/* Copyright (c) 2022 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 WARRANNTY OF ANY KIND, EXPRESS OR IMPLIED, INNCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANNY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER INN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR INN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. */ /* Test Case Description: 1) This testcase verifies the hipMallocManaged basic scenario - supported on all devices 2) This testcase verifies the hipMallocManaged advanced scenario - supported only on HMM enabled devices 3) This testcase verifies that hipMallocManaged returns an OutOfMemory error for allocations much larger than the available memory - supported on all devices */ #include "hipMallocManagedCommon.hh" #include #include // Kernel functions __global__ void KernelMul_MngdMem(int* Hmm, int* Dptr, size_t n) { size_t index = blockIdx.x * blockDim.x + threadIdx.x; size_t stride = blockDim.x * gridDim.x; for (size_t i = index; i < n; i += stride) { Hmm[i] = Dptr[i] * 10; } } __global__ void KernelMulAdd_MngdMem(int* Hmm, size_t n) { size_t index = blockIdx.x * blockDim.x + threadIdx.x; size_t stride = blockDim.x * gridDim.x; for (size_t i = index; i < n; i += stride) { Hmm[i] = Hmm[i] * 2 + 10; } } static size_t numElements{64 * 1024 * 1024}; static unsigned blocksPerCU{6}; static unsigned threadsPerBlock{256}; /* This testcase verifies the hipMallocManaged basic scenario - supported on all devices */ TEST_CASE("Unit_hipMallocManaged_Basic") { auto managed = HmmAttrPrint(); if (managed != 1) { WARN( "GPU doesn't support hipDeviceAttributeManagedMemory attribute so defaulting to system " "memory."); } float *A, *B, *C; HIP_CHECK(hipMallocManaged(&A, numElements * sizeof(float))); HIP_CHECK(hipMallocManaged(&B, numElements * sizeof(float))); HIP_CHECK(hipMallocManaged(&C, numElements * sizeof(float))); HIP_CHECK(hipFree(A)); HIP_CHECK(hipFree(B)); HIP_CHECK(hipFree(C)); } /* This testcase verifies the hipMallocManaged advanced scenario - supported only on HMM enabled devices */ TEST_CASE("Unit_hipMallocManaged_Advanced") { auto managed = HmmAttrPrint(); if (managed != 1) { HipTest::HIP_SKIP_TEST("GPU doesn't support managed memory so skipping test."); return; } float *A, *B, *C; HIP_CHECK(hipMallocManaged(&A, numElements * sizeof(float))); HIP_CHECK(hipMallocManaged(&B, numElements * sizeof(float))); HIP_CHECK(hipMallocManaged(&C, numElements * sizeof(float))); HipTest::setDefaultData(numElements, A, B, C); hipDevice_t device = hipCpuDeviceId; HIP_CHECK(hipMemAdvise(A, numElements * sizeof(float), hipMemAdviseSetReadMostly, device)); HIP_CHECK(hipMemPrefetchAsync(A, numElements * sizeof(float), 0)); HIP_CHECK(hipMemPrefetchAsync(B, numElements * sizeof(float), 0)); HIP_CHECK(hipDeviceSynchronize()); HIP_CHECK(hipMemRangeGetAttribute(&device, sizeof(device), hipMemRangeAttributeLastPrefetchLocation, A, numElements * sizeof(float))); if (device != 0) { INFO("hipMemRangeGetAttribute error, device = " << device); } uint32_t read_only = 0xf; HIP_CHECK(hipMemRangeGetAttribute(&read_only, sizeof(read_only), hipMemRangeAttributeReadMostly, A, numElements * sizeof(float))); if (read_only != 1) { SUCCEED("hipMemRangeGetAttribute error, read_only = " << read_only); } unsigned blocks = HipTest::setNumBlocks(blocksPerCU, threadsPerBlock, numElements); hipEvent_t event0, event1; HIP_CHECK(hipEventCreate(&event0)); HIP_CHECK(hipEventCreate(&event1)); HIP_CHECK(hipEventRecord(event0, 0)); hipLaunchKernelGGL(HipTest::vectorADD, dim3(blocks), dim3(threadsPerBlock), 0, 0, static_cast(A), static_cast(B), C, numElements); HIP_CHECK(hipGetLastError()); HIP_CHECK(hipEventRecord(event1, 0)); HIP_CHECK(hipDeviceSynchronize()); float time = 0.0f; HIP_CHECK(hipEventElapsedTime(&time, event0, event1)); printf("Time %.3f ms\n", time); float maxError = 0.0f; HIP_CHECK(hipMemPrefetchAsync(B, numElements * sizeof(float), hipCpuDeviceId)); HIP_CHECK(hipDeviceSynchronize()); device = 0; HIP_CHECK(hipMemRangeGetAttribute(&device, sizeof(device), hipMemRangeAttributeLastPrefetchLocation, A, numElements * sizeof(float))); if (device != hipCpuDeviceId) { SUCCEED("hipMemRangeGetAttribute error device = " << device); } for (size_t i = 0; i < numElements; i++) { maxError = fmax(maxError, fabs(B[i] - 3.0f)); } HIP_CHECK(hipFree(A)); HIP_CHECK(hipFree(B)); HIP_CHECK(hipFree(C)); HIP_CHECK(hipEventDestroy(event0)); HIP_CHECK(hipEventDestroy(event1)); REQUIRE(maxError != 0.0f); } /* This testcase verifies that hipMallocManaged returns an OutOfMemory error for allocations much larger than the available memory - supported on all devices */ TEST_CASE("Unit_hipMallocManaged_Large") { auto managed = HmmAttrPrint(); if (managed != 1) { WARN( "GPU doesn't support hipDeviceAttributeManagedMemory attribute so defaulting to system " "memory."); } float* A; HIP_CHECK_ERROR(hipMallocManaged(&A, std::numeric_limits::max()), hipErrorOutOfMemory); }