8bab4f04b7
* Implement RCCL Replayer
170 行
5.7 KiB
C++
170 行
5.7 KiB
C++
#pragma once
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#include <map>
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#include <cstring>
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#include <rccl/rccl.h>
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// NOTE: Parsing is based on this line logging collective information in enqueue.cc
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// INFO(NCCL_COLL,"%s: opCount %lx sendbuff %p recvbuff %p count %zi datatype %d op %d \
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root %d comm %p [nranks=%d] stream %p task %d globalrank %d",
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// info->opName, info->comm->opCount, info->sendbuff, info->recvbuff, info->count,
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// info->datatype, info->op, info->root, info->comm, info->comm->nRanks, info->stream,
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// info->comm->tasks.nTasksP2p + info->comm->tasks.nTasksColl,
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// info->comm->localRankToRank[info->comm->localRank]);
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#define MPICHECK(cmd) do { \
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int e = cmd; \
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if( e != MPI_SUCCESS ) { \
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printf("Failed: MPI error %s:%d '%d'\n", \
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__FILE__,__LINE__, e); \
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exit(EXIT_FAILURE); \
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} \
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} while(0)
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#define HIPCALL(cmd) \
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do { \
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hipError_t error = (cmd); \
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if (error != hipSuccess) \
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{ \
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printf("Encountered HIP error (%s) at line %d in file %s\n", \
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hipGetErrorString(error), __LINE__, __FILE__); \
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exit(-1); \
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} \
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} while (0)
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#define NCCLCHECK(cmd) do { \
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ncclResult_t res = cmd; \
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if (res != ncclSuccess) { \
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printf("NCCL failure %s:%d '%s'\n", \
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__FILE__,__LINE__,ncclGetErrorString(res)); \
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} \
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} while(0)
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struct LineItem
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{
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char hostname[MPI_MAX_PROCESSOR_NAME];
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int pid;
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int tid;
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int cudaDev;
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char opName[32];
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int opCount;
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char sendbuff[32];
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char recvbuff[32];
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size_t count;
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int datatype;
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int op;
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int root;
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char comm[32];
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int nRanks;
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void* stream;
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int task;
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int globalRank;
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};
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// Enumeration of all collective functions currently supported
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typedef enum
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{
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ncclCollBroadcast = 0,
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ncclCollReduce,
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ncclCollAllGather,
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ncclCollReduceScatter,
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ncclCollAllReduce,
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ncclCollGather,
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ncclCollScatter,
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ncclCollAllToAll,
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ncclCollAllToAllv,
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ncclCollSend,
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ncclCollRecv,
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ncclNumFuncs
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} ncclFunc_t;
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char const ncclFuncNames[ncclNumFuncs][32] =
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{
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"Broadcast",
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"Reduce",
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"AllGather",
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"ReduceScatter",
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"AllReduce",
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"Gather",
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"Scatter",
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"AllToAll",
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"AllToAllv",
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"Send",
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"Recv"
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};
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struct TaskInfo
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{
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ncclFunc_t funcType;
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bool inPlace;
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size_t count;
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ncclDataType_t datatype;
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ncclRedOp_t op;
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int root;
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};
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struct RankData
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{
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int lineNum;
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std::string comm;
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std::vector<TaskInfo> tasks;
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};
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struct GroupCall
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{
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bool isValid;
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int opCount;
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std::map<int, RankData> rankData; // Indexed by globalRank
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};
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size_t DataTypeToBytes(ncclDataType_t const dataType)
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{
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switch (dataType) {
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case ncclInt8: return 1;
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case ncclUint8: return 1;
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case ncclInt32: return 4;
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case ncclUint32: return 4;
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case ncclInt64: return 8;
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case ncclUint64: return 8;
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case ncclFloat16: return 2;
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case ncclFloat32: return 4;
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case ncclFloat64: return 8;
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case ncclBfloat16: return 2;
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default:
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printf("Unsupported datatype (%d)\n", dataType);
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exit(0);
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}
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}
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ncclFunc_t GetFuncType(char* func)
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{
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for (int i = 0; i < ncclNumFuncs; i++)
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if (!strcmp(func, ncclFuncNames[i])) return (ncclFunc_t)i;
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printf("[ERROR] Unrecognzied func %s\n", func);
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exit(1);
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}
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// parse the logs and assign them into lineItem
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bool ParseLineItem(char const* line, LineItem& li);
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// this covers grouping the logs based on opCount and task number,
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// validatation of the groupCalls for both non-send/recv collectives and send/recv
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void ParseCollectives(char const* logFilename,
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int const numGlobalRanks,
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std::vector<GroupCall>& groupCalls);
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// size differ for each collective call and getSize gives a specific size in bytes depending on type of task,
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// global rank, element count and data type
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std::pair<size_t, size_t> GetSize(TaskInfo taskInfo,
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int numGlobalRanks);
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// executes the collective call (task)
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void ExecuteCollective(TaskInfo task, ncclComm_t comm, hipStream_t stream, const void *sendbuff, void *recvbuff);
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// allocates send/recv buff, sets the device based on which rank the task belongs to,
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// syncronize devices after executing all the tasks and free device memory.
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void ReplayRccl(GroupCall& groupCall, std::vector<ncclComm_t> comms, std::vector<hipStream_t> streams,
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int const localGpuOffset,
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int const numGpusPerMpiRank,
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int const firstGlobalRank,
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int const numGlobalRanks); |