Atul Kulkarni
e4aef19511
* Added new unit tests for AllReduce with Bias API
* Address review comments
[ROCm/rccl commit: 7c12b0b76b]
697 líneas
23 KiB
C++
697 líneas
23 KiB
C++
/*************************************************************************
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* Copyright (c) 2023 Advanced Micro Devices, Inc. All rights reserved.
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*
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* See LICENSE.txt for license information
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************************************************************************/
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#include "TestBed.hpp"
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#include "CallCollectiveForked.hpp"
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namespace RcclUnitTesting
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{
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TEST(AllReduce, OutOfPlace)
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{
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TestBed testBed;
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// Configuration
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std::vector<ncclFunc_t> const funcTypes = {ncclCollAllReduce};
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std::vector<ncclDataType_t> const dataTypes = {ncclFloat32, ncclFloat8e4m3, ncclFloat8e5m2};
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std::vector<ncclRedOp_t> const redOps = {ncclSum};
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std::vector<int> const roots = {0};
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std::vector<int> const numElements = {393216, 384};
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std::vector<bool> const inPlaceList = {false};
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std::vector<bool> const managedMemList = {false};
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std::vector<bool> const useHipGraphList = {false};
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testBed.RunSimpleSweep(funcTypes, dataTypes, redOps, roots, numElements,
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inPlaceList, managedMemList, useHipGraphList);
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testBed.Finalize();
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}
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TEST(AllReduce, OutOfPlaceGraph)
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{
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TestBed testBed;
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// Configuration
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std::vector<ncclFunc_t> const funcTypes = {ncclCollAllReduce};
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std::vector<ncclDataType_t> const dataTypes = {ncclFloat16, ncclFloat64, ncclFloat8e4m3, ncclFloat8e5m2};
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std::vector<ncclRedOp_t> const redOps = {ncclMin};
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std::vector<int> const roots = {0};
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std::vector<int> const numElements = {12888};
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std::vector<bool> const inPlaceList = {false};
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std::vector<bool> const managedMemList = {false};
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std::vector<bool> const useHipGraphList = {true};
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testBed.RunSimpleSweep(funcTypes, dataTypes, redOps, roots, numElements,
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inPlaceList, managedMemList, useHipGraphList);
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testBed.Finalize();
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}
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TEST(AllReduce, InPlace)
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{
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TestBed testBed;
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// Configuration
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std::vector<ncclFunc_t> const funcTypes = {ncclCollAllReduce};
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std::vector<ncclDataType_t> const dataTypes = {ncclInt32, ncclInt8};
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std::vector<ncclRedOp_t> const redOps = {ncclProd};
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std::vector<int> const roots = {0};
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std::vector<int> const numElements = {384};
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std::vector<bool> const inPlaceList = {true};
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std::vector<bool> const managedMemList = {false};
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std::vector<bool> const useHipGraphList = {false};
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testBed.RunSimpleSweep(funcTypes, dataTypes, redOps, roots, numElements,
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inPlaceList, managedMemList, useHipGraphList);
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testBed.Finalize();
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}
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TEST(AllReduce, InPlaceGraph)
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{
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TestBed testBed;
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// Configuration
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std::vector<ncclFunc_t> const funcTypes = {ncclCollAllReduce};
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std::vector<ncclDataType_t> const dataTypes = {ncclInt32, ncclFloat8e4m3, ncclFloat8e5m2};
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std::vector<ncclRedOp_t> const redOps = {ncclMax};
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std::vector<int> const roots = {0};
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std::vector<int> const numElements = {393216, 12888, 384};
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std::vector<bool> const inPlaceList = {true};
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std::vector<bool> const managedMemList = {false};
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std::vector<bool> const useHipGraphList = {true};
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testBed.RunSimpleSweep(funcTypes, dataTypes, redOps, roots, numElements,
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inPlaceList, managedMemList, useHipGraphList);
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testBed.Finalize();
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}
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TEST(AllReduce, ManagedMem)
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{
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TestBed testBed;
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// Configuration
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std::vector<ncclFunc_t> const funcTypes = {ncclCollAllReduce};
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std::vector<ncclDataType_t> const dataTypes = {ncclUint8, ncclUint64};
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std::vector<ncclRedOp_t> const redOps = {ncclSum};
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std::vector<int> const roots = {0};
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std::vector<int> const numElements = {2500};
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std::vector<bool> const inPlaceList = {false};
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std::vector<bool> const managedMemList = {true};
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std::vector<bool> const useHipGraphList = {false};
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testBed.RunSimpleSweep(funcTypes, dataTypes, redOps, roots, numElements,
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inPlaceList, managedMemList, useHipGraphList);
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testBed.Finalize();
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}
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TEST(AllReduce, Channels)
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{
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TestBed testBed;
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if(testBed.ev.maxGpus >= 8) {
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if(testBed.ev.isGfx94) {
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// Configuration
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std::vector<ncclFunc_t> const funcTypes = {ncclCollAllReduce};
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std::vector<ncclDataType_t> const dataTypes = {ncclBfloat16};
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std::vector<ncclRedOp_t> const redOps = {ncclSum};
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std::vector<int> const roots = {0};
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std::vector<int> const numElements = {64 * 1024 * 1024, 1024};
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std::vector<bool> const inPlaceList = {false};
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std::vector<bool> const managedMemList = {false};
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std::vector<bool> const useHipGraphList = {false, true};
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std::vector<const char *> const channelList = {"84", "112"};
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bool const enableSweep = false;
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for (auto channel : channelList) {
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setenv("NCCL_MIN_NCHANNELS", channel, 1);
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testBed.RunSimpleSweep(funcTypes, dataTypes, redOps, roots, numElements,
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inPlaceList, managedMemList, useHipGraphList, enableSweep);
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testBed.Finalize();
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unsetenv("NCCL_MIN_NCHANNELS");
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}
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}
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}
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}
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TEST(AllReduce, ManagedMemGraph)
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{
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TestBed testBed;
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// Configuration
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std::vector<ncclFunc_t> const funcTypes = {ncclCollAllReduce};
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std::vector<ncclDataType_t> const dataTypes = {ncclFloat64, ncclBfloat16};
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std::vector<ncclRedOp_t> const redOps = {ncclSum};
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std::vector<int> const roots = {0};
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std::vector<int> const numElements = {4314};
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std::vector<bool> const inPlaceList = {false};
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std::vector<bool> const managedMemList = {true};
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std::vector<bool> const useHipGraphList = {true};
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testBed.RunSimpleSweep(funcTypes, dataTypes, redOps, roots, numElements,
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inPlaceList, managedMemList, useHipGraphList);
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testBed.Finalize();
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}
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// This tests using custom pre-mult scalars reductions
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TEST(AllReduce, PreMultScalar)
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{
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TestBed testBed;
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// Configuration
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ncclFunc_t const funcType = ncclCollAllReduce;
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std::vector<ncclDataType_t> const& dataTypes = {ncclFloat32};
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ncclRedOp_t const redOp = ncclSum;
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std::vector<int> const numElements = {384 * 1024, 384 * 32, 384};
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bool const inPlace = false;
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bool const useManagedMem = false;
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OptionalColArgs options;
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// Terminate the test as soon as first failure occurs
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bool isCorrect = true;
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for (int totalRanks : testBed.ev.GetNumGpusList())
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for (int isMultiProcess : testBed.ev.GetIsMultiProcessList())
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{
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int const numProcesses = isMultiProcess ? totalRanks : 1;
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const std::vector<int>& gpuPriorityOrder = testBed.ev.GetGpuPriorityOrder();
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testBed.InitComms(TestBed::GetDeviceIdsList(numProcesses, totalRanks, gpuPriorityOrder));
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for (int dataIdx = 0; dataIdx < dataTypes.size() && isCorrect; ++dataIdx)
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{
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ncclDataType_t const dataType = dataTypes[dataIdx];
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// Set scalars per rank
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PtrUnion scalarsPerRank;
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scalarsPerRank.AllocateCpuMem(totalRanks * DataTypeToBytes(dataType));
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for (int i = 0; i < totalRanks; i++)
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{
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double F = i;
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scalarsPerRank.Set(dataType, i, i, F);
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}
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int const numBytes = totalRanks * DataTypeToBytes(dataType);
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memcpy(options.scalarTransport.ptr, scalarsPerRank.ptr, numBytes);
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// Test various scalar residence modes
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for (int scalarMode = 0; scalarMode <= 1 && isCorrect; ++scalarMode)
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{
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if (testBed.ev.showNames)
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INFO("%s %d-ranks AllReduce (custom-scalar Mode %d %s)\n",
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isMultiProcess ? "MP" : "SP",
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totalRanks, scalarMode, ncclDataTypeNames[dataType]);
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for (int i = 0; i < numElements.size() && isCorrect; ++i)
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{
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options.scalarMode = scalarMode;
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options.redOp = redOp;
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testBed.SetCollectiveArgs(funcType, dataType,
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numElements[i], numElements[i],
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options);
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// For performance, only allocate and prepare data on largest size
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if (i == 0)
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{
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testBed.AllocateMem(inPlace, useManagedMem);
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testBed.PrepareData();
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}
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testBed.ExecuteCollectives();
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testBed.ValidateResults(isCorrect);
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}
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testBed.DeallocateMem();
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}
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}
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testBed.DestroyComms();
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}
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testBed.Finalize();
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}
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TEST(AllReduce, UserBufferRegistration)
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{
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const int nranks = 8;
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size_t count = 2048;
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std::vector<int> sendBuff(count, 0);
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std::vector<int> recvBuff(count, 0);
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std::vector<int> expected(count, 0);
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for (int i = 0; i < count; ++i){
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sendBuff[i] = i;
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expected[i] = i * nranks;
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}
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callCollectiveForked(nranks, ncclCollAllReduce, sendBuff, recvBuff, expected);
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}
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TEST(AllReduce, ManagedMemUserBufferRegistration)
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{
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const int nranks = 8;
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size_t count = 2048;
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std::vector<int> sendBuff(count, 0);
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std::vector<int> recvBuff(count, 0);
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std::vector<int> expected(count, 0);
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const bool use_managed_mem = true;
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for (int i = 0; i < count; ++i){
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sendBuff[i] = i;
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expected[i] = i * nranks;
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}
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callCollectiveForked(nranks, ncclCollAllReduce, sendBuff, recvBuff, expected, use_managed_mem);
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}
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#ifdef RCCL_ALLREDUCE_WITH_BIAS
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// Note: All bias tests require:
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// nRanks >= 2 (bias NOT supported for single rank)
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// Named constants for bias test configuration
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namespace BiasTestConstants
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{
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// Element counts for different operations
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constexpr std::initializer_list<int> STANDARD_ELEM_COUNTS = {2048, 384}; // For Sum/Max/Min
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constexpr std::initializer_list<int> PROD_ELEM_COUNTS_MEDIUM = {32}; // For Int32/Uint32 Prod
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constexpr std::initializer_list<int> PROD_ELEM_COUNTS_LARGE = {64}; // For Int8/Uint8/Int64/Uint64/Float Prod
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// Bias and input pattern constants
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constexpr int BIAS_CONSTANT_ONE = 1; // Use constant bias value of 1 (prevents overflow)
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constexpr int BIAS_INCREMENTAL_PATTERN
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= -1; // Use incremental pattern: bias[i] = i (more thorough testing)
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constexpr int INPUT_RANK_BASED_PATTERN
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= -1; // Use rank-based pattern: input[rank][i] = (rank+i)%256
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constexpr int INPUT_CONSTANT_ONE = 1; // Use constant input value of 1 (prevents overflow)
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} // namespace BiasTestConstants
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/*
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* @brief Helper function for running bias tests with specific datatype and redOp
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* @param dataType Data type
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* @param redOp Reduction operation
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* @param numElements Number of elements
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* @param biasConstVal Bias constant value, -1 for incremental bias
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* @param inputConstVal Input constant value, -1 for rank-based input
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*/
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void RunBiasTest(ncclDataType_t dataType,
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ncclRedOp_t redOp,
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std::vector<int> numElements,
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int biasConstVal = BiasTestConstants::BIAS_INCREMENTAL_PATTERN,
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int inputConstVal = BiasTestConstants::INPUT_RANK_BASED_PATTERN)
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{
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// Create TestBed first (doesn't create child processes yet)
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TestBed testBed;
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// Check if architecture is gfx94 (covers gfx942) or gfx95 (covers gfx950)
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if (!testBed.ev.isGfx94 && !testBed.ev.isGfx95)
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{
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INFO("SKIPPED: AllReduce with Bias is only supported on gfx942 or gfx950 architectures.\n");
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return;
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}
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bool const inPlace = false;
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bool const useManagedMem = false;
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bool const useHipGraph = false;
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OptionalColArgs options;
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options.useBias = true;
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options.redOp = redOp;
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options.biasConstantValue = biasConstVal;
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options.inputConstantValue = inputConstVal;
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bool isCorrect = true;
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for(int totalRanks : testBed.ev.GetNumGpusList())
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{
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if(totalRanks < 2)
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continue;
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int const numProcesses = totalRanks;
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bool const isMultiProcess = true;
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const std::vector<int>& gpuPriorityOrder = testBed.ev.GetGpuPriorityOrder();
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testBed.InitComms(TestBed::GetDeviceIdsList(numProcesses, totalRanks, gpuPriorityOrder));
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for(auto numElem : numElements)
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{
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if(!isCorrect)
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break;
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if(testBed.ev.showNames)
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{
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std::string name = testBed.GetTestCaseName(totalRanks,
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isMultiProcess,
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ncclCollAllReduce,
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dataType,
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redOp,
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-1,
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inPlace,
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useManagedMem,
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useHipGraph);
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INFO(" %s (with bias, count=%d)\n", name.c_str(), numElem);
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}
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options.biasNumElements = numElem;
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testBed.SetCollectiveArgs(ncclCollAllReduce,
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dataType,
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numElem,
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numElem,
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options,
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-1,
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0,
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-1);
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testBed.AllocateMem(inPlace, useManagedMem);
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testBed.PrepareData();
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testBed.ExecuteCollectives({}, useHipGraph);
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testBed.ValidateResults(isCorrect);
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testBed.DeallocateMem();
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}
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testBed.DestroyComms();
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}
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testBed.Finalize();
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}
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// Int8 Tests
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TEST(AllReduce, BiasInt8_Sum)
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{
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using namespace BiasTestConstants;
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RunBiasTest(ncclInt8,
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ncclSum,
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STANDARD_ELEM_COUNTS,
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BIAS_CONSTANT_ONE,
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INPUT_RANK_BASED_PATTERN);
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}
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TEST(AllReduce, BiasInt8_Max)
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{
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using namespace BiasTestConstants;
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RunBiasTest(ncclInt8,
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ncclMax,
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STANDARD_ELEM_COUNTS,
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BIAS_CONSTANT_ONE,
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INPUT_RANK_BASED_PATTERN);
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}
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TEST(AllReduce, BiasInt8_Min)
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{
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using namespace BiasTestConstants;
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RunBiasTest(ncclInt8,
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ncclMin,
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STANDARD_ELEM_COUNTS,
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BIAS_CONSTANT_ONE,
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INPUT_RANK_BASED_PATTERN);
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}
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TEST(AllReduce, BiasInt8_Prod)
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{
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using namespace BiasTestConstants;
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RunBiasTest(ncclInt8,
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ncclProd,
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PROD_ELEM_COUNTS_LARGE,
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BIAS_CONSTANT_ONE,
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INPUT_CONSTANT_ONE);
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}
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// Uint8 Tests
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TEST(AllReduce, BiasUint8_Sum)
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{
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using namespace BiasTestConstants;
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RunBiasTest(ncclUint8,
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ncclSum,
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STANDARD_ELEM_COUNTS,
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BIAS_CONSTANT_ONE,
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INPUT_RANK_BASED_PATTERN);
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}
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TEST(AllReduce, BiasUint8_Max)
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{
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using namespace BiasTestConstants;
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RunBiasTest(ncclUint8,
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ncclMax,
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STANDARD_ELEM_COUNTS,
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BIAS_CONSTANT_ONE,
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INPUT_RANK_BASED_PATTERN);
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}
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TEST(AllReduce, BiasUint8_Min)
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{
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using namespace BiasTestConstants;
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RunBiasTest(ncclUint8,
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ncclMin,
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STANDARD_ELEM_COUNTS,
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BIAS_CONSTANT_ONE,
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INPUT_RANK_BASED_PATTERN);
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}
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TEST(AllReduce, BiasUint8_Prod)
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{
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using namespace BiasTestConstants;
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RunBiasTest(ncclUint8,
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ncclProd,
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PROD_ELEM_COUNTS_LARGE,
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BIAS_CONSTANT_ONE,
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INPUT_CONSTANT_ONE);
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}
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// Int32 Tests
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TEST(AllReduce, BiasInt32_Sum)
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{
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using namespace BiasTestConstants;
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RunBiasTest(ncclInt32,
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ncclSum,
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STANDARD_ELEM_COUNTS,
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BIAS_CONSTANT_ONE,
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INPUT_RANK_BASED_PATTERN);
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}
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TEST(AllReduce, BiasInt32_Max)
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{
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using namespace BiasTestConstants;
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RunBiasTest(ncclInt32,
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ncclMax,
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STANDARD_ELEM_COUNTS,
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BIAS_CONSTANT_ONE,
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INPUT_RANK_BASED_PATTERN);
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}
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TEST(AllReduce, BiasInt32_Min)
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{
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using namespace BiasTestConstants;
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RunBiasTest(ncclInt32,
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ncclMin,
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STANDARD_ELEM_COUNTS,
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BIAS_CONSTANT_ONE,
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INPUT_RANK_BASED_PATTERN);
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}
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TEST(AllReduce, BiasInt32_Prod)
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{
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using namespace BiasTestConstants;
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RunBiasTest(ncclInt32,
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ncclProd,
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PROD_ELEM_COUNTS_MEDIUM,
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BIAS_CONSTANT_ONE,
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INPUT_CONSTANT_ONE);
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}
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// Uint32 Tests
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TEST(AllReduce, BiasUint32_Sum)
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{
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using namespace BiasTestConstants;
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RunBiasTest(ncclUint32,
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ncclSum,
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STANDARD_ELEM_COUNTS,
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BIAS_CONSTANT_ONE,
|
|
INPUT_RANK_BASED_PATTERN);
|
|
}
|
|
|
|
TEST(AllReduce, BiasUint32_Max)
|
|
{
|
|
using namespace BiasTestConstants;
|
|
RunBiasTest(ncclUint32,
|
|
ncclMax,
|
|
STANDARD_ELEM_COUNTS,
|
|
BIAS_CONSTANT_ONE,
|
|
INPUT_RANK_BASED_PATTERN);
|
|
}
|
|
|
|
TEST(AllReduce, BiasUint32_Min)
|
|
{
|
|
using namespace BiasTestConstants;
|
|
RunBiasTest(ncclUint32,
|
|
ncclMin,
|
|
STANDARD_ELEM_COUNTS,
|
|
BIAS_CONSTANT_ONE,
|
|
INPUT_RANK_BASED_PATTERN);
|
|
}
|
|
|
|
TEST(AllReduce, BiasUint32_Prod)
|
|
{
|
|
using namespace BiasTestConstants;
|
|
RunBiasTest(ncclUint32,
|
|
ncclProd,
|
|
PROD_ELEM_COUNTS_MEDIUM,
|
|
BIAS_CONSTANT_ONE,
|
|
INPUT_CONSTANT_ONE);
|
|
}
|
|
|
|
// Int64 Tests
|
|
TEST(AllReduce, BiasInt64_Sum)
|
|
{
|
|
using namespace BiasTestConstants;
|
|
RunBiasTest(ncclInt64,
|
|
ncclSum,
|
|
STANDARD_ELEM_COUNTS,
|
|
BIAS_INCREMENTAL_PATTERN,
|
|
INPUT_RANK_BASED_PATTERN);
|
|
}
|
|
|
|
TEST(AllReduce, BiasInt64_Max)
|
|
{
|
|
using namespace BiasTestConstants;
|
|
RunBiasTest(ncclInt64,
|
|
ncclMax,
|
|
STANDARD_ELEM_COUNTS,
|
|
BIAS_INCREMENTAL_PATTERN,
|
|
INPUT_RANK_BASED_PATTERN);
|
|
}
|
|
|
|
TEST(AllReduce, BiasInt64_Min)
|
|
{
|
|
using namespace BiasTestConstants;
|
|
RunBiasTest(ncclInt64,
|
|
ncclMin,
|
|
STANDARD_ELEM_COUNTS,
|
|
BIAS_INCREMENTAL_PATTERN,
|
|
INPUT_RANK_BASED_PATTERN);
|
|
}
|
|
|
|
TEST(AllReduce, BiasInt64_Prod)
|
|
{
|
|
using namespace BiasTestConstants;
|
|
RunBiasTest(ncclInt64,
|
|
ncclProd,
|
|
PROD_ELEM_COUNTS_LARGE,
|
|
BIAS_INCREMENTAL_PATTERN,
|
|
INPUT_CONSTANT_ONE);
|
|
}
|
|
|
|
// Uint64 Tests
|
|
TEST(AllReduce, BiasUint64_Sum)
|
|
{
|
|
using namespace BiasTestConstants;
|
|
RunBiasTest(ncclUint64,
|
|
ncclSum,
|
|
STANDARD_ELEM_COUNTS,
|
|
BIAS_INCREMENTAL_PATTERN,
|
|
INPUT_RANK_BASED_PATTERN);
|
|
}
|
|
|
|
TEST(AllReduce, BiasUint64_Max)
|
|
{
|
|
using namespace BiasTestConstants;
|
|
RunBiasTest(ncclUint64,
|
|
ncclMax,
|
|
STANDARD_ELEM_COUNTS,
|
|
BIAS_INCREMENTAL_PATTERN,
|
|
INPUT_RANK_BASED_PATTERN);
|
|
}
|
|
|
|
TEST(AllReduce, BiasUint64_Min)
|
|
{
|
|
using namespace BiasTestConstants;
|
|
RunBiasTest(ncclUint64,
|
|
ncclMin,
|
|
STANDARD_ELEM_COUNTS,
|
|
BIAS_INCREMENTAL_PATTERN,
|
|
INPUT_RANK_BASED_PATTERN);
|
|
}
|
|
|
|
TEST(AllReduce, BiasUint64_Prod)
|
|
{
|
|
using namespace BiasTestConstants;
|
|
RunBiasTest(ncclUint64,
|
|
ncclProd,
|
|
PROD_ELEM_COUNTS_LARGE,
|
|
BIAS_INCREMENTAL_PATTERN,
|
|
INPUT_CONSTANT_ONE);
|
|
}
|
|
|
|
// Float32 Tests
|
|
TEST(AllReduce, BiasFloat32_Sum)
|
|
{
|
|
using namespace BiasTestConstants;
|
|
RunBiasTest(ncclFloat32,
|
|
ncclSum,
|
|
STANDARD_ELEM_COUNTS,
|
|
BIAS_INCREMENTAL_PATTERN,
|
|
INPUT_RANK_BASED_PATTERN);
|
|
}
|
|
|
|
TEST(AllReduce, BiasFloat32_Max)
|
|
{
|
|
using namespace BiasTestConstants;
|
|
RunBiasTest(ncclFloat32,
|
|
ncclMax,
|
|
STANDARD_ELEM_COUNTS,
|
|
BIAS_INCREMENTAL_PATTERN,
|
|
INPUT_RANK_BASED_PATTERN);
|
|
}
|
|
|
|
TEST(AllReduce, BiasFloat32_Min)
|
|
{
|
|
using namespace BiasTestConstants;
|
|
RunBiasTest(ncclFloat32,
|
|
ncclMin,
|
|
STANDARD_ELEM_COUNTS,
|
|
BIAS_INCREMENTAL_PATTERN,
|
|
INPUT_RANK_BASED_PATTERN);
|
|
}
|
|
|
|
TEST(AllReduce, BiasFloat32_Prod)
|
|
{
|
|
using namespace BiasTestConstants;
|
|
RunBiasTest(ncclFloat32,
|
|
ncclProd,
|
|
PROD_ELEM_COUNTS_LARGE,
|
|
BIAS_INCREMENTAL_PATTERN,
|
|
INPUT_CONSTANT_ONE);
|
|
}
|
|
|
|
// Float64 Tests
|
|
TEST(AllReduce, BiasFloat64_Sum)
|
|
{
|
|
using namespace BiasTestConstants;
|
|
RunBiasTest(ncclFloat64,
|
|
ncclSum,
|
|
STANDARD_ELEM_COUNTS,
|
|
BIAS_INCREMENTAL_PATTERN,
|
|
INPUT_RANK_BASED_PATTERN);
|
|
}
|
|
|
|
TEST(AllReduce, BiasFloat64_Max)
|
|
{
|
|
using namespace BiasTestConstants;
|
|
RunBiasTest(ncclFloat64,
|
|
ncclMax,
|
|
STANDARD_ELEM_COUNTS,
|
|
BIAS_INCREMENTAL_PATTERN,
|
|
INPUT_RANK_BASED_PATTERN);
|
|
}
|
|
|
|
TEST(AllReduce, BiasFloat64_Min)
|
|
{
|
|
using namespace BiasTestConstants;
|
|
RunBiasTest(ncclFloat64,
|
|
ncclMin,
|
|
STANDARD_ELEM_COUNTS,
|
|
BIAS_INCREMENTAL_PATTERN,
|
|
INPUT_RANK_BASED_PATTERN);
|
|
}
|
|
|
|
TEST(AllReduce, BiasFloat64_Prod)
|
|
{
|
|
using namespace BiasTestConstants;
|
|
RunBiasTest(ncclFloat64,
|
|
ncclProd,
|
|
PROD_ELEM_COUNTS_LARGE,
|
|
BIAS_INCREMENTAL_PATTERN,
|
|
INPUT_CONSTANT_ONE);
|
|
}
|
|
|
|
#else
|
|
// If RCCL_ALLREDUCE_WITH_BIAS is not defined, skip all bias tests
|
|
TEST(AllReduce, BiasNotAvailable)
|
|
{
|
|
INFO("SKIPPED: RCCL_ALLREDUCE_WITH_BIAS not defined - bias tests skipped\n");
|
|
return;
|
|
}
|
|
#endif
|
|
}
|