llama-cpp-turboquant/examples/array_multiplication/src/Main.cpp
2021-03-07 14:03:51 +00:00

56 lines
1.4 KiB
C++
Executable file

#include <iostream>
#include <memory>
#include <vector>
#include "kompute/Kompute.hpp"
int main()
{
#if KOMPUTE_ENABLE_SPDLOG
spdlog::set_level(
static_cast<spdlog::level::level_enum>(SPDLOG_ACTIVE_LEVEL));
#endif
kp::Manager mgr;
auto tensorInA = mgr.tensor({ 2.0, 4.0, 6.0 });
auto tensorInB = mgr.tensor({ 0.0, 1.0, 2.0 });
auto tensorOut = mgr.tensor({ 0.0, 0.0, 0.0 });
std::string shader(R"(
// The version to use
#version 450
// The execution structure
layout (local_size_x = 1) in;
// The buffers are provided via the tensors
layout(binding = 0) buffer bufA { float a[]; };
layout(binding = 1) buffer bufB { float b[]; };
layout(binding = 2) buffer bufOut { float o[]; };
void main() {
uint index = gl_GlobalInvocationID.x;
o[index] = a[index] * b[index];
}
)");
std::vector<std::shared_ptr<kp::Tensor>> params = { tensorInA, tensorInB, tensorOut };
std::shared_ptr<kp::Algorithm> algo = mgr.algorithm(params, kp::Shader::compileSource(shader));
mgr.sequence()
->record<kp::OpTensorSyncDevice>(params)
->record<kp::OpAlgoDispatch>(algo)
->record<kp::OpTensorSyncLocal>(params);
// prints "Output { 0 4 12 }"
std::cout<< "Output: { ";
for (const float& elem : tensorOut->data()) {
std::cout << elem << " ";
}
std::cout << "}" << std::endl;
}