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llama-cpp-turboquant/single_include/kompute/Kompute.hpp
Alejandro Saucedo e3406ef2c3 Updated headers to linux build
2021-02-18 22:29:41 +00:00

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#pragma once
#ifdef VK_USE_PLATFORM_ANDROID_KHR
#include <android/log.h>
#include <kompute_vk_ndk_wrapper.hpp>
// VK_NO_PROTOTYPES required before vulkan import but after wrapper.hpp
#undef VK_NO_PROTOTYPES
static const char* KOMPUTE_LOG_TAG = "KomputeLog";
#endif
#include <vulkan/vulkan.hpp>
// Typedefs to simplify interaction with core types
namespace kp {
typedef std::array<uint32_t, 3> Workgroup;
typedef std::vector<float> 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 <pybind11/pybind11.h>
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 <spdlog/spdlog.h>
#else
#include <iostream>
#if SPDLOG_ACTIVE_LEVEL > 1
#define SPDLOG_DEBUG(message, ...)
#else
#if defined(VK_USE_PLATFORM_ANDROID_KHR)
#define SPDLOG_DEBUG(message, ...) \
((void)__android_log_print(ANDROID_LOG_DEBUG, KOMPUTE_LOG_TAG, message))
#elif defined(KOMPUTE_BUILD_PYTHON)
#define SPDLOG_DEBUG(message, ...) kp_debug(message);
#else
#define SPDLOG_DEBUG(message, ...) \
std::cout << "DEBUG: " << message << std::endl
#endif // VK_USE_PLATFORM_ANDROID_KHR
#endif // SPDLOG_ACTIVE_LEVEL > 1
#if SPDLOG_ACTIVE_LEVEL > 2
#define SPDLOG_INFO(message, ...)
#else
#if defined(VK_USE_PLATFORM_ANDROID_KHR)
#define SPDLOG_INFO(message, ...) \
((void)__android_log_print(ANDROID_LOG_INFO, KOMPUTE_LOG_TAG, message))
#elif defined(KOMPUTE_BUILD_PYTHON)
#define SPDLOG_INFO(message, ...) kp_info(message);
#else
#define SPDLOG_INFO(message, ...) std::cout << "INFO: " << message << std::endl
#endif // VK_USE_PLATFORM_ANDROID_KHR
#endif // SPDLOG_ACTIVE_LEVEL > 2
#if SPDLOG_ACTIVE_LEVEL > 3
#define SPDLOG_WARN(message, ...)
#else
#if defined(VK_USE_PLATFORM_ANDROID_KHR)
#define SPDLOG_WARN(message, ...) \
((void)__android_log_print(ANDROID_LOG_INFO, KOMPUTE_LOG_TAG, message))
#elif defined(KOMPUTE_BUILD_PYTHON)
#define SPDLOG_WARN(message, ...) kp_warning(message);
#else
#define SPDLOG_WARN(message, ...) \
std::cout << "WARNING: " << message << std::endl
#endif // VK_USE_PLATFORM_ANDROID_KHR
#endif // SPDLOG_ACTIVE_LEVEL > 3
#if SPDLOG_ACTIVE_LEVEL > 4
#define SPDLOG_ERROR(message, ...)
#else
#if defined(VK_USE_PLATFORM_ANDROID_KHR)
#define SPDLOG_ERROR(message, ...) \
((void)__android_log_print(ANDROID_LOG_INFO, KOMPUTE_LOG_TAG, message))
#elif defined(KOMPUTE_BUILD_PYTHON)
#define SPDLOG_ERROR(message, ...) kp_error(message);
#else
#define SPDLOG_ERROR(message, ...) \
std::cout << "ERROR: " << message << std::endl
#endif // VK_USE_PLATFORM_ANDROID_KHR
#endif // SPDLOG_ACTIVE_LEVEL > 4
#endif // KOMPUTE_SPDLOG_ENABLED
#endif // KOMPUTE_LOG_OVERRIDE
/*
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[] = {
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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,
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0x3d, 0x00, 0x04, 0x00, 0x3c, 0x00, 0x00, 0x00, 0x96, 0x00, 0x00, 0x00,
0x3e, 0x00, 0x00, 0x00, 0x41, 0x00, 0x05, 0x00, 0x07, 0x00, 0x00, 0x00,
0x98, 0x00, 0x00, 0x00, 0x7f, 0x00, 0x00, 0x00, 0x97, 0x00, 0x00, 0x00,
0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x99, 0x00, 0x00, 0x00,
0x98, 0x00, 0x00, 0x00, 0x41, 0x00, 0x06, 0x00, 0x4d, 0x00, 0x00, 0x00,
0x9a, 0x00, 0x00, 0x00, 0x95, 0x00, 0x00, 0x00, 0x4c, 0x00, 0x00, 0x00,
0x96, 0x00, 0x00, 0x00, 0x3e, 0x00, 0x03, 0x00, 0x9a, 0x00, 0x00, 0x00,
0x99, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x3c, 0x00, 0x00, 0x00,
0x9f, 0x00, 0x00, 0x00, 0x3e, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00,
0x06, 0x00, 0x00, 0x00, 0xa0, 0x00, 0x00, 0x00, 0x86, 0x00, 0x00, 0x00,
0x41, 0x00, 0x06, 0x00, 0x4d, 0x00, 0x00, 0x00, 0xa1, 0x00, 0x00, 0x00,
0x9e, 0x00, 0x00, 0x00, 0x4c, 0x00, 0x00, 0x00, 0x9f, 0x00, 0x00, 0x00,
0x3e, 0x00, 0x03, 0x00, 0xa1, 0x00, 0x00, 0x00, 0xa0, 0x00, 0x00, 0x00,
0x3d, 0x00, 0x04, 0x00, 0x3c, 0x00, 0x00, 0x00, 0xa6, 0x00, 0x00, 0x00,
0x3e, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00,
0xa8, 0x00, 0x00, 0x00, 0x73, 0x00, 0x00, 0x00, 0x3e, 0x00, 0x03, 0x00,
0xa7, 0x00, 0x00, 0x00, 0xa8, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00,
0x06, 0x00, 0x00, 0x00, 0xaa, 0x00, 0x00, 0x00, 0x6b, 0x00, 0x00, 0x00,
0x3e, 0x00, 0x03, 0x00, 0xa9, 0x00, 0x00, 0x00, 0xaa, 0x00, 0x00, 0x00,
0x39, 0x00, 0x06, 0x00, 0x06, 0x00, 0x00, 0x00, 0xab, 0x00, 0x00, 0x00,
0x17, 0x00, 0x00, 0x00, 0xa7, 0x00, 0x00, 0x00, 0xa9, 0x00, 0x00, 0x00,
0x41, 0x00, 0x06, 0x00, 0x4d, 0x00, 0x00, 0x00, 0xac, 0x00, 0x00, 0x00,
0xa5, 0x00, 0x00, 0x00, 0x4c, 0x00, 0x00, 0x00, 0xa6, 0x00, 0x00, 0x00,
0x3e, 0x00, 0x03, 0x00, 0xac, 0x00, 0x00, 0x00, 0xab, 0x00, 0x00, 0x00,
0xfd, 0x00, 0x01, 0x00, 0x38, 0x00, 0x01, 0x00, 0x36, 0x00, 0x05, 0x00,
0x06, 0x00, 0x00, 0x00, 0x0a, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0x08, 0x00, 0x00, 0x00, 0x37, 0x00, 0x03, 0x00, 0x07, 0x00, 0x00, 0x00,
0x09, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00, 0x0b, 0x00, 0x00, 0x00,
0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x1a, 0x00, 0x00, 0x00,
0x09, 0x00, 0x00, 0x00, 0x7f, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00,
0x1b, 0x00, 0x00, 0x00, 0x1a, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x06, 0x00,
0x06, 0x00, 0x00, 0x00, 0x1c, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
0x1b, 0x00, 0x00, 0x00, 0x1b, 0x00, 0x00, 0x00, 0x81, 0x00, 0x05, 0x00,
0x06, 0x00, 0x00, 0x00, 0x1d, 0x00, 0x00, 0x00, 0x19, 0x00, 0x00, 0x00,
0x1c, 0x00, 0x00, 0x00, 0x88, 0x00, 0x05, 0x00, 0x06, 0x00, 0x00, 0x00,
0x1e, 0x00, 0x00, 0x00, 0x19, 0x00, 0x00, 0x00, 0x1d, 0x00, 0x00, 0x00,
0xfe, 0x00, 0x02, 0x00, 0x1e, 0x00, 0x00, 0x00, 0x38, 0x00, 0x01, 0x00,
0x36, 0x00, 0x05, 0x00, 0x06, 0x00, 0x00, 0x00, 0x12, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x00, 0x00, 0x37, 0x00, 0x03, 0x00,
0x0d, 0x00, 0x00, 0x00, 0x0f, 0x00, 0x00, 0x00, 0x37, 0x00, 0x03, 0x00,
0x0d, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x37, 0x00, 0x03, 0x00,
0x07, 0x00, 0x00, 0x00, 0x11, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00,
0x13, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00, 0x07, 0x00, 0x00, 0x00,
0x21, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x3b, 0x00, 0x04, 0x00,
0x07, 0x00, 0x00, 0x00, 0x27, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00,
0x3b, 0x00, 0x04, 0x00, 0x07, 0x00, 0x00, 0x00, 0x28, 0x00, 0x00, 0x00,
0x07, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x0c, 0x00, 0x00, 0x00,
0x22, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00,
0x0c, 0x00, 0x00, 0x00, 0x23, 0x00, 0x00, 0x00, 0x0f, 0x00, 0x00, 0x00,
0x94, 0x00, 0x05, 0x00, 0x06, 0x00, 0x00, 0x00, 0x24, 0x00, 0x00, 0x00,
0x22, 0x00, 0x00, 0x00, 0x23, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00,
0x06, 0x00, 0x00, 0x00, 0x25, 0x00, 0x00, 0x00, 0x11, 0x00, 0x00, 0x00,
0x81, 0x00, 0x05, 0x00, 0x06, 0x00, 0x00, 0x00, 0x26, 0x00, 0x00, 0x00,
0x24, 0x00, 0x00, 0x00, 0x25, 0x00, 0x00, 0x00, 0x3e, 0x00, 0x03, 0x00,
0x21, 0x00, 0x00, 0x00, 0x26, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00,
0x06, 0x00, 0x00, 0x00, 0x29, 0x00, 0x00, 0x00, 0x21, 0x00, 0x00, 0x00,
0x3e, 0x00, 0x03, 0x00, 0x28, 0x00, 0x00, 0x00, 0x29, 0x00, 0x00, 0x00,
0x39, 0x00, 0x05, 0x00, 0x06, 0x00, 0x00, 0x00, 0x2a, 0x00, 0x00, 0x00,
0x0a, 0x00, 0x00, 0x00, 0x28, 0x00, 0x00, 0x00, 0x3e, 0x00, 0x03, 0x00,
0x27, 0x00, 0x00, 0x00, 0x2a, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00,
0x06, 0x00, 0x00, 0x00, 0x2b, 0x00, 0x00, 0x00, 0x27, 0x00, 0x00, 0x00,
0xfe, 0x00, 0x02, 0x00, 0x2b, 0x00, 0x00, 0x00, 0x38, 0x00, 0x01, 0x00,
0x36, 0x00, 0x05, 0x00, 0x06, 0x00, 0x00, 0x00, 0x17, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x37, 0x00, 0x03, 0x00,
0x07, 0x00, 0x00, 0x00, 0x15, 0x00, 0x00, 0x00, 0x37, 0x00, 0x03, 0x00,
0x07, 0x00, 0x00, 0x00, 0x16, 0x00, 0x00, 0x00, 0xf8, 0x00, 0x02, 0x00,
0x18, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00,
0x2e, 0x00, 0x00, 0x00, 0x16, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00,
0x06, 0x00, 0x00, 0x00, 0x2f, 0x00, 0x00, 0x00, 0x15, 0x00, 0x00, 0x00,
0x0c, 0x00, 0x06, 0x00, 0x06, 0x00, 0x00, 0x00, 0x30, 0x00, 0x00, 0x00,
0x01, 0x00, 0x00, 0x00, 0x1c, 0x00, 0x00, 0x00, 0x2f, 0x00, 0x00, 0x00,
0x85, 0x00, 0x05, 0x00, 0x06, 0x00, 0x00, 0x00, 0x31, 0x00, 0x00, 0x00,
0x2e, 0x00, 0x00, 0x00, 0x30, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00,
0x06, 0x00, 0x00, 0x00, 0x32, 0x00, 0x00, 0x00, 0x16, 0x00, 0x00, 0x00,
0x83, 0x00, 0x05, 0x00, 0x06, 0x00, 0x00, 0x00, 0x33, 0x00, 0x00, 0x00,
0x19, 0x00, 0x00, 0x00, 0x32, 0x00, 0x00, 0x00, 0x3d, 0x00, 0x04, 0x00,
0x06, 0x00, 0x00, 0x00, 0x34, 0x00, 0x00, 0x00, 0x15, 0x00, 0x00, 0x00,
0x83, 0x00, 0x05, 0x00, 0x06, 0x00, 0x00, 0x00, 0x35, 0x00, 0x00, 0x00,
0x19, 0x00, 0x00, 0x00, 0x34, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x06, 0x00,
0x06, 0x00, 0x00, 0x00, 0x36, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
0x1c, 0x00, 0x00, 0x00, 0x35, 0x00, 0x00, 0x00, 0x85, 0x00, 0x05, 0x00,
0x06, 0x00, 0x00, 0x00, 0x37, 0x00, 0x00, 0x00, 0x33, 0x00, 0x00, 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
#include <set>
#include <unordered_map>
#define KP_MAX_DIM_SIZE 1
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)
};
/**
* Base constructor, should not be used unless explicitly intended.
*/
Tensor();
/**
* 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(const std::vector<float>& data,
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 init(std::shared_ptr<vk::PhysicalDevice> physicalDevice,
std::shared_ptr<vk::Device> device);
/**
* Destroys and frees the GPU resources which include the buffer and memory.
*/
void freeMemoryDestroyGPUResources();
/**
* 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<float>& 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();
/**
* Returns the shape of the tensor, which includes the number of dimensions
* and the size per dimension.
*
* @return Array containing the sizes for each dimension. Zero means
* respective dimension is not active.
*/
std::array<uint32_t, KP_MAX_DIM_SIZE> shape();
/**
* Retrieve the tensor type of the Tensor
*
* @return Tensor type of tensor
*/
TensorTypes tensorType();
/**
* Returns true if the tensor initialisation function has been carried out
* successful, which would mean that the buffer and memory will have been
* provisioned.
*/
bool isInit();
/**
* 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<float>& 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<vk::CommandBuffer> commandBuffer,
std::shared_ptr<Tensor> 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<vk::CommandBuffer> 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<vk::CommandBuffer> 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<vk::CommandBuffer> 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<vk::PhysicalDevice> mPhysicalDevice;
std::shared_ptr<vk::Device> mDevice;
// -------------- OPTIONALLY OWNED RESOURCES
std::shared_ptr<vk::Buffer> mPrimaryBuffer;
bool mFreePrimaryBuffer = false;
std::shared_ptr<vk::Buffer> mStagingBuffer;
bool mFreeStagingBuffer = false;
std::shared_ptr<vk::DeviceMemory> mPrimaryMemory;
bool mFreePrimaryMemory = false;
std::shared_ptr<vk::DeviceMemory> mStagingMemory;
bool mFreeStagingMemory = false;
// -------------- ALWAYS OWNED RESOURCES
std::vector<float> mData;
TensorTypes mTensorType = TensorTypes::eDevice;
std::array<uint32_t, KP_MAX_DIM_SIZE> mShape;
bool mIsInit = false;
void allocateMemoryCreateGPUResources(); // Creates the vulkan buffer
void createBuffer(std::shared_ptr<vk::Buffer> buffer,
vk::BufferUsageFlags bufferUsageFlags);
void allocateBindMemory(std::shared_ptr<vk::Buffer> buffer,
std::shared_ptr<vk::DeviceMemory> memory,
vk::MemoryPropertyFlags memoryPropertyFlags);
void copyBuffer(std::shared_ptr<vk::CommandBuffer> commandBuffer,
std::shared_ptr<vk::Buffer> bufferFrom,
std::shared_ptr<vk::Buffer> 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 {
/**
* 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:
/**
* Base constructor, should not be used unless explicitly intended.
*/
OpBase() { SPDLOG_DEBUG("Compute OpBase base constructor"); }
/**
* 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
*/
OpBase(std::shared_ptr<vk::PhysicalDevice> physicalDevice,
std::shared_ptr<vk::Device> device,
std::shared_ptr<vk::CommandBuffer> commandBuffer,
std::vector<std::shared_ptr<Tensor>>& tensors)
{
SPDLOG_DEBUG("Compute OpBase constructor with params");
this->mPhysicalDevice = physicalDevice;
this->mDevice = device;
this->mCommandBuffer = commandBuffer;
this->mTensors = tensors;
}
/**
* 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()
{
SPDLOG_DEBUG("Kompute OpBase destructor started");
if (!this->mDevice) {
SPDLOG_WARN("Kompute OpBase destructor called with empty device");
return;
}
if (this->mFreeTensors) {
SPDLOG_DEBUG("Kompute OpBase freeing tensors");
for (std::shared_ptr<Tensor> tensor : this->mTensors) {
if (tensor && tensor->isInit()) {
tensor->freeMemoryDestroyGPUResources();
} else {
SPDLOG_WARN("Kompute OpBase expected to free "
"tensor but has already been freed.");
}
}
}
}
/**
* The init function is responsible for setting up all the resources and
* should be called after the Operation has been created.
*/
virtual void init() = 0;
/**
* 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() = 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;
protected:
// -------------- NEVER OWNED RESOURCES
std::shared_ptr<vk::PhysicalDevice>
mPhysicalDevice; ///< Vulkan Physical Device
std::shared_ptr<vk::Device> mDevice; ///< Vulkan Logical Device
std::shared_ptr<vk::CommandBuffer>
mCommandBuffer; ///< Vulkan Command Buffer
// -------------- OPTIONALLY OWNED RESOURCES
std::vector<std::shared_ptr<Tensor>>
mTensors; ///< Tensors referenced by operation that can be managed
///< optionally by operation
bool mFreeTensors = false; ///< Explicit boolean that specifies whether the
///< tensors are freed (if they are managed)
};
} // End namespace kp
namespace kp {
/**
* Container of operations that can be sent to GPU as batch
*/
class Sequence
{
public:
/**
* Base constructor for Sequence. Should not be used unless explicit
* intended.
*/
Sequence();
/**
* 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<vk::PhysicalDevice> physicalDevice,
std::shared_ptr<vk::Device> device,
std::shared_ptr<vk::Queue> computeQueue,
uint32_t queueIndex);
/**
* Destructor for sequence which is responsible for cleaning all subsequent
* owned operations.
*/
~Sequence();
/**
* Initialises sequence including the creation of the command pool and the
* command buffer.
*/
void init();
/**
* Begins recording commands for commands to be submitted into the command
* buffer.
*
* @return Boolean stating whether execution was successful.
*/
bool begin();
/**
* Ends the recording and stops recording commands when the record command
* is sent.
*
* @return Boolean stating whether execution was successful.
*/
bool end();
/**
* Eval sends all the recorded and stored operations in the vector of
* operations into the gpu as a submit job with a barrier.
*
* @return Boolean stating whether execution was successful.
*/
bool eval();
/**
* 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.
*/
bool evalAsync();
/**
* 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.
*/
bool evalAwait(uint64_t waitFor = UINT64_MAX);
/**
* Returns true if the sequence is currently in recording activated.
*
* @return Boolean stating if recording ongoing.
*/
bool isRecording();
/**
* Returns true if the sequence is currently running - mostly used for async
* workloads.
*
* @return Boolean stating if currently running.
*/
bool isRunning();
/**
* Returns true if the sequence has been successfully initialised.
*
* @return Boolean stating if sequence has been initialised.
*/
bool isInit();
/**
* Destroys and frees the GPU resources which include the buffer and memory
* and sets the sequence as init=False.
*/
void freeMemoryDestroyGPUResources();
/**
* 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<typename T, typename... TArgs>
bool record(std::vector<std::shared_ptr<Tensor>> tensors, TArgs&&... params)
{
static_assert(std::is_base_of<OpBase, T>::value,
"Kompute Sequence record(...) template only valid with "
"OpBase derived classes");
SPDLOG_DEBUG("Kompute Sequence record function started");
if (!this->isRecording()) {
SPDLOG_ERROR(
"Kompute sequence record attempted when not record BEGIN");
return false;
}
SPDLOG_DEBUG("Kompute Sequence creating OpBase derived class instance");
T* op = new T(this->mPhysicalDevice,
this->mDevice,
this->mCommandBuffer,
tensors,
std::forward<TArgs>(params)...);
OpBase* baseOp = dynamic_cast<OpBase*>(op);
std::unique_ptr<OpBase> baseOpPtr{ baseOp };
SPDLOG_DEBUG(
"Kompute Sequence running init on OpBase derived class instance");
baseOpPtr->init();
SPDLOG_DEBUG(
"Kompute Sequence running record on OpBase derived class instance");
baseOpPtr->record();
mOperations.push_back(std::move(baseOpPtr));
return true;
}
private:
// -------------- NEVER OWNED RESOURCES
std::shared_ptr<vk::PhysicalDevice> mPhysicalDevice = nullptr;
std::shared_ptr<vk::Device> mDevice = nullptr;
std::shared_ptr<vk::Queue> mComputeQueue = nullptr;
uint32_t mQueueIndex = -1;
// -------------- OPTIONALLY OWNED RESOURCES
std::shared_ptr<vk::CommandPool> mCommandPool = nullptr;
bool mFreeCommandPool = false;
std::shared_ptr<vk::CommandBuffer> mCommandBuffer = nullptr;
bool mFreeCommandBuffer = false;
// -------------- ALWAYS OWNED RESOURCES
vk::Fence mFence;
std::vector<std::unique_ptr<OpBase>> mOperations;
// State
bool mIsInit = false;
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:
OpTensorSyncDevice();
/**
* 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(std::shared_ptr<vk::PhysicalDevice> physicalDevice,
std::shared_ptr<vk::Device> device,
std::shared_ptr<vk::CommandBuffer> commandBuffer,
std::vector<std::shared_ptr<Tensor>> tensors);
/**
* Default destructor. This class does not manage memory so it won't be expecting the parent to perform a release.
*/
~OpTensorSyncDevice() override;
/**
* Performs basic checks such as ensuring that there is at least one tensor provided with min memory of 1 element.
*/
void init() override;
/**
* For device tensors, it records the copy command for the tensor to copy the data from its staging to device memory.
*/
void record() override;
/**
* Does not perform any preEval commands.
*/
virtual void preEval() override;
/**
* Does not perform any postEval commands.
*/
virtual void postEval() override;
private:
};
} // 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 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<uint32_t>& 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<vk::Instance> instance,
std::shared_ptr<vk::PhysicalDevice> physicalDevice,
std::shared_ptr<vk::Device> device,
uint32_t physicalDeviceIndex);
/**
* 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> sequence(
std::string sequenceName = KP_DEFAULT_SESSION,
uint32_t queueIndex = 0);
/**
* Function that evaluates operation against named sequence.
*
* @param tensors The tensors to be used in the operation recorded
* @param sequenceName The name of the sequence to be retrieved or created
* @param TArgs Template parameters that will be used to initialise
* Operation to allow for extensible configurations on initialisation
*/
template<typename T, typename... TArgs>
void evalOp(std::vector<std::shared_ptr<Tensor>> tensors,
std::string sequenceName,
TArgs&&... params)
{
SPDLOG_DEBUG("Kompute Manager evalOp triggered");
std::shared_ptr<kp::Sequence> sq =
this->sequence(sequenceName);
SPDLOG_DEBUG("Kompute Manager evalOp running sequence BEGIN");
sq->begin();
SPDLOG_DEBUG("Kompute Manager evalOp running sequence RECORD");
sq->record<T>(tensors, std::forward<TArgs>(params)...);
SPDLOG_DEBUG("Kompute Manager evalOp running sequence END");
sq->end();
SPDLOG_DEBUG("Kompute Manager evalOp running sequence EVAL");
sq->eval();
SPDLOG_DEBUG("Kompute Manager evalOp running sequence SUCCESS");
}
/**
* Function that evaluates operation against a newly created sequence.
*
* @param tensors The tensors to be used in the operation recorded
* @param TArgs Template parameters that will be used to initialise
* Operation to allow for extensible configurations on initialisation
*/
template<typename T, typename... TArgs>
void evalOpDefault(std::vector<std::shared_ptr<Tensor>> tensors,
TArgs&&... params)
{
SPDLOG_DEBUG("Kompute Manager evalOp Default triggered");
this->mCurrentSequenceIndex++;
this->evalOp<T>(
tensors, KP_DEFAULT_SESSION, std::forward<TArgs>(params)...);
}
/**
* Function that evaluates operation against named sequence asynchronously.
*
* @param tensors The tensors to be used in the operation recorded
* @param sequenceName The name of the sequence to be retrieved or created
* @param params Template parameters that will be used to initialise
* Operation to allow for extensible configurations on initialisation
*/
template<typename T, typename... TArgs>
void evalOpAsync(std::vector<std::shared_ptr<Tensor>> tensors,
std::string sequenceName,
TArgs&&... params)
{
SPDLOG_DEBUG("Kompute Manager evalOpAsync triggered");
std::shared_ptr<kp::Sequence> sq =
this->sequence(sequenceName);
SPDLOG_DEBUG("Kompute Manager evalOpAsync running sequence BEGIN");
sq->begin();
SPDLOG_DEBUG("Kompute Manager evalOpAsync running sequence RECORD");
sq->record<T>(tensors, std::forward<TArgs>(params)...);
SPDLOG_DEBUG("Kompute Manager evalOpAsync running sequence END");
sq->end();
SPDLOG_DEBUG("Kompute Manager evalOpAsync running sequence EVAL");
sq->evalAsync();
SPDLOG_DEBUG("Kompute Manager evalOpAsync running sequence SUCCESS");
}
/**
* Operation that evaluates operation against default sequence
* asynchronously.
*
* @param tensors The tensors to be used in the operation recorded
* @param params Template parameters that will be used to initialise
* Operation to allow for extensible configurations on initialisation
*/
template<typename T, typename... TArgs>
void evalOpAsyncDefault(std::vector<std::shared_ptr<Tensor>> tensors,
TArgs&&... params)
{
SPDLOG_DEBUG("Kompute Manager evalOpAsyncDefault triggered");
this->mCurrentSequenceIndex++;
this->evalOpAsync<T>(
tensors, KP_DEFAULT_SESSION, std::forward<TArgs>(params)...);
}
/**
* Operation that awaits for named sequence to finish.
*
* @param sequenceName The name of the sequence to wait for termination
* @param waitFor The amount of time to wait before timing out
*/
void evalOpAwait(std::string sequenceName, uint64_t waitFor = UINT64_MAX)
{
SPDLOG_DEBUG("Kompute Manager evalOpAwait triggered with sequence {}",
sequenceName);
std::unordered_map<std::string, std::shared_ptr<Sequence>>::iterator
found = this->mManagedSequences.find(sequenceName);
if (found != this->mManagedSequences.end()) {
if (std::shared_ptr<kp::Sequence> sq = found->second) {
SPDLOG_DEBUG("Kompute Manager evalOpAwait running sequence "
"Sequence EVAL AWAIT");
if (sq->isRunning()) {
sq->evalAwait(waitFor);
}
}
SPDLOG_DEBUG(
"Kompute Manager evalOpAwait running sequence SUCCESS");
} else {
SPDLOG_ERROR("Kompute Manager evalOpAwait Sequence not found");
}
}
/**
* Operation that awaits for default sequence to finish.
*
* @param tensors The tensors to be used in the operation recorded
* @param params Template parameters that will be used to initialise
* Operation to allow for extensible configurations on initialisation
*/
void evalOpAwaitDefault(uint64_t waitFor = UINT64_MAX)
{
SPDLOG_DEBUG("Kompute Manager evalOpAwaitDefault triggered");
this->evalOpAwait(KP_DEFAULT_SESSION, waitFor);
}
/**
* 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> tensor(
const std::vector<float>& data,
Tensor::TensorTypes tensorType = Tensor::TensorTypes::eDevice,
bool syncDataToGPU = true);
/**
* Function that simplifies the common workflow of tensor initialisation. It
* will take the constructor parameters for a Tensor and will will us it to
* create a new Tensor. The tensor memory will then be managed and owned by
* the manager.
*
* @param tensors Array of tensors to rebuild
* @param syncDataToGPU Whether to sync the data to GPU memory
*/
void rebuild(std::vector<std::shared_ptr<kp::Tensor>> tensors,
bool syncDataToGPU = true);
/**
* Function that simplifies the common workflow of tensor initialisation. It
* will take the constructor parameters for a Tensor and will will us it to
* create a new Tensor. The tensor memory will then be managed and owned by
* the manager.
*
* @param tensors Single tensor to rebuild
* @param syncDataToGPU Whether to sync the data to GPU memory
*/
void rebuild(std::shared_ptr<kp::Tensor> tensor,
bool syncDataToGPU = true);
/**
* Destroy owned Vulkan GPU resources and free GPU memory for
* single tensor.
*
* @param tensors Single tensor to rebuild
*/
void destroy(std::shared_ptr<kp::Tensor> tensor);
/**
* Destroy owned Vulkan GPU resources and free GPU memory for
* vector of tensors.
*
* @param tensors Single tensor to rebuild
*/
void destroy(std::vector<std::shared_ptr<kp::Tensor>> tensors);
/**
* Destroy owned Vulkan GPU resources and free GPU memory for
* vector of sequences. Destroying by sequence name is more efficent
* and hence recommended instead of by object.
*
* @param sequences Vector for shared ptrs with sequences to destroy
*/
void destroy(std::vector<std::shared_ptr<kp::Sequence>> sequences);
/**
* Destroy owned Vulkan GPU resources and free GPU memory for
* single sequence. Destroying by sequence name is more efficent
* and hence recommended instead of by object.
*
* @param sequences Single sequence to rebuild
*/
void destroy(std::shared_ptr<kp::Sequence> sequence);
/**
* Destroy owned Vulkan GPU resources and free GPU memory for
* sequence by name.
*
* @param sequenceName Single name of named sequence to destroy
*/
void destroy(const std::string& sequenceName);
/**
* Destroy owned Vulkan GPU resources and free GPU memory for
* sequences using vector of named sequence names.
*
* @param sequenceName Vector of sequence names to destroy
*/
void destroy(const std::vector<std::string>& sequenceNames);
private:
// -------------- OPTIONALLY OWNED RESOURCES
std::shared_ptr<vk::Instance> mInstance = nullptr;
bool mFreeInstance = false;
std::shared_ptr<vk::PhysicalDevice> mPhysicalDevice = nullptr;
uint32_t mPhysicalDeviceIndex = -1;
std::shared_ptr<vk::Device> mDevice = nullptr;
bool mFreeDevice = false;
// -------------- ALWAYS OWNED RESOURCES
std::set<std::shared_ptr<Tensor>> mManagedTensors;
std::unordered_map<std::string, std::shared_ptr<Sequence>>
mManagedSequences;
std::vector<uint32_t> mComputeQueueFamilyIndices;
std::vector<std::shared_ptr<vk::Queue>> mComputeQueues;
uint32_t mCurrentSequenceIndex = -1;
#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<uint32_t>& familyQueueIndices = {});
};
} // End namespace kp
#include <fstream>
namespace kp {
/**
Abstraction for compute shaders that are run on top of tensors grouped via
ParameterGroups (which group descriptorsets)
*/
class Algorithm
{
public:
/**
Base constructor for Algorithm. Should not be used unless explicit
intended.
*/
Algorithm();
/**
* 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<vk::Device> device,
std::shared_ptr<vk::CommandBuffer> commandBuffer,
const Constants& specializationConstants = {});
/**
* 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 init(const std::vector<char>& shaderFileData,
std::vector<std::shared_ptr<Tensor>> tensorParams);
/**
* 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(uint32_t x = 1, uint32_t y = 1, uint32_t z = 1);
private:
// -------------- NEVER OWNED RESOURCES
std::shared_ptr<vk::Device> mDevice;
std::shared_ptr<vk::CommandBuffer> mCommandBuffer;
// -------------- OPTIONALLY OWNED RESOURCES
std::shared_ptr<vk::DescriptorSetLayout> mDescriptorSetLayout;
bool mFreeDescriptorSetLayout = false;
std::shared_ptr<vk::DescriptorPool> mDescriptorPool;
bool mFreeDescriptorPool = false;
std::shared_ptr<vk::DescriptorSet> mDescriptorSet;
bool mFreeDescriptorSet = false;
std::shared_ptr<vk::ShaderModule> mShaderModule;
bool mFreeShaderModule = false;
std::shared_ptr<vk::PipelineLayout> mPipelineLayout;
bool mFreePipelineLayout = false;
std::shared_ptr<vk::PipelineCache> mPipelineCache;
bool mFreePipelineCache = false;
std::shared_ptr<vk::Pipeline> mPipeline;
bool mFreePipeline = false;
// -------------- ALWAYS OWNED RESOURCES
Constants mSpecializationConstants;
// Create util functions
void createShaderModule(const std::vector<char>& shaderFileData);
void createPipeline();
// Parameters
void createParameters(std::vector<std::shared_ptr<Tensor>>& tensorParams);
void createDescriptorPool();
};
} // End namespace kp
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 OpAlgoBase : public OpBase
{
public:
/**
* Base constructor, should not be used unless explicitly intended.
*/
OpAlgoBase();
/**
* 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 shaderFilePath Optional parameter to specify the shader to load (either in spirv or raw format)
* @param komputeWorkgroup Optional parameter to specify the layout for processing
*/
OpAlgoBase(std::shared_ptr<vk::PhysicalDevice> physicalDevice,
std::shared_ptr<vk::Device> device,
std::shared_ptr<vk::CommandBuffer> commandBuffer,
std::vector<std::shared_ptr<Tensor>>& tensors,
const Workgroup& komputeWorkgroup = {},
const Constants& specializationConstants = {});
/**
* Constructor that enables a file to be passed to the operation with
* the contents of the shader. This can be either in raw format or in
* compiled SPIR-V binary format.
*
* @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 shaderFilePath Parameter to specify the shader to load (either in spirv or raw format)
* @param komputeWorkgroup Optional parameter to specify the layout for processing
*/
OpAlgoBase(std::shared_ptr<vk::PhysicalDevice> physicalDevice,
std::shared_ptr<vk::Device> device,
std::shared_ptr<vk::CommandBuffer> commandBuffer,
std::vector<std::shared_ptr<Tensor>>& tensors,
std::string shaderFilePath,
const Workgroup& komputeWorkgroup = {},
const Constants& specializationConstants = {});
/**
* Constructor that enables raw shader data to be passed to the main operation
* which can be either in raw shader glsl code or in compiled SPIR-V binary.
*
* @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 shaderDataRaw Optional parameter to specify the shader data either in binary or raw form
* @param komputeWorkgroup Optional parameter to specify the layout for processing
*/
OpAlgoBase(std::shared_ptr<vk::PhysicalDevice> physicalDevice,
std::shared_ptr<vk::Device> device,
std::shared_ptr<vk::CommandBuffer> commandBuffer,
std::vector<std::shared_ptr<Tensor>>& tensors,
const std::vector<char>& shaderDataRaw,
const Workgroup& komputeWorkgroup = {},
const Constants& specializationConstants = {});
/**
* Default destructor, which is in charge of destroying the algorithm
* components but does not destroy the underlying tensors
*/
virtual ~OpAlgoBase() override;
/**
* The init function is responsible for the initialisation of the algorithm
* component based on the parameters specified, and allows for extensibility
* on the options provided. Further dependent classes can perform more
* specific checks such as ensuring tensors provided are initialised, etc.
*/
virtual void init() 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() 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;
protected:
// -------------- NEVER OWNED RESOURCES
// -------------- OPTIONALLY OWNED RESOURCES
std::shared_ptr<Algorithm> mAlgorithm;
bool mFreeAlgorithm = false;
// -------------- ALWAYS OWNED RESOURCES
Workgroup mKomputeWorkgroup;
std::string mShaderFilePath; ///< Optional member variable which can be provided for the OpAlgoBase to find the data automatically and load for processing
std::vector<char> mShaderDataRaw; ///< Optional member variable which can be provided to contain either the raw shader content or the spirv binary content
virtual std::vector<char> fetchSpirvBinaryData();
};
} // End namespace kp
#include <fstream>
namespace kp {
/**
* Operation base class to simplify the creation of operations that require
* right hand and left hand side datapoints together with a single output.
* The expected data passed is two input tensors and one output tensor.
*/
class OpAlgoLhsRhsOut : public OpAlgoBase
{
public:
/**
* Base constructor, should not be used unless explicitly intended.
*/
OpAlgoLhsRhsOut();
/**
* 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 freeTensors Whether operation manages the memory of the Tensors
* @param komputeWorkgroup Optional parameter to specify the layout for processing
*/
OpAlgoLhsRhsOut(std::shared_ptr<vk::PhysicalDevice> physicalDevice,
std::shared_ptr<vk::Device> device,
std::shared_ptr<vk::CommandBuffer> commandBuffer,
std::vector<std::shared_ptr<Tensor>> tensors,
const Workgroup& komputeWorkgroup = {});
/**
* Default destructor, which is in charge of destroying the algorithm
* components but does not destroy the underlying tensors
*/
virtual ~OpAlgoLhsRhsOut() override;
/**
* The init function is responsible for ensuring that all of the tensors
* provided are aligned with requirements such as LHS, RHS and Output
* tensors, and creates the algorithm component which processes the
* computation.
*/
virtual void init() 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() 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;
protected:
// -------------- NEVER OWNED RESOURCES
std::shared_ptr<Tensor> mTensorLHS; ///< Reference to the parameter used in the left hand side equation of the shader
std::shared_ptr<Tensor> mTensorRHS; ///< Reference to the parameter used in the right hand side equation of the shader
std::shared_ptr<Tensor> mTensorOutput; ///< Reference to the parameter used in the output of the shader and will be copied with a staging vector
};
} // End namespace kp
#include <fstream>
#if RELEASE
#endif
namespace kp {
/**
* Operation that performs multiplication on two tensors and outpus on third
* tensor.
*/
class OpMult : public OpAlgoBase
{
public:
/**
* Base constructor, should not be used unless explicitly intended.
*/
OpMult() {
}
/**
* 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::shared_ptr<vk::PhysicalDevice> physicalDevice,
std::shared_ptr<vk::Device> device,
std::shared_ptr<vk::CommandBuffer> commandBuffer,
std::vector<std::shared_ptr<Tensor>> tensors,
const Workgroup& komputeWorkgroup = {})
: OpAlgoBase(physicalDevice, device, commandBuffer, tensors, "", komputeWorkgroup)
{
SPDLOG_DEBUG("Kompute OpMult constructor with params");
#ifndef RELEASE
this->mShaderFilePath = "shaders/glsl/opmult.comp";
#endif
}
#if RELEASE
/**
* If RELEASE=1 it will be using the static version of the shader which is
* loaded using this file directly. Otherwise it should not override the function.
*/
std::vector<char> fetchSpirvBinaryData() override
{
SPDLOG_WARN(
"Kompute OpMult Running shaders directly from header");
return std::vector<char>(
shader_data::shaders_glsl_opmult_comp_spv,
shader_data::shaders_glsl_opmult_comp_spv +
kp::shader_data::shaders_glsl_opmult_comp_spv_len);
}
#endif
/**
* Default destructor, which is in charge of destroying the algorithm
* components but does not destroy the underlying tensors
*/
~OpMult() override {
SPDLOG_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:
OpTensorCopy();
/**
* 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(std::shared_ptr<vk::PhysicalDevice> physicalDevice,
std::shared_ptr<vk::Device> device,
std::shared_ptr<vk::CommandBuffer> commandBuffer,
std::vector<std::shared_ptr<Tensor>> tensors);
/**
* Default destructor. This class does not manage memory so it won't be expecting the parent to perform a release.
*/
~OpTensorCopy() override;
/**
* Performs basic checks such as ensuring there are at least two tensors provided, that they are initialised and that they are not of type TensorTypes::eStorage.
*/
void init() override;
/**
* Records the copy commands from the first tensor into all the other tensors provided. Also optionally records a barrier.
*/
void record() 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:
};
} // 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:
OpTensorSyncLocal();
/**
* 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(std::shared_ptr<vk::PhysicalDevice> physicalDevice,
std::shared_ptr<vk::Device> device,
std::shared_ptr<vk::CommandBuffer> commandBuffer,
std::vector<std::shared_ptr<Tensor>> tensors);
/**
* Default destructor. This class does not manage memory so it won't be expecting the parent to perform a release.
*/
~OpTensorSyncLocal() override;
/**
* Performs basic checks such as ensuring that there is at least one tensor provided with min memory of 1 element.
*/
void init() override;
/**
* For device tensors, it records the copy command for the tensor to copy the data from its device to staging memory.
*/
void record() 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:
};
} // End namespace kp
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