test_shaders_glsl_test_workgroup_comp_spv_len = 1396; } } #endif // define SHADEROP_SHADERTEST_WORKGROUP_HPP diff --git a/test/shaders/glsl/test_logistic_regression.comp.spv b/test/shaders/glsl/test_logistic_regression.comp.spv index 2f6883dac..f68cb431d 100755 Binary files a/test/shaders/glsl/test_logistic_regression.comp.spv and b/test/shaders/glsl/test_logistic_regression.comp.spv differ diff --git a/test/shaders/glsl/test_op_custom_shader.comp.spv b/test/shaders/glsl/test_op_custom_shader.comp.spv index 1c1a83c30..88b54d372 100755 Binary files a/test/shaders/glsl/test_op_custom_shader.comp.spv and b/test/shaders/glsl/test_op_custom_shader.comp.spv differ diff --git a/test/shaders/glsl/test_workgroup.comp.spv b/test/shaders/glsl/test_workgroup.comp.spv index 533d994fe..93b87ba7d 100755 Binary files a/test/shaders/glsl/test_workgroup.comp.spv and b/test/shaders/glsl/test_workgroup.comp.spv differ