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Commit 9976826

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committedOct 8, 2021
Add new vector add example
This new vector example compares different kinds of kernel functions to show the differences in assembly between each.
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‎samples/CMakeLists.txt

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@@ -71,5 +71,6 @@ add_sample(TARGET using-function-objects SOURCES using-function-objects.cpp)
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# This property is not necessary here, but demonstrates how to use it.
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# Forces the integration header to appear after the main code.
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set_property(TARGET using-function-objects PROPERTY COMPUTECPP_INCLUDE_AFTER 1)
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add_sample(TARGET vector-addition SOURCES vector-addition-examples.cpp)
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add_sample(TARGET vptr SOURCES vptr.cpp)
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target_include_directories(vptr PRIVATE ${PROJECT_SOURCE_DIR}/include)

‎samples/README.md

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`smart-pointer.cpp` | Custom Allocators in SYCL.
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`vptr.cpp` | Using the Virtual Pointer interface in SYCL on matrix addition kernel.
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`opencl-c-interop.cpp` | OpenCL/SYCL interopability example.
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`vector-addition-examples.cpp` | Comparison of different vector addition code to show masking, predication and vectorisation.

‎samples/vector-addition-examples.cpp

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/***************************************************************************
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*
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* Copyright (C) Codeplay Software Ltd.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*
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* Codeplay's ComputeCpp SDK
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*
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* vector-addition-examples.cpp
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*
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* Description:
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* Shows different code generation for vector addition kernels
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*/
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#include <iostream>
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#include <CL/sycl.hpp>
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using namespace cl;
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/* Base vector add function. */
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void vecAdd(const float* a, const float* b, float* c, size_t id) {
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c[id] = a[id] + b[id];
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}
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/* Masked variant where the store is hidden behind a runtime branch. */
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void vecAddMasked(const float* a, const float* b, float* c, size_t id) {
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float v = a[id] + b[id];
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if (v < 0.0f) {
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c[id] = v;
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}
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}
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/* Variant where the variable value is predicated on a branch. */
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void vecAddPredicated(const float* a, const float* b, float* c, size_t id) {
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float v = a[id] + b[id];
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if (v < 0.0f) {
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v = 0.0f;
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}
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c[id] = v;
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}
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class VecAddKernel;
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class VecAddKernelMasked;
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class VecAddKernelPredicated;
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void zeroBuffer(sycl::buffer<float, 1> b) {
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constexpr auto dwrite = sycl::access::mode::discard_write;
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auto h = b.get_access<dwrite>();
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for (auto i = 0u; i < b.get_range()[0]; i++) {
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h[i] = 0.f;
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}
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}
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void sumBuffer(sycl::buffer<float, 1> b) {
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constexpr auto read = sycl::access::mode::read;
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auto h = b.get_access<read>();
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auto sum = 0.0f;
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for (auto i = 0u; i < b.get_range()[0]; i++) {
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sum += h[i];
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}
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std::cout << "computation result: " << sum << std::endl;
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}
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/* This sample shows three different vector addition functions. It
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* is possible to inspect the assembly generated by these samples
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* using the ComputeSuite tooling to compare the different approaches.
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* The general flow is that the output buffer is zeroed, the calculation
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* scheduled, then the sum printed for each of the functions. */
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int main(int argc, char* argv[]) {
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constexpr auto read = sycl::access::mode::read;
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constexpr auto write = sycl::access::mode::write;
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constexpr auto dwrite = sycl::access::mode::discard_write;
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constexpr const size_t N = 100000;
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const sycl::range<1> VecSize{N};
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sycl::buffer<float> bufA{VecSize};
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sycl::buffer<float> bufB{VecSize};
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sycl::buffer<float> bufC{VecSize};
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{
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auto h_a = bufA.get_access<dwrite>();
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auto h_b = bufB.get_access<dwrite>();
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for (auto i = 0u; i < N; i++) {
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h_a[i] = sin(i);
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h_b[i] = cos(i);
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}
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}
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sycl::queue myQueue;
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{
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zeroBuffer(bufC);
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auto cg = [&](sycl::handler& h) {
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auto a = bufA.get_access<read>(h);
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auto b = bufB.get_access<read>(h);
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auto c = bufC.get_access<write>(h);
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h.parallel_for<VecAddKernel>(
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VecSize, [=](sycl::id<1> i) { vecAdd(&a[0], &b[0], &c[0], i[0]); });
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};
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myQueue.submit(cg);
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sumBuffer(bufC);
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}
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{
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zeroBuffer(bufC);
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auto cg = [&](sycl::handler& h) {
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auto a = bufA.get_access<read>(h);
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auto b = bufB.get_access<read>(h);
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auto c = bufC.get_access<write>(h);
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h.parallel_for<VecAddKernelMasked>(VecSize, [=](sycl::id<1> i) {
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vecAddMasked(&a[0], &b[0], &c[0], i[0]);
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});
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};
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myQueue.submit(cg);
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sumBuffer(bufC);
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}
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{
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zeroBuffer(bufC);
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auto cg = [&](sycl::handler& h) {
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auto a = bufA.get_access<read>(h);
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auto b = bufB.get_access<read>(h);
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auto c = bufC.get_access<write>(h);
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h.parallel_for<VecAddKernelPredicated>(VecSize, [=](sycl::id<1> i) {
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vecAddPredicated(&a[0], &b[0], &c[0], i[0]);
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});
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};
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myQueue.submit(cg);
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sumBuffer(bufC);
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}
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return 0;
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}

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