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Complete first GPU tensors

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Степанов Платон
2025-11-18 00:04:49 +04:00
parent 982ddcb5e0
commit c1874212ae
5 changed files with 83 additions and 26 deletions
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6
src/tensor/Makefile
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@@ -26,13 +26,17 @@ PYTHON_INCLUDE = $(shell python -c "import sysconfig; print(sysconfig.get_config
PYTHON_LIBS = $(PYTHON_PATH)$(SP)libs
PYBIND_INCLUDE = $(shell python -c "import pybind11; print(pybind11.get_include())")
OPENCL_INCLUDES = -I"A:/Programs/OpenCL/include"
OPENCL_LIB_PATH = -L"A:/Programs/OpenCL/lib" -lOpenCL
OPENCL_LIB = -L"A:/Programs/OpenCL/lib" -lOpenCL
.DEFAULT_GOAL := $(TARGET)
$(BUILD_DIR):
$(MKDIR) $(BUILD_DIR)
$(TARGET): $(COMMON_SRC) main.cpp | $(BUILD_DIR)
$(CXX) $(CXXFLAGS) -o $@ $^
$(CXX) $(CXXFLAGS) $(OPENCL_INCLUDES) $(OPENCL_LIB_PATH) -o $@ $^ $(OPENCL_LIB)
module: $(COMMON_SRC) pybind.cpp | $(BUILD_DIR)
$(CXX) $(CXXFLAGS) -shared -fPIC -o tensor.$(SHARED_LIB_EXT) $^ -I"$(PYTHON_INCLUDE)" -L"$(PYTHON_LIBS)" -lpython3.13 -I"$(PYBIND_INCLUDE)"

11
src/tensor/main.cpp
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@@ -5,9 +5,16 @@
// TODO: GENERIC KERNELS
// TODO: Scalar mult
// TODO: TMult >2
OpenCL openCL;
int main() {
Tensor<float, 2> a = Tensor<float, 2>({2, 4});
std::cout << a.toString();
Tensor<float, 2> a = Tensor<float, 2>({8192, 8192}, 1);
Tensor<float, 2> b = Tensor<float, 2>({8192, 8192}, 1);
auto c = a % b;
Tensor<float, 2> d = Tensor<float, 2>(c);
d += 1;
std::cout << d.toString();
return 0;
}

2
src/tensor/opencl/kernels/scalar.cl
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@@ -5,5 +5,5 @@ __kernel void add(__global float *A, float scalar) {
__kernel void mult(__global float *A, float scalar) {
int i = get_global_id(0);
B[i] = A[i] * scalar;
A[i] *= scalar;
}

2
src/tensor/opencl/opencl.hpp
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@@ -70,4 +70,4 @@ public:
void printDeviceInfo() const;
};
OpenCL openCL;
extern OpenCL openCL;

88
src/tensor/opencl/tensor.hpp
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@@ -4,12 +4,13 @@
#include "../tensor.hpp"
#include <iostream>
#include <random>
#include <sstream>
template <typename T, int Dim> class Tensor : public ITensor<T, Dim> {
private:
cl::Buffer *data_ = nullptr;
cl::Event *event_ = new cl::Event();
cl::Event event_ = cl::Event();
class AutoEventList {
private:
@@ -19,7 +20,7 @@ private:
AutoEventList(std::initializer_list<cl::Event> events) : events_(events) {}
operator const std::vector<cl::Event> *() const { return &events_; }
};
template <typename... Events> AutoEventList all(Events &&...events) {
template <typename... Events> AutoEventList all(Events &&...events) const {
return AutoEventList{std::forward<Events>(events)...};
}
@@ -32,16 +33,15 @@ private:
void fillBuf(const std::vector<T> &data) {
createBuf(data.size());
// event_ = event?!
openCL.getQueue().enqueueWriteBuffer(*data_, CL_FALSE, 0,
data.size() * sizeof(T), data.data(),
all(*event_), event_);
nullptr, &event_);
}
void fillBuf(const Tensor &other) {
createBuf(other.getSize());
openCL.getQueue().enqueueCopyBuffer(
*other.getData(), *data_, 0, 0, other.getSize() * sizeof(T),
all(*event_, *other.getEvent()), event_);
openCL.getQueue().enqueueCopyBuffer(*other.getData(), *data_, 0, 0,
other.getSize() * sizeof(T),
all(other.getEvent()), &event_);
}
public:
@@ -97,7 +97,7 @@ public:
Tensor(Tensor &&other) noexcept : ITensor(std::move(other)) {
data_ = other.data_;
event_ = other.event_;
other.data = nullptr;
other.data_ = nullptr;
}
Tensor &operator=(Tensor &&other) noexcept {
ITensor::operator=(std::move(other));
@@ -112,7 +112,7 @@ public:
};
const cl::Buffer *getData() const { return data_; }
const cl::Event *getEvent() const { return event_; }
const cl::Event &getEvent() const { return event_; }
// T &operator[](size_t i);
// const T &operator[](size_t i) const;
@@ -128,7 +128,7 @@ public:
kernel.setArg(0, *data_);
openCL.getQueue().enqueueNDRangeKernel(kernel, cl::NullRange,
cl::NDRange(getSize()),
cl::NullRange, all(*event_), event_);
cl::NullRange, all(event_), &event_);
return *this;
}
@@ -137,7 +137,7 @@ public:
kernel.setArg(0, *data_);
openCL.getQueue().enqueueNDRangeKernel(kernel, cl::NullRange,
cl::NDRange(getSize()),
cl::NullRange, all(*event_), event_);
cl::NullRange, all(event_), &event_);
return *this;
}
@@ -147,7 +147,7 @@ public:
kernel.setArg(1, scalar);
openCL.getQueue().enqueueNDRangeKernel(kernel, cl::NullRange,
cl::NDRange(getSize()),
cl::NullRange, all(*event_), event_);
cl::NullRange, all(event_), &event_);
return *this;
}
@@ -157,7 +157,7 @@ public:
kernel.setArg(1, scalar);
openCL.getQueue().enqueueNDRangeKernel(kernel, cl::NullRange,
cl::NDRange(getSize()),
cl::NullRange, all(*event_), event_);
cl::NullRange, all(event_), &event_);
return *this;
}
@@ -167,7 +167,7 @@ public:
kernel.setArg(1, *other.getData());
openCL.getQueue().enqueueNDRangeKernel(
kernel, cl::NullRange, cl::NDRange(getSize()), cl::NullRange,
all(*event_, *other.event_), event_);
all(event_, other.event_), &event_);
return *this;
}
@@ -177,7 +177,7 @@ public:
kernel.setArg(1, *other.getData());
openCL.getQueue().enqueueNDRangeKernel(
kernel, cl::NullRange, cl::NDRange(getSize()), cl::NullRange,
all(*event_, *other.event_), event_);
all(event_, other.event_), &event_);
return *this;
}
@@ -191,9 +191,9 @@ public:
if (shape_[axes_[1]] != other.shape_[other.axes_[0]])
throw std::invalid_argument(
"Matrix dimensions must match for multiplication");
size_t m = shape_[axes_[0]];
size_t k = shape_[axes_[1]];
size_t n = other.shape_[other.axes_[1]];
int m = (int)shape_[axes_[0]];
int k = (int)shape_[axes_[1]];
int n = (int)other.shape_[other.axes_[1]];
Tensor<T, 2> result({m, n});
cl::Kernel kernel = openCL.createKernel(OpenCL::Method::T_MULT);
kernel.setArg(0, *data_);
@@ -207,12 +207,58 @@ public:
cl::NDRange local_size(TILE_SIZE, TILE_SIZE);
openCL.getQueue().enqueueNDRangeKernel(
kernel, cl::NullRange, global_size, local_size,
all(*event_, *other.event_), result.event_);
all(event_, other.event_), &result.event_);
return result;
}
}
std::string toString() const override;
std::string toString() const override {
std::vector<float> result(getSize());
openCL.getQueue().enqueueReadBuffer(
*data_, CL_TRUE, 0, getSize() * sizeof(T), result.data(), all(event_));
std::ostringstream oss;
if constexpr (Dim == 0) {
oss << "Scalar<" << typeid(T).name() << ">: " << result[0];
} else if constexpr (Dim == 1) {
oss << "Vector<" << typeid(T).name() << ">(" << shape_[0] << "): [";
for (size_t i = 0; i < getSize(); ++i) {
oss << result[i];
if (i < getSize() - 1)
oss << ", ";
}
oss << "]";
} else if constexpr (Dim == 2) {
oss << "Matrix<" << typeid(T).name() << ">(" << shape_[axes_[0]] << "x"
<< shape_[axes_[1]] << "):";
for (size_t i = 0; i < shape_[axes_[0]]; ++i) {
oss << "\n [";
for (size_t j = 0; j < shape_[axes_[1]]; ++j) {
oss << result[i * shape_[axes_[0]] + j];
if (j < shape_[axes_[1]] - 1)
oss << ", ";
}
oss << "]";
}
} else {
oss << "Tensor" << Dim << "D<" << typeid(T).name() << ">" << "[";
for (size_t i = 0; i < Dim; ++i) {
oss << shape_[axes_[i]];
if (i < Dim - 1)
oss << "x";
}
oss << "]: [";
size_t show = std::min(getSize(), size_t(10));
for (size_t i = 0; i < show; ++i) {
oss << result[i];
if (i < show - 1)
oss << ", ";
}
if (getSize() > 10)
oss << ", ...";
oss << "]";
}
return oss.str();
}
};
#include "tensor.tpp"