/* Copyright (c) 2020 - 2023 Advanced Micro Devices, Inc. All rights reserved. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. */ // Test Description: /* This test implements sum reduction kernel, first with each threads own rank as input and comparing the sum with expected sum output derieved from n(n-1)/2 formula. The second part, partitions this parent group into child subgroups a.k.a tiles using using tiled_partition() collective operation. This can be called with a static tile size, passed in templated non-type variable-tiled_partition, or in runtime as tiled_partition(thread_group parent, tileSz). This test covers both these cases. This test tests functionality of cg group partitioning, (static and dynamic) and its respective API's size(), thread_rank(), and sync(). */ #include #include #include #include using namespace cooperative_groups; /* Parallel reduce kernel. * * Step complexity: O(log n) * Work complexity: O(n) * * Note: This kernel works only with power of 2 input arrays. */ __device__ int reduction_kernel(thread_group g, int* x, int val) { int lane = g.thread_rank(); for (int i = g.size() / 2; i > 0; i /= 2) { // use lds to store the temporary result x[lane] = val; // Ensure all the stores are completed. g.sync(); if (lane < i) { val += x[lane + i]; } // It must work on one tiled thread group at a time, // and it must make sure all memory operations are // completed before moving to the next stride. // sync() here just does that. g.sync(); } // Choose the 0'th indexed thread that holds the reduction value to return if (g.thread_rank() == 0) { return val; } // Rest of the threads return no useful values else { return -1; } } template __global__ void kernel_cg_group_partition_static(int* result, bool isGlobalMem, int* globalMem) { thread_block threadBlockCGTy = this_thread_block(); int threadBlockGroupSize = threadBlockCGTy.size(); int* workspace = NULL; if (isGlobalMem) { workspace = globalMem; } else { // Declare a shared memory extern __shared__ int sharedMem[]; workspace = sharedMem; } int input, outputSum, expectedOutput; // we pass its own thread rank as inputs input = threadBlockCGTy.thread_rank(); expectedOutput = (threadBlockGroupSize - 1) * threadBlockGroupSize / 2; outputSum = reduction_kernel(threadBlockCGTy, workspace, input); // Choose a leader thread to print the results if (threadBlockCGTy.thread_rank() == 0) { printf(" Sum of all ranks 0..%d in threadBlockCooperativeGroup is %d (expected %d)\n\n", (int)threadBlockCGTy.size() - 1, outputSum, expectedOutput); printf(" Creating %d groups, of tile size %d threads:\n\n", (int)threadBlockCGTy.size() / tileSz, tileSz); } threadBlockCGTy.sync(); thread_block_tile tiledPartition = tiled_partition(threadBlockCGTy); // This offset allows each group to have its own unique area in the workspace array int workspaceOffset = threadBlockCGTy.thread_rank() - tiledPartition.thread_rank(); outputSum = reduction_kernel(tiledPartition, workspace + workspaceOffset, input); if (tiledPartition.thread_rank() == 0) { printf( " Sum of all ranks 0..%d in this tiledPartition group is %d. Corresponding parent thread " "rank via meta_group_rank : %d and the total number of groups created when partitioned : %d\n", tiledPartition.size() - 1, outputSum, tiledPartition.meta_group_rank(), tiledPartition.meta_group_size()); result[input / (tileSz)] = outputSum; } return; } __global__ void kernel_cg_group_partition_dynamic(unsigned int tileSz, int* result, bool isGlobalMem, int* globalMem) { thread_block threadBlockCGTy = this_thread_block(); int* workspace = NULL; if (isGlobalMem) { workspace = globalMem; } else { // Declare a shared memory extern __shared__ int sharedMem[]; workspace = sharedMem; } int input, outputSum; // input to reduction, for each thread, is its' rank in the group input = threadBlockCGTy.thread_rank(); outputSum = reduction_kernel(threadBlockCGTy, workspace, input); if (threadBlockCGTy.thread_rank() == 0) { printf(" Sum of all ranks 0..%d in threadBlockCooperativeGroup is %d\n\n", (int)threadBlockCGTy.size() - 1, outputSum); printf(" Creating %d groups, of tile size %d threads:\n\n", (int)threadBlockCGTy.size() / tileSz, tileSz); } threadBlockCGTy.sync(); thread_group tiledPartition = tiled_partition(threadBlockCGTy, tileSz); // This offset allows each group to have its own unique area in the workspace array int workspaceOffset = threadBlockCGTy.thread_rank() - tiledPartition.thread_rank(); outputSum = reduction_kernel(tiledPartition, workspace + workspaceOffset, input); if (tiledPartition.thread_rank() == 0) { printf( " Sum of all ranks 0..%d in this tiledPartition group is %d. Corresponding parent thread " " %d\n", tiledPartition.size() - 1, outputSum, input); result[input / (tileSz)] = outputSum; } return; } // Search if the sum exists in the expected results array void verifyResults(int* hPtr, int* dPtr, int size) { int i = 0, j = 0; for (i = 0; i < size; i++) { for (j = 0; j < size; j++) { if (hPtr[i] == dPtr[j]) { break; } } if (j == size) { REQUIRE(" Result verification failed!"); } } } template static void test_group_partition(bool useGlobalMem) { hipError_t err; int blockSize = 1; int threadsPerBlock = 64; int numTiles = (blockSize * threadsPerBlock) / tileSz; // Build an array of expected reduction sum output on the host // based on the sum of their respective thread ranks for verification. // eg: parent group has 64threads. // child thread ranks: 0-15, 16-31, 32-47, 48-63 // expected sum: 120, 376, 632, 888 int* expectedSum = new int[numTiles]; int temp = 0, sum = 0; for (int i = 1; i <= numTiles; i++) { sum = temp; temp = (((tileSz * i) - 1) * (tileSz * i)) / 2; expectedSum[i-1] = temp - sum; } int* dResult = NULL; HIPCHECK(hipMalloc((void**)&dResult, numTiles * sizeof(int))); int* globalMem = NULL; if (useGlobalMem) { HIPCHECK(hipMalloc((void**)&globalMem, threadsPerBlock * sizeof(int))); } int* hResult = NULL; HIPCHECK(hipHostMalloc(&hResult, numTiles * sizeof(int), hipHostMallocDefault)); memset(hResult, 0, numTiles * sizeof(int)); if (useGlobalMem) { // Launch Kernel hipLaunchKernelGGL(kernel_cg_group_partition_static, blockSize, threadsPerBlock, 0, 0, dResult, useGlobalMem, globalMem); err = hipDeviceSynchronize(); if (err != hipSuccess) { fprintf(stderr, "Failed to launch kernel (error code %s)!\n", hipGetErrorString(err)); } } else { // Launch Kernel hipLaunchKernelGGL(kernel_cg_group_partition_static, blockSize, threadsPerBlock, threadsPerBlock * sizeof(int), 0, dResult, useGlobalMem, globalMem); err = hipDeviceSynchronize(); if (err != hipSuccess) { fprintf(stderr, "Failed to launch kernel (error code %s)!\n", hipGetErrorString(err)); } } HIPCHECK(hipMemcpy(hResult, dResult, numTiles * sizeof(int), hipMemcpyDeviceToHost)); verifyResults(expectedSum, hResult, numTiles); // Free all allocated memory on host and device HIPCHECK(hipFree(dResult)); HIPCHECK(hipFree(hResult)); if (useGlobalMem) { HIPCHECK(hipFree(globalMem)); } delete[] expectedSum; printf("\n...PASSED.\n\n"); } static void test_group_partition(unsigned int tileSz, bool useGlobalMem) { hipError_t err; int blockSize = 1; int threadsPerBlock = 64; int numTiles = (blockSize * threadsPerBlock) / tileSz; // Build an array of expected reduction sum output on the host // based on the sum of their respective thread ranks to use for verification int* expectedSum = new int[numTiles]; int temp = 0, sum = 0; for (int i = 1; i <= numTiles; i++) { sum = temp; temp = (((tileSz * i) - 1) * (tileSz * i)) / 2; expectedSum[i-1] = temp - sum; } int* dResult = NULL; HIPCHECK(hipMalloc(&dResult, sizeof(int) * numTiles)); int* globalMem = NULL; if (useGlobalMem) { HIPCHECK(hipMalloc((void**)&globalMem, threadsPerBlock * sizeof(int))); } int* hResult = NULL; HIPCHECK(hipHostMalloc(&hResult, numTiles * sizeof(int), hipHostMallocDefault)); memset(hResult, 0, numTiles * sizeof(int)); // Launch Kernel if (useGlobalMem) { hipLaunchKernelGGL(kernel_cg_group_partition_dynamic, blockSize, threadsPerBlock, 0, 0, tileSz, dResult, useGlobalMem, globalMem); err = hipDeviceSynchronize(); if (err != hipSuccess) { fprintf(stderr, "Failed to launch kernel (error code %s)!\n", hipGetErrorString(err)); } } else { hipLaunchKernelGGL(kernel_cg_group_partition_dynamic, blockSize, threadsPerBlock, threadsPerBlock * sizeof(int), 0, tileSz, dResult, useGlobalMem, globalMem); err = hipDeviceSynchronize(); if (err != hipSuccess) { fprintf(stderr, "Failed to launch kernel (error code %s)!\n", hipGetErrorString(err)); } } HIPCHECK(hipMemcpy(hResult, dResult, numTiles * sizeof(int), hipMemcpyDeviceToHost)); verifyResults(expectedSum, hResult, numTiles); // Free all allocated memory on host and device HIPCHECK(hipFree(dResult)); HIPCHECK(hipFree(hResult)); if (useGlobalMem) { HIPCHECK(hipFree(globalMem)); } delete[] expectedSum; printf("\n...PASSED.\n\n"); } TEST_CASE("Unit_tiled_partition") { // Use default device for validating the test int deviceId; HIP_CHECK_ERROR(hipGetDevice(&deviceId), hipSuccess); hipDeviceProp_t deviceProperties; HIP_CHECK_ERROR(hipGetDeviceProperties(&deviceProperties, deviceId), hipSuccess); if (!deviceProperties.cooperativeLaunch) { HipTest::HIP_SKIP_TEST("Device doesn't support cooperative launch!"); } bool useGlobalMem = true; std::cout << "Testing static tiled_partition for different tile sizes" << std::endl; std::cout << "\nUsing global memory for computation\n"; /* Test static tile_partition */ std::cout << "TEST 1:" << '\n' << std::endl; test_group_partition<2>(useGlobalMem); std::cout << "TEST 2:" << '\n' << std::endl; test_group_partition<4>(useGlobalMem); std::cout << "TEST 3:" << '\n' << std::endl; test_group_partition<8>(useGlobalMem); std::cout << "TEST 4:" << '\n' << std::endl; test_group_partition<16>(useGlobalMem); std::cout << "TEST 5:" << '\n' << std::endl; test_group_partition<32>(useGlobalMem); useGlobalMem = false; std::cout << "Testing static tiled_partition for different tile sizes" << std::endl; std::cout << "\nUsing shared memory for computation\n"; /* Test static tile_partition */ std::cout << "TEST 1:" << '\n' << std::endl; test_group_partition<2>(useGlobalMem); std::cout << "TEST 2:" << '\n' << std::endl; test_group_partition<4>(useGlobalMem); std::cout << "TEST 3:" << '\n' << std::endl; test_group_partition<8>(useGlobalMem); std::cout << "TEST 4:" << '\n' << std::endl; test_group_partition<16>(useGlobalMem); std::cout << "TEST 5:" << '\n' << std::endl; test_group_partition<32>(useGlobalMem); std::cout << "Now testing dynamic tiled_partition for different tile sizes" << '\n' << std::endl; /* Test dynamic group partition*/ useGlobalMem = true; int testNo = 1; std::vector tileSizes = {2, 4, 8, 16, 32}; std::cout << "\nUsing global memory for computation\n"; for (auto i : tileSizes) { std::cout << "TEST " << testNo << ":" << '\n' << std::endl; test_group_partition(i, useGlobalMem); testNo++; } useGlobalMem = false; testNo = 1; std::cout << "\nUsing shared memory for computation\n"; for (auto i : tileSizes) { std::cout << "TEST " << testNo << ":" << '\n' << std::endl; test_group_partition(i, useGlobalMem); testNo++; } printf("\n...PASSED.\n\n"); return; }