29ad0f5fbe
Refactoring and consolidating single-process / multi-process unit testing
343 lines
13 KiB
C++
343 lines
13 KiB
C++
/*************************************************************************
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* Copyright (c) 2022 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 "CollectiveArgs.hpp"
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#include "PrepDataFuncs.hpp"
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#include <cstdio>
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#include <hip/hip_runtime.h>
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namespace RcclUnitTesting
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{
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ErrCode DefaultPrepareDataFunc(CollectiveArgs &collArgs)
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{
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switch (collArgs.funcType)
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{
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case ncclCollBroadcast: return DefaultPrepData_Broadcast(collArgs);
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case ncclCollReduce: return DefaultPrepData_Reduce(collArgs, false);
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case ncclCollAllGather: return DefaultPrepData_Gather(collArgs, true);
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case ncclCollReduceScatter: return DefaultPrepData_ReduceScatter(collArgs);
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case ncclCollAllReduce: return DefaultPrepData_Reduce(collArgs, true);
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case ncclCollGather: return DefaultPrepData_Gather(collArgs, false);
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case ncclCollScatter: return DefaultPrepData_Scatter(collArgs);
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case ncclCollAllToAll: return DefaultPrepData_AllToAll(collArgs);
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//case ncclCollSendRecv: return DefaultPrepData_SendRecv(collArgs);
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default:
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ERROR("Unknown func type %d\n", collArgs.funcType);
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return TEST_FAIL;
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}
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}
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ErrCode CheckAllocation(CollectiveArgs const& collArgs)
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{
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if (collArgs.numInputElements > collArgs.numInputElementsAllocated)
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{
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ERROR("Number of input elements (%lu) exceeds the number of allocated input elements (%lu)\n",
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collArgs.numInputElements, collArgs.numInputElementsAllocated);
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return TEST_FAIL;
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}
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if (collArgs.numOutputElements > collArgs.numOutputElementsAllocated)
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{
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ERROR("Number of output elements (%lu) exceeds the number of allocated output elements (%lu)\n",
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collArgs.numOutputElements, collArgs.numOutputElementsAllocated);
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return TEST_FAIL;
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}
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return TEST_SUCCESS;
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}
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ErrCode DefaultPrepData_Broadcast(CollectiveArgs &collArgs)
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{
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CHECK_CALL(CheckAllocation(collArgs));
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if (collArgs.numInputElements != collArgs.numOutputElements)
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{
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ERROR("Number of input elements must match number of output elements for Broadcast\n");
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return TEST_FAIL;
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}
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size_t const numBytes = collArgs.numInputElements * DataTypeToBytes(collArgs.dataType);
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// Clear output for all ranks (done before filling input in case of in-place)
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CHECK_CALL(collArgs.outputGpu.ClearGpuMem(numBytes));
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// Only root needs input pattern
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if (collArgs.globalRank == collArgs.root)
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CHECK_CALL(collArgs.inputGpu.FillPattern(collArgs.dataType,
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collArgs.numInputElements,
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collArgs.root, true));
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// Otherwise all other ranks expected output is the same as input of root
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return collArgs.expected.FillPattern(collArgs.dataType,
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collArgs.numInputElements,
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collArgs.root,
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false);
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}
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ErrCode DefaultPrepData_Reduce(CollectiveArgs &collArgs, bool const isAllReduce)
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{
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CHECK_CALL(CheckAllocation(collArgs));
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if (collArgs.numInputElements != collArgs.numOutputElements)
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{
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ERROR("Number of input elements must match number of output elements for Reduce\n");
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return TEST_FAIL;
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}
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size_t const numBytes = collArgs.numInputElements * DataTypeToBytes(collArgs.dataType);
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// Clear output for all ranks (done before filling input in case of in-place)
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CHECK_CALL(collArgs.outputGpu.ClearGpuMem(numBytes));
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// Clear expected buffer for holding reduction
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PtrUnion result;
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CHECK_CALL(result.Attach(collArgs.expected));
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CHECK_CALL(result.ClearCpuMem(numBytes));
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// If average or custom reduction operator is used, perform a summation instead
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ncclRedOp_t const tempOp = (collArgs.redOp >= ncclAvg ? ncclSum : collArgs.redOp);
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// Loop over each rank and generate their input into a temp buffer, then reduce
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PtrUnion scalarsPerRank;
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scalarsPerRank.Attach(collArgs.scalarTransport.ptr);
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PtrUnion tempInputCpu;
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CHECK_CALL(tempInputCpu.Attach(collArgs.outputCpu));
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for (int rank = 0; rank < collArgs.totalRanks; ++rank)
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{
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// Generate temporary input for this rank
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CHECK_CALL(tempInputCpu.FillPattern(collArgs.dataType, collArgs.numInputElements, rank, false));
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// Copy the pre-scaled input into GPU memory for the correct rank
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if (rank == collArgs.globalRank)
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{
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CHECK_HIP(hipMemcpy(collArgs.inputGpu.ptr, tempInputCpu.ptr, numBytes, hipMemcpyHostToDevice));
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}
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// Scale the temporary input by local scalar for this rank
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// (Used by custom reduction ops)
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if (collArgs.scalarMode >= 0)
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{
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CHECK_CALL(tempInputCpu.Scale(collArgs.dataType, collArgs.numInputElements,
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scalarsPerRank, rank));
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}
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// Any rank that requires output reduces the scaled-inputs
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if (isAllReduce || collArgs.root == collArgs.globalRank)
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{
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if (rank == 0)
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{
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memcpy(result.ptr, tempInputCpu.ptr, numBytes);
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}
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else
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{
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CHECK_CALL(result.Reduce(collArgs.dataType, collArgs.numInputElements,
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tempInputCpu, tempOp));
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}
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}
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}
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// Perform averaging if necessary
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if (collArgs.redOp == ncclAvg && (isAllReduce || collArgs.root == collArgs.globalRank))
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{
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CHECK_CALL(result.DivideByInt(collArgs.dataType, collArgs.numInputElements, collArgs.totalRanks));
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}
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return TEST_SUCCESS;
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}
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ErrCode DefaultPrepData_Gather(CollectiveArgs &collArgs, bool const isAllGather)
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{
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CHECK_CALL(CheckAllocation(collArgs));
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if (collArgs.totalRanks * collArgs.numInputElements != collArgs.numOutputElements)
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{
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ERROR("# of output elements must be total ranks * # input elements for AllGather\n");
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return TEST_FAIL;
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}
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// Clear output for all ranks (done before filling input in case of in-place)
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size_t const numInputBytes = collArgs.numInputElements * DataTypeToBytes(collArgs.dataType);
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size_t const numOutputBytes = collArgs.numOutputElements * DataTypeToBytes(collArgs.dataType);
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CHECK_CALL(collArgs.inputGpu.ClearGpuMem(numInputBytes));
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CHECK_CALL(collArgs.outputGpu.ClearGpuMem(numOutputBytes));
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PtrUnion result;
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CHECK_CALL(result.Attach(collArgs.expected.ptr));
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CHECK_CALL(result.ClearCpuMem(numOutputBytes));
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// Use outputCpu buffer to store temporary input
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PtrUnion tempInputCpu;
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CHECK_CALL(tempInputCpu.Attach(collArgs.outputCpu.ptr));
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for (int rank = 0; rank < collArgs.totalRanks; ++rank)
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{
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CHECK_CALL(tempInputCpu.FillPattern(collArgs.dataType, collArgs.numInputElements, rank, false));
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if (rank == collArgs.globalRank)
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{
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CHECK_HIP(hipMemcpy(collArgs.inputGpu.ptr, tempInputCpu.ptr, numInputBytes, hipMemcpyHostToDevice));
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}
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if (isAllGather || collArgs.root == collArgs.globalRank)
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{
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memcpy(result.I1 + (rank * numInputBytes), tempInputCpu.ptr, numInputBytes);
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}
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}
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return TEST_SUCCESS;
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}
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ErrCode DefaultPrepData_ReduceScatter(CollectiveArgs &collArgs)
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{
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CHECK_CALL(CheckAllocation(collArgs));
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if (collArgs.numInputElements != collArgs.numOutputElements * collArgs.totalRanks)
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{
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ERROR("# of input elements must be total ranks * # output elements for ReduceScatter\n");
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return TEST_FAIL;
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}
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size_t const numInputBytes = collArgs.numInputElements * DataTypeToBytes(collArgs.dataType);
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size_t const numOutputBytes = collArgs.numOutputElements * DataTypeToBytes(collArgs.dataType);
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// Clear output for all ranks (done before filling input in case of in-place)
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CHECK_CALL(collArgs.outputGpu.ClearGpuMem(numOutputBytes));
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PtrUnion tempInputCpu;
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PtrUnion tempResultCpu;
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CHECK_CALL(tempInputCpu.AllocateCpuMem(numInputBytes));
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CHECK_CALL(tempResultCpu.AllocateCpuMem(numInputBytes));
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CHECK_CALL(tempResultCpu.ClearCpuMem(numInputBytes));
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// If average or custom reduction operator is used, perform a summation instead
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ncclRedOp_t const tempOp = (collArgs.redOp >= ncclAvg ? ncclSum : collArgs.redOp);
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// Loop over each rank and generate the input / scale / reduce
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PtrUnion scalarsPerRank;
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scalarsPerRank.Attach(collArgs.scalarTransport.ptr);
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for (int rank = 0; rank < collArgs.totalRanks; ++rank)
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{
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CHECK_CALL(tempInputCpu.FillPattern(collArgs.dataType, collArgs.numInputElements, rank, false));
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if (rank == collArgs.globalRank)
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{
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if (hipMemcpy(collArgs.inputGpu.ptr, tempInputCpu.ptr, numInputBytes, hipMemcpyHostToDevice) != hipSuccess)
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{
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ERROR("hipMemcpy to input failed\n");
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CHECK_CALL(tempInputCpu.FreeCpuMem());
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CHECK_CALL(tempResultCpu.FreeCpuMem());
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return TEST_FAIL;
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}
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}
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// Scale the temporary input by local scalar for this rank
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// (Used by custom reduction ops)
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if (collArgs.scalarMode >= 0)
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{
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CHECK_CALL(tempInputCpu.Scale(collArgs.dataType, collArgs.numInputElements,
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scalarsPerRank, rank));
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}
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if (rank == 0)
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{
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memcpy(tempResultCpu.ptr, tempInputCpu.ptr, numInputBytes);
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}
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else
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{
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CHECK_CALL(tempResultCpu.Reduce(collArgs.dataType, collArgs.numInputElements,
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tempInputCpu, tempOp));
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}
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}
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// Perform averaging if necessary
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if (collArgs.redOp == ncclAvg)
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{
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CHECK_CALL(tempResultCpu.DivideByInt(collArgs.dataType, collArgs.numInputElements, collArgs.totalRanks));
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}
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// Copy over portion of result
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memcpy(collArgs.expected.I1,
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tempResultCpu.I1 + collArgs.globalRank * numOutputBytes,
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numOutputBytes);
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CHECK_CALL(tempInputCpu.FreeCpuMem());
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CHECK_CALL(tempResultCpu.FreeCpuMem());
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return TEST_SUCCESS;
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}
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ErrCode DefaultPrepData_Scatter(CollectiveArgs &collArgs)
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{
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CHECK_CALL(CheckAllocation(collArgs));
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if (collArgs.numInputElements != collArgs.numOutputElements * collArgs.totalRanks)
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{
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ERROR("# of input elements must be total ranks * # output elements for Scatter\n");
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return TEST_FAIL;
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}
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size_t const numInputBytes = collArgs.numInputElements * DataTypeToBytes(collArgs.dataType);
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size_t const numOutputBytes = collArgs.numOutputElements * DataTypeToBytes(collArgs.dataType);
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// Clear outputs on all ranks (prior to input in case of in-place)
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collArgs.outputGpu.ClearGpuMem(numOutputBytes);
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// Generate input as if on root rank - each rank will receive a portion
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PtrUnion tempInput;
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tempInput.AllocateCpuMem(numInputBytes);
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tempInput.FillPattern(collArgs.dataType, collArgs.numInputElements, collArgs.root, false);
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// Copy input to root rank
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if (collArgs.globalRank == collArgs.root)
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{
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if (hipMemcpy(collArgs.inputGpu.ptr, tempInput.ptr, numInputBytes, hipMemcpyHostToDevice) != hipSuccess)
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{
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ERROR("hipMemcpy to input failed\n");
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tempInput.FreeCpuMem();
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return TEST_FAIL;
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}
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}
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else
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{
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collArgs.inputGpu.ClearGpuMem(numInputBytes);
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}
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// Each rank receive a portion of the input
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memcpy(collArgs.expected.U1, tempInput.U1 + (collArgs.globalRank * numOutputBytes), numOutputBytes);
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tempInput.FreeCpuMem();
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return TEST_SUCCESS;
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}
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ErrCode DefaultPrepData_AllToAll(CollectiveArgs &collArgs)
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{
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CHECK_CALL(CheckAllocation(collArgs));
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if (collArgs.numInputElements != collArgs.numOutputElements)
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{
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ERROR("Number of input elements must match number of output elements for AllToAll\n");
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return TEST_FAIL;
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}
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if (collArgs.numInputElements % collArgs.totalRanks)
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{
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ERROR("Input / Output size for AllToAll must be a multiple of %d\n", collArgs.totalRanks);
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return TEST_FAIL;
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}
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size_t const numInputBytes = collArgs.numInputElements * DataTypeToBytes(collArgs.dataType);
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size_t const numOutputBytes = collArgs.numOutputElements * DataTypeToBytes(collArgs.dataType);
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size_t const numBytes = numInputBytes / collArgs.totalRanks;
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// Clear outputs on all ranks (prior to input in case of in-place)
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collArgs.outputGpu.ClearGpuMem(numOutputBytes);
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// Generate input on root rank - each rank will receive a portion
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PtrUnion tempInput;
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tempInput.Attach(collArgs.outputCpu);
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for (int rank = 0; rank < collArgs.totalRanks; ++rank)
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{
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tempInput.FillPattern(collArgs.dataType, collArgs.numInputElements, rank, false);
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// Copy input
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if (rank == collArgs.globalRank)
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{
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CHECK_HIP(hipMemcpy(collArgs.inputGpu.ptr, tempInput.ptr, numInputBytes, hipMemcpyHostToDevice));
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}
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memcpy(collArgs.expected.U1 + (numBytes * rank), tempInput.U1 + (numBytes * collArgs.globalRank), numBytes);
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}
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return TEST_SUCCESS;
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}
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}
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