/* Copyright (c) 2020-present 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, INCLUDING 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 ANY 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. */ /** Testcase Scenarios : (TestCase 1):: 1) Test hipMalloc() api passing zero size and confirming *ptr returning nullptr. Also pass nullptr to hipFree() api. 2) Pass maximum value of size_t for hipMalloc() api and make sure appropriate error is returned. 3) Check for hipMalloc() error code, passing invalid/null pointer. (TestCase 2):: 4) Regress hipMalloc()/hipFree() in loop for bigger chunk of allocation with adequate number of iterations and later test for kernel execution on default gpu. 5) Regress hipMalloc()/hipFree() in loop while allocating smaller chunks keeping maximum number of iterations and then run kernel code on default gpu, perfom data validation. (TestCase 3):: 6) Check hipMalloc() api adaptability when app creates small chunks of memory continuously, stores it for later use and then frees it at later point of time. (TestCase 4):: 7) Run hipMalloc() api/kernel code on same gpu parallely from parent and child processes, validate the results. (TestCase 5):: 8) Execute hipMalloc() api simultaneously on all the gpus by spawning multiple child processes. Validate buffers allocated after running kernel code. (TestCase 6):: 9) Multithread Scenario : Exercise hipMalloc() api parellely on all gpus from multiple threads and regress the api. (TestCases 2, 3, 4, 5, 6):: 10) Validate memory usage with hipMemGetInfo() while regressing hipMalloc() api. Check for any possible memory leaks. */ /* HIT_START * BUILD: %t %s ../../test_common.cpp NVCC_OPTIONS --std=c++11 * TEST_NAMED: %t hipMalloc_ArgValidation --tests 1 * TEST_NAMED: %t hipMalloc_LoopRegression_AllocFreeCycle --tests 2 * TEST_NAMED: %t hipMalloc_LoopRegression_AllocPool --tests 3 * TEST_NAMED: %t hipMallocChild_Concurrency_DefaultGpu --tests 4 * TEST_NAMED: %t hipMallocChild_Concurrency_MultiGpu --tests 5 * TEST_NAMED: %t hipMalloc_MultiThreaded_MultiGpu --tests 6 * HIT_END */ #include #include #include #include #include #include #include #include "test_common.h" /* Max alloc/free iterations for bigger chunks */ #define MAX_ALLOCFREE_BC (10000) /* Buffer size for alloc/free cycles */ #define BUFF_SIZE_AF (5*1024*1024) /* Max alloc/free iterations for smaller chunks */ #define MAX_ALLOCFREE_SC (5000000) /* Max alloc and pool iterations (TBD) */ #define MAX_ALLOCPOOL_ITER (2000000) /** * Validates data consitency on supplied gpu */ bool validateMemoryOnGPU(int gpu) { size_t Nbytes = N * sizeof(int); int *A_d, *B_d, *C_d; int *A_h, *B_h, *C_h; size_t prevAvl, prevTot, curAvl, curTot; bool TestPassed = true; HIPCHECK(hipSetDevice(gpu)); HIPCHECK(hipMemGetInfo(&prevAvl, &prevTot)); HipTest::initArrays(&A_d, &B_d, &C_d, &A_h, &B_h, &C_h, N, false); unsigned blocks = HipTest::setNumBlocks(blocksPerCU, threadsPerBlock, N); HIPCHECK(hipMemcpy(A_d, A_h, Nbytes, hipMemcpyHostToDevice)); HIPCHECK(hipMemcpy(B_d, B_h, Nbytes, hipMemcpyHostToDevice)); hipLaunchKernelGGL(HipTest::vectorADD, dim3(blocks), dim3(threadsPerBlock), 0, 0, static_cast(A_d), static_cast(B_d), C_d, N); HIPCHECK(hipMemcpy(C_h, C_d, Nbytes, hipMemcpyDeviceToHost)); if (!HipTest::checkVectorADD(A_h, B_h, C_h, N)) { printf("Validation PASSED for gpu %d from pid %d\n", gpu, getpid()); } else { printf("%s : Validation FAILED for gpu %d from pid %d\n", __func__, gpu, getpid()); TestPassed &= false; } HipTest::freeArrays(A_d, B_d, C_d, A_h, B_h, C_h, false); HIPCHECK(hipMemGetInfo(&curAvl, &curTot)); if ((prevAvl != curAvl) || (prevTot != curTot)) { printf("%s : Memory allocation mismatch observed." "Possible memory leak.", __func__); TestPassed &= false; } return TestPassed; } /** * Fetches Gpu device count */ void getDeviceCount(int *pdevCnt) { #ifdef __linux__ int fd[2], val = 0; pid_t childpid; // create pipe descriptors pipe(fd); // disable visible_devices env from shell unsetenv("ROCR_VISIBLE_DEVICES"); unsetenv("HIP_VISIBLE_DEVICES"); childpid = fork(); if (childpid > 0) { // Parent close(fd[1]); // parent will wait to read the device cnt read(fd[0], &val, sizeof(val)); // close the read-descriptor close(fd[0]); // wait for child exit wait(NULL); *pdevCnt = val; } else if (!childpid) { // Child int devCnt = 1; // writing only, no need for read-descriptor close(fd[0]); HIPCHECK(hipGetDeviceCount(&devCnt)); // send the value on the write-descriptor: write(fd[1], &devCnt, sizeof(devCnt)); // close the write descriptor: close(fd[1]); exit(0); } else { // failure *pdevCnt = 1; return; } #else HIPCHECK(hipGetDeviceCount(pdevCnt)); #endif } /** * Regress memory allocation and free in loop */ bool regressAllocInLoop(int gpu) { bool TestPassed = true; size_t tot, avail, ptot, pavail; int i = 0; int *ptr; HIPCHECK(hipSetDevice(gpu)); // Exercise allocation in loop with bigger chunks for (i = 0; i < MAX_ALLOCFREE_BC; i++) { size_t numBytes = BUFF_SIZE_AF; HIPCHECK(hipMemGetInfo(&pavail, &ptot)); HIPCHECK(hipMalloc(&ptr, numBytes)); HIPCHECK(hipMemGetInfo(&avail, &tot)); if (pavail-avail != numBytes) { printf("LoopAllocation : Memory allocation of %6.2fMB" "not matching with hipMemGetInfo - FAIL\n", numBytes/(1024.0*1024.0)); TestPassed &= false; HIPCHECK(hipFree(ptr)); break; } HIPCHECK(hipFree(ptr)); } // Exercise allocation in loop with smaller chunks and max iters HIPCHECK(hipMemGetInfo(&pavail, &ptot)); for (i = 0; i < MAX_ALLOCFREE_SC; i++) { size_t numBytes = 16; HIPCHECK(hipMalloc(&ptr, numBytes)); HIPCHECK(hipFree(ptr)); } HIPCHECK(hipMemGetInfo(&avail, &tot)); if ((pavail != avail) || (ptot != tot)) { printf("LoopAllocation : Memory allocation mismatch observed." "Possible memory leak."); TestPassed &= false; } return TestPassed; } /* * Thread func to regress alloc and check data consistency */ std::atomic g_thTestPassed(true); void threadFunc(int gpu) { g_thTestPassed = g_thTestPassed & regressAllocInLoop(gpu); g_thTestPassed = g_thTestPassed & validateMemoryOnGPU(gpu); printf("thread execution status on gpu(%d) : %d\n", gpu, g_thTestPassed.load()); } int main(int argc, char* argv[]) { HipTest::parseStandardArguments(argc, argv, true); if (p_tests == 1) { // Arg validation // Test hipMalloc for zero size bool TestPassed = true; int *ptr; HIPCHECK(hipMalloc(&ptr, 0)); // ptr expected to be reset to null ptr if (ptr) { printf("ArgValidation : Failed in zero size test\n"); TestPassed &= false; } // Free null ptr HIPCHECK(hipFree(ptr)); // Test hipMalloc for invalid arguments hipError_t ret; if ((ret = hipMalloc(NULL, 100)) != hipErrorInvalidValue) { printf("ArgValidation : Inappropritate error value returned" " for invalid argument. Error: '%s'(%d)\n", hipGetErrorString(ret), ret); TestPassed &= false; } // Test hipMalloc for Maximum value of size_t if ((ret = hipMalloc(&ptr, std::numeric_limits::max())) != hipErrorMemoryAllocation) { printf("ArgValidation : Invalid error returned for max size_t." " Error: '%s'(%d)\n", hipGetErrorString(ret), ret); TestPassed &= false; } if (TestPassed) { passed(); } else { failed("hipMalloc ArgumentValidation Failure!"); } } else if (p_tests == 2) { // Loop Regression Alloc/Free Cycle bool TestPassed = true; TestPassed &= regressAllocInLoop(0); TestPassed &= validateMemoryOnGPU(0); if (TestPassed) { passed(); } else { failed("hipMalloc_LoopRegression_AllocFreeCycle Failure!"); } } else if (p_tests == 3) { // Loop Regression Alloc and Pool size_t avail, tot, pavail, ptot; bool TestPassed = true; hipError_t err; int *ptr; std::vector ptrlist; HIPCHECK(hipMemGetInfo(&pavail, &ptot)); // Allocate small chunks of memory million times for (int i = 0; i < MAX_ALLOCPOOL_ITER; i++) { // Iterations TBD if ((err = hipMalloc(&ptr, 10)) != hipSuccess) { HIPCHECK(hipMemGetInfo(&avail, &tot)); printf("Loop regression pool allocation failure. " "Total gpu memory : %6.2fMB, Free memory %6.2fMB iter %d error '%s'\n", tot/(1024.0*1024.0), avail/(1024.0*1024.0), i, hipGetErrorString(err)); TestPassed &= false; break; } // Store pointers allocated to emulate memory pool of app ptrlist.push_back(ptr); } // Free ptrs at later point of time for ( auto &t : ptrlist ) { HIPCHECK(hipFree(t)); } HIPCHECK(hipMemGetInfo(&avail, &tot)); TestPassed &= validateMemoryOnGPU(0); if ((pavail != avail) || (ptot != tot)) { printf("%s : Memory allocation mismatch observed. Possible memory leak.", __func__); TestPassed &= false; } if (TestPassed) { passed(); } else { failed("hipMalloc_LoopRegression_AllocPool failure!"); } } else if (p_tests == 4) { bool TestPassed = true; #ifdef __linux__ // Parallel execution of parent and child on gpu0 int pid; if ((pid = fork()) < 0) { printf("Child_Concurrency_Gpu0 : fork() returned error %d.", pid); TestPassed &= false; } else if (!pid) { // Child process bool TestPassedChild = true; TestPassedChild = validateMemoryOnGPU(0); if (TestPassedChild) { exit(0); // child exit with success status } else { printf("Child_Concurrency_Gpu0 : childpid %d failed\n", getpid()); exit(1); // child exit with failure status } } else { // Parent process int exitStatus; TestPassed = validateMemoryOnGPU(0); pid = wait(&exitStatus); if ( WEXITSTATUS(exitStatus) || ( pid < 0 ) ) TestPassed &= false; } #else printf("Test hipMallocChild_Concurrency_DefaultGpu skipped on non-linux\n"); #endif // TC scenarios specific to linux // are treated as pass in windows. if (TestPassed) { passed(); } else { failed("hipMallocChild_Concurrency_DefaultGpu Failed!"); } } else if (p_tests == 5) { bool TestPassed = true; #ifdef __linux__ // Parallel execution on multiple gpus from different child processes int devCnt = 1, pid = 0, cumStatus = 0; // Get GPU count getDeviceCount(&devCnt); // Spawn child for each GPU for (int gpu = 0; gpu < devCnt; gpu++) { if ((pid = fork()) < 0) { printf("Child_Concurrency_MultiGpu : fork() returned error %d\n", pid); failed("Test Failed!"); } else if (!pid) { // Child process bool TestPassedChild = true; TestPassedChild = validateMemoryOnGPU(gpu); if (TestPassedChild) { exit(0); // child exit with success status } else { printf("Child_Concurrency_MultiGpu : childpid %d failed\n", getpid()); exit(1); // child exit with failure status } } } // Parent shall wait for child to complete for (int i = 0; i < devCnt; i++) { int pidwait = 0, exitStatus; pidwait = wait(&exitStatus); if (pidwait < 0) { TestPassed &= false; break; } cumStatus |= WEXITSTATUS(exitStatus); } // Cummulative status of all child if (cumStatus) { TestPassed &= false; } #else printf("Test hipMallocChild_Concurrency_MultiGpu skipped on non-linux\n"); #endif // TC scenarios specific to linux // are treated as pass in windows. if (TestPassed) { passed(); } else { failed("hipMallocChild_Concurrency_MultiGpu Failed!"); } } else if (p_tests == 6) { // Multithreaded multiple gpu execution std::vector threadlist; int devCnt = 1; // Get GPU count getDeviceCount(&devCnt); for (int i = 0; i < devCnt; i++) { threadlist.push_back(std::thread(threadFunc, i)); } for (auto &t : threadlist) { t.join(); } if (g_thTestPassed) { passed(); } else { failed("hipMalloc_MultiThreaded_MultiGpu Failed!"); } } else { failed("Didnt receive any valid option. Try options 1 to 6\n"); } }