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common.cu
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/*************************************************************************
* Copyright (c) 2016-2022, NVIDIA CORPORATION. All rights reserved.
*
* See LICENSE.txt for license information
************************************************************************/
#include "common.h"
#include <pthread.h>
#include <cstdio>
#include <type_traits>
#include <getopt.h>
#include <libgen.h>
#include "cuda.h"
#include "../verifiable/verifiable.h"
int test_ncclVersion = 0; // init'd with ncclGetVersion()
#if NCCL_MAJOR >= 2
ncclDataType_t test_types[ncclNumTypes] = {
ncclInt8, ncclUint8, ncclInt32, ncclUint32, ncclInt64, ncclUint64, ncclHalf, ncclFloat, ncclDouble
#if defined(__CUDA_BF16_TYPES_EXIST__) && NCCL_VERSION_CODE >= NCCL_VERSION(2,10,0)
, ncclBfloat16
#endif
};
const char *test_typenames[ncclNumTypes] = {
"int8", "uint8", "int32", "uint32", "int64", "uint64", "half", "float", "double"
#if defined(__CUDA_BF16_TYPES_EXIST__) && NCCL_VERSION_CODE >= NCCL_VERSION(2,10,0)
, "bfloat16"
#endif
};
int test_typenum = -1;
const char *test_opnames[] = {"sum", "prod", "max", "min", "avg", "mulsum"};
ncclRedOp_t test_ops[] = {ncclSum, ncclProd, ncclMax, ncclMin
#if NCCL_VERSION_CODE >= NCCL_VERSION(2,10,0)
, ncclAvg
#endif
#if NCCL_VERSION_CODE >= NCCL_VERSION(2,11,0)
, ncclNumOps // stand in for ncclRedOpCreatePreMulSum() created on-demand
#endif
};
int test_opnum = -1;
#else
ncclDataType_t test_types[ncclNumTypes] = {ncclChar, ncclInt, ncclHalf, ncclFloat, ncclDouble, ncclInt64, ncclUint64};
const char *test_typenames[ncclNumTypes] = {"char", "int", "half", "float", "double", "int64", "uint64"};
int test_typenum = 7;
const char *test_opnames[] = {"sum", "prod", "max", "min"};
ncclRedOp_t test_ops[] = {ncclSum, ncclProd, ncclMax, ncclMin};
int test_opnum = 4;
#endif
// For libnccl's < 2.13
extern "C" __attribute__((weak)) char const* ncclGetLastError(ncclComm_t comm) {
return "";
}
int is_main_proc = 0;
thread_local int is_main_thread = 0;
// Command line parameter defaults
static int nThreads = 1;
static int nGpus = 1;
static size_t minBytes = 32*1024*1024;
static size_t maxBytes = 32*1024*1024;
static size_t stepBytes = 1*1024*1024;
static size_t stepFactor = 1;
static int datacheck = 1;
static int warmup_iters = 5;
static int iters = 20;
static int agg_iters = 1;
static int run_cycles = 1;
static int ncclop = ncclSum;
static int nccltype = ncclFloat;
static int ncclroot = 0;
static int parallel_init = 0;
static int blocking_coll = 0;
static int streamnull = 0;
static int timeout = 0;
static int cudaGraphLaunches = 0;
static int report_cputime = 0;
// Report average iteration time: (0=RANK0,1=AVG,2=MIN,3=MAX)
static int average = 1;
#if NCCL_VERSION_CODE >= NCCL_VERSION(2,19,0)
static int local_register = 0;
#endif
#define NUM_BLOCKS 32
static double parsesize(const char *value) {
long long int units;
double size;
char size_lit;
int count = sscanf(value, "%lf %1s", &size, &size_lit);
switch (count) {
case 2:
switch (size_lit) {
case 'G':
case 'g':
units = 1024*1024*1024;
break;
case 'M':
case 'm':
units = 1024*1024;
break;
case 'K':
case 'k':
units = 1024;
break;
default:
return -1.0;
};
break;
case 1:
units = 1;
break;
default:
return -1.0;
}
return size * units;
}
testResult_t CheckDelta(void* results, void* expected, size_t count, size_t offset, ncclDataType_t type, ncclRedOp_t op, uint64_t seed, int nranks, int64_t *wrongEltN) {
ncclVerifiableVerify(results, expected, count, (int)type, (int)op, nranks, seed, offset, wrongEltN, cudaStreamDefault);
CUDACHECK(cudaDeviceSynchronize());
return testSuccess;
}
testResult_t InitDataReduce(void* data, const size_t count, const size_t offset, ncclDataType_t type, ncclRedOp_t op, uint64_t seed, int nranks) {
ncclVerifiablePrepareExpected(data, count, (int)type, (int)op, nranks, seed, offset, cudaStreamDefault);
return testSuccess;
}
testResult_t InitData(void* data, const size_t count, size_t offset, ncclDataType_t type, ncclRedOp_t op, uint64_t seed, int nranks, int rank) {
ncclVerifiablePrepareInput(data, count, (int)type, (int)op, nranks, rank, seed, offset, cudaStreamDefault);
return testSuccess;
}
void Barrier(struct threadArgs *args) {
thread_local int epoch = 0;
static pthread_mutex_t lock[2] = {PTHREAD_MUTEX_INITIALIZER, PTHREAD_MUTEX_INITIALIZER};
static pthread_cond_t cond[2] = {PTHREAD_COND_INITIALIZER, PTHREAD_COND_INITIALIZER};
static int counter[2] = {0, 0};
pthread_mutex_lock(&lock[epoch]);
if(++counter[epoch] == args->nThreads)
pthread_cond_broadcast(&cond[epoch]);
if(args->thread+1 == args->nThreads) {
while(counter[epoch] != args->nThreads)
pthread_cond_wait(&cond[epoch], &lock[epoch]);
#ifdef MPI_SUPPORT
MPI_Barrier(MPI_COMM_WORLD);
#endif
counter[epoch] = 0;
pthread_cond_broadcast(&cond[epoch]);
}
else {
while(counter[epoch] != 0)
pthread_cond_wait(&cond[epoch], &lock[epoch]);
}
pthread_mutex_unlock(&lock[epoch]);
epoch ^= 1;
}
// Inter-thread/process barrier+allreduce. The quality of the return value
// for average=0 (which means broadcast from rank=0) is dubious. The returned
// value will actually be the result of process-local broadcast from the local thread=0.
template<typename T>
void Allreduce(struct threadArgs* args, T* value, int average) {
thread_local int epoch = 0;
static pthread_mutex_t lock[2] = {PTHREAD_MUTEX_INITIALIZER, PTHREAD_MUTEX_INITIALIZER};
static pthread_cond_t cond[2] = {PTHREAD_COND_INITIALIZER, PTHREAD_COND_INITIALIZER};
static T accumulator[2];
static int counter[2] = {0, 0};
pthread_mutex_lock(&lock[epoch]);
if(counter[epoch] == 0) {
if(average != 0 || args->thread == 0) accumulator[epoch] = *value;
} else {
switch(average) {
case /*r0*/ 0: if(args->thread == 0) accumulator[epoch] = *value; break;
case /*avg*/1: accumulator[epoch] += *value; break;
case /*min*/2: accumulator[epoch] = std::min<T>(accumulator[epoch], *value); break;
case /*max*/3: accumulator[epoch] = std::max<T>(accumulator[epoch], *value); break;
case /*sum*/4: accumulator[epoch] += *value; break;
}
}
if(++counter[epoch] == args->nThreads)
pthread_cond_broadcast(&cond[epoch]);
if(args->thread+1 == args->nThreads) {
while(counter[epoch] != args->nThreads)
pthread_cond_wait(&cond[epoch], &lock[epoch]);
#ifdef MPI_SUPPORT
if(average != 0) {
static_assert(std::is_same<T, long long>::value || std::is_same<T, double>::value, "Allreduce<T> only for T in {long long, double}");
MPI_Datatype ty = std::is_same<T, long long>::value ? MPI_LONG_LONG :
std::is_same<T, double>::value ? MPI_DOUBLE :
MPI_Datatype();
MPI_Op op = average == 1 ? MPI_SUM :
average == 2 ? MPI_MIN :
average == 3 ? MPI_MAX :
average == 4 ? MPI_SUM : MPI_Op();
MPI_Allreduce(MPI_IN_PLACE, (void*)&accumulator[epoch], 1, ty, op, MPI_COMM_WORLD);
}
#endif
if(average == 1) accumulator[epoch] /= args->totalProcs*args->nThreads;
counter[epoch] = 0;
pthread_cond_broadcast(&cond[epoch]);
}
else {
while(counter[epoch] != 0)
pthread_cond_wait(&cond[epoch], &lock[epoch]);
}
pthread_mutex_unlock(&lock[epoch]);
*value = accumulator[epoch];
epoch ^= 1;
}
testResult_t CheckData(struct threadArgs* args, ncclDataType_t type, ncclRedOp_t op, int root, int in_place, int64_t *wrongElts) {
int nranks = args->nProcs*args->nGpus*args->nThreads;
size_t count = args->expectedBytes/wordSize(type);
int64_t *wrongPerGpu = nullptr;
CUDACHECK(cudaHostAlloc((void**)&wrongPerGpu, args->nGpus*sizeof(int64_t), cudaHostAllocMapped));
for (int i=0; i<args->nGpus; i++) {
int rank = ((args->proc*args->nThreads + args->thread)*args->nGpus + i);
CUDACHECK(cudaSetDevice(args->gpus[i]));
void *data = in_place ? ((void *)((uintptr_t)args->recvbuffs[i] + args->recvInplaceOffset*rank)) : args->recvbuffs[i];
TESTCHECK(CheckDelta(data, args->expected[i], count, 0, type, op, 0, nranks, wrongPerGpu+i));
#if 1 && DEBUG_PRINT
if (args->reportErrors && wrongPerGpu[i] != 0) {
printf("rank=%d #wrong=%d\n", rank, (int)wrongPerGpu[i]);
char *expectedHost = (char*)malloc(args->expectedBytes);
char *dataHost = (char*)malloc(args->expectedBytes);
int eltsz = wordSize(type);
cudaMemcpy(expectedHost, args->expected[i], args->expectedBytes, cudaMemcpyDeviceToHost);
cudaMemcpy(dataHost, data, args->expectedBytes, cudaMemcpyDeviceToHost);
for(int j=0; j<args->expectedBytes/eltsz; j++) {
unsigned long long want, got;
want = 0;
memcpy(&want, expectedHost + j*eltsz, eltsz);
got = 0;
memcpy(&got, dataHost + j*eltsz, eltsz);
if(want != got) {
printf(" rank=%d elt[%d]: want=0x%llx got=0x%llx\n", rank, j, want, got);
}
}
free(expectedHost);
free(dataHost);
}
#endif
}
*wrongElts = 0;
for (int i=0; i < args->nGpus; i++) *wrongElts += wrongPerGpu[i];
cudaFreeHost(wrongPerGpu);
if (args->reportErrors && *wrongElts) args->errors[0]++;
return testSuccess;
}
testResult_t testStreamSynchronize(int ngpus, cudaStream_t* streams, ncclComm_t* comms) {
cudaError_t cudaErr;
int remaining = ngpus;
int* done = (int*)malloc(sizeof(int)*ngpus);
memset(done, 0, sizeof(int)*ngpus);
timer tim;
while (remaining) {
int idle = 1;
for (int i=0; i<ngpus; i++) {
if (done[i]) continue;
cudaErr = cudaStreamQuery(streams[i]);
if (cudaErr == cudaSuccess) {
done[i] = 1;
remaining--;
idle = 0;
continue;
}
if (cudaErr != cudaErrorNotReady) CUDACHECK(cudaErr);
#if NCCL_VERSION_CODE >= NCCL_VERSION(2,4,0)
if (test_ncclVersion >= NCCL_VERSION(2,4,0) && comms) {
ncclResult_t ncclAsyncErr;
NCCLCHECK(ncclCommGetAsyncError(comms[i], &ncclAsyncErr));
if (ncclAsyncErr != ncclSuccess) {
// An asynchronous error happened. Stop the operation and destroy
// the communicator
for (int i=0; i<ngpus; i++)
NCCLCHECK(ncclCommAbort(comms[i]));
// Abort the perf test
NCCLCHECK(ncclAsyncErr);
}
}
double delta = tim.elapsed();
if (delta > timeout && timeout > 0) {
for (int i=0; i<ngpus; i++)
NCCLCHECK(ncclCommAbort(comms[i]));
char hostname[1024];
getHostName(hostname, 1024);
printf("%s: Test timeout (%ds) %s:%d\n",
hostname,
timeout,
__FILE__,__LINE__);
free(done);
return testTimeout;
}
#endif
}
// We might want to let other threads (including NCCL threads) use the CPU.
if (idle) sched_yield();
}
free(done);
return testSuccess;
}
testResult_t startColl(struct threadArgs* args, ncclDataType_t type, ncclRedOp_t opIndex, int root, int in_place, int iter) {
size_t count = args->nbytes / wordSize(type);
// Try to change offset for each iteration so that we avoid cache effects and catch race conditions in ptrExchange
size_t totalnbytes = max(args->sendBytes, args->expectedBytes);
size_t steps = totalnbytes ? args->maxbytes / totalnbytes : 1;
size_t shift = totalnbytes * (iter % steps);
if (args->nGpus > 1) NCCLCHECK(ncclGroupStart());
for (int i = 0; i < args->nGpus; i++) {
#ifndef NCCL_MAJOR
CUDACHECK(cudaSetDevice(args->gpus[i]));
#endif
int rank = ((args->proc*args->nThreads + args->thread)*args->nGpus + i);
char* recvBuff = ((char*)args->recvbuffs[i]) + shift;
char* sendBuff = ((char*)args->sendbuffs[i]) + shift;
ncclRedOp_t op;
if(opIndex < ncclNumOps) {
op = opIndex;
}
#if NCCL_VERSION_CODE >= NCCL_VERSION(2,11,0)
else {
union {
int8_t i8; uint8_t u8; int32_t i32; uint32_t u32; int64_t i64; uint64_t u64;
half f16; float f32; double f64;
#if defined(__CUDA_BF16_TYPES_EXIST__)
__nv_bfloat16 bf16;
#endif
};
switch(type) {
case ncclInt8: i8 = ncclVerifiablePremulScalar<int8_t>(rank); break;
case ncclUint8: u8 = ncclVerifiablePremulScalar<uint8_t>(rank); break;
case ncclInt32: i32 = ncclVerifiablePremulScalar<int32_t>(rank); break;
case ncclUint32: u32 = ncclVerifiablePremulScalar<uint32_t>(rank); break;
case ncclInt64: i64 = ncclVerifiablePremulScalar<int64_t>(rank); break;
case ncclUint64: u64 = ncclVerifiablePremulScalar<uint64_t>(rank); break;
case ncclFloat16: f16 = ncclVerifiablePremulScalar<half>(rank); break;
case ncclFloat32: f32 = ncclVerifiablePremulScalar<float>(rank); break;
case ncclFloat64: f64 = ncclVerifiablePremulScalar<double>(rank); break;
#if defined(__CUDA_BF16_TYPES_EXIST__)
case ncclBfloat16: bf16 = ncclVerifiablePremulScalar<__nv_bfloat16>(rank); break;
#endif
}
NCCLCHECK(ncclRedOpCreatePreMulSum(&op, &u64, type, ncclScalarHostImmediate, args->comms[i]));
}
#endif
TESTCHECK(args->collTest->runColl(
(void*)(in_place ? recvBuff + args->sendInplaceOffset*rank : sendBuff),
(void*)(in_place ? recvBuff + args->recvInplaceOffset*rank : recvBuff),
count, type, op, root, args->comms[i], args->streams[i]));
#if NCCL_VERSION_CODE >= NCCL_VERSION(2,11,0)
if(opIndex >= ncclNumOps) {
NCCLCHECK(ncclRedOpDestroy(op, args->comms[i]));
}
#endif
}
if (args->nGpus > 1) NCCLCHECK(ncclGroupEnd());
if (blocking_coll) {
// Complete op before returning
TESTCHECK(testStreamSynchronize(args->nGpus, args->streams, args->comms));
}
if (blocking_coll) Barrier(args);
return testSuccess;
}
testResult_t completeColl(struct threadArgs* args) {
if (blocking_coll) return testSuccess;
TESTCHECK(testStreamSynchronize(args->nGpus, args->streams, args->comms));
return testSuccess;
}
testResult_t BenchTime(struct threadArgs* args, ncclDataType_t type, ncclRedOp_t op, int root, int in_place) {
size_t count = args->nbytes / wordSize(type);
if (datacheck) {
// Initialize sendbuffs, recvbuffs and expected
TESTCHECK(args->collTest->initData(args, type, op, root, 99, in_place));
}
// Sync
TESTCHECK(startColl(args, type, op, root, in_place, 0));
TESTCHECK(completeColl(args));
Barrier(args);
#if CUDART_VERSION >= 11030
cudaGraph_t graphs[args->nGpus];
cudaGraphExec_t graphExec[args->nGpus];
if (cudaGraphLaunches >= 1) {
// Begin cuda graph capture
for (int i=0; i<args->nGpus; i++) {
// Thread local mdoe is needed for:
// - Multi-thread mode: where graph capture and instantiation can happen concurrently across threads
// - P2P pre-connect: when there is no warm-up, P2P pre-connect is done during graph capture.
// Since pre-connect calls cudaMalloc, we cannot use global capture mode
CUDACHECK(cudaStreamBeginCapture(args->streams[i], cudaStreamCaptureModeThreadLocal));
}
}
#endif
// Performance Benchmark
timer tim;
for (int iter = 0; iter < iters; iter++) {
if (agg_iters>1) NCCLCHECK(ncclGroupStart());
for (int aiter = 0; aiter < agg_iters; aiter++) {
TESTCHECK(startColl(args, type, op, root, in_place, iter*agg_iters+aiter));
}
if (agg_iters>1) NCCLCHECK(ncclGroupEnd());
}
#if CUDART_VERSION >= 11030
if (cudaGraphLaunches >= 1) {
// End cuda graph capture
for (int i=0; i<args->nGpus; i++) {
CUDACHECK(cudaStreamEndCapture(args->streams[i], graphs+i));
}
// Instantiate cuda graph
for (int i=0; i<args->nGpus; i++) {
CUDACHECK(cudaGraphInstantiate(graphExec+i, graphs[i], NULL, NULL, 0));
}
// Resync CPU, restart timing, launch cuda graph
Barrier(args);
tim.reset();
for (int l=0; l<cudaGraphLaunches; l++) {
for (int i=0; i<args->nGpus; i++) {
CUDACHECK(cudaGraphLaunch(graphExec[i], args->streams[i]));
}
}
}
#endif
double cputimeSec = tim.elapsed()/(iters*agg_iters);
TESTCHECK(completeColl(args));
double deltaSec = tim.elapsed();
deltaSec = deltaSec/(iters*agg_iters);
if (cudaGraphLaunches >= 1) deltaSec = deltaSec/cudaGraphLaunches;
Allreduce(args, &deltaSec, average);
#if CUDART_VERSION >= 11030
if (cudaGraphLaunches >= 1) {
//destroy cuda graph
for (int i=0; i<args->nGpus; i++) {
CUDACHECK(cudaGraphExecDestroy(graphExec[i]));
CUDACHECK(cudaGraphDestroy(graphs[i]));
}
}
#endif
double algBw, busBw;
args->collTest->getBw(count, wordSize(type), deltaSec, &algBw, &busBw, args->nProcs*args->nThreads*args->nGpus);
Barrier(args);
int64_t wrongElts = 0;
static __thread int rep = 0;
rep++;
for (int c = 0; c < datacheck; c++) {
// Initialize sendbuffs, recvbuffs and expected
TESTCHECK(args->collTest->initData(args, type, op, root, rep, in_place));
#if CUDART_VERSION >= 11030
if (cudaGraphLaunches >= 1) {
// Begin cuda graph capture for data check
for (int i=0; i<args->nGpus; i++) {
CUDACHECK(cudaStreamBeginCapture(args->streams[i], args->nThreads > 1 ? cudaStreamCaptureModeThreadLocal : cudaStreamCaptureModeGlobal));
}
}
#endif
//test validation in single itertion, should ideally be included into the multi-iteration run
TESTCHECK(startColl(args, type, op, root, in_place, 0));
#if CUDART_VERSION >= 11030
if (cudaGraphLaunches >= 1) {
// End cuda graph capture
for (int i=0; i<args->nGpus; i++) {
CUDACHECK(cudaStreamEndCapture(args->streams[i], graphs+i));
}
// Instantiate cuda graph
for (int i=0; i<args->nGpus; i++) {
CUDACHECK(cudaGraphInstantiate(graphExec+i, graphs[i], NULL, NULL, 0));
}
// Launch cuda graph
for (int i=0; i<args->nGpus; i++) {
CUDACHECK(cudaGraphLaunch(graphExec[i], args->streams[i]));
}
}
#endif
TESTCHECK(completeColl(args));
#if CUDART_VERSION >= 11030
if (cudaGraphLaunches >= 1) {
//destroy cuda graph
for (int i=0; i<args->nGpus; i++) {
CUDACHECK(cudaGraphExecDestroy(graphExec[i]));
CUDACHECK(cudaGraphDestroy(graphs[i]));
}
}
#endif
TESTCHECK(CheckData(args, type, op, root, in_place, &wrongElts));
//aggregate delta from all threads and procs
long long wrongElts1 = wrongElts;
//if (wrongElts) fprintf(stderr, "\nERROR: Data corruption : rank %d size %ld wrongElts %ld\n", args->proc, args->expectedBytes, wrongElts);
Allreduce(args, &wrongElts1, /*sum*/4);
wrongElts = wrongElts1;
if (wrongElts) break;
}
double timeUsec = (report_cputime ? cputimeSec : deltaSec)*1.0E6;
char timeStr[100];
if (timeUsec >= 10000.0) {
sprintf(timeStr, "%7.0f", timeUsec);
} else if (timeUsec >= 100.0) {
sprintf(timeStr, "%7.1f", timeUsec);
} else {
sprintf(timeStr, "%7.2f", timeUsec);
}
if (args->reportErrors) {
PRINT(" %7s %6.2f %6.2f %5g", timeStr, algBw, busBw, (double)wrongElts);
} else {
PRINT(" %7s %6.2f %6.2f %5s", timeStr, algBw, busBw, "N/A");
}
args->bw[0] += busBw;
args->bw_count[0]++;
return testSuccess;
}
void setupArgs(size_t size, ncclDataType_t type, struct threadArgs* args) {
int nranks = args->nProcs*args->nGpus*args->nThreads;
size_t count, sendCount, recvCount, paramCount, sendInplaceOffset, recvInplaceOffset;
count = size / wordSize(type);
args->collTest->getCollByteCount(&sendCount, &recvCount, ¶mCount, &sendInplaceOffset, &recvInplaceOffset, (size_t)count, (size_t)nranks);
args->nbytes = paramCount * wordSize(type);
args->sendBytes = sendCount * wordSize(type);
args->expectedBytes = recvCount * wordSize(type);
args->sendInplaceOffset = sendInplaceOffset * wordSize(type);
args->recvInplaceOffset = recvInplaceOffset * wordSize(type);
}
testResult_t TimeTest(struct threadArgs* args, ncclDataType_t type, const char* typeName, ncclRedOp_t op, const char* opName, int root) {
// Sync to avoid first-call timeout
Barrier(args);
// Warm-up for large size
setupArgs(args->maxbytes, type, args);
for (int iter = 0; iter < warmup_iters; iter++) {
TESTCHECK(startColl(args, type, op, root, 0, iter));
}
TESTCHECK(completeColl(args));
// Warm-up for small size
setupArgs(args->minbytes, type, args);
for (int iter = 0; iter < warmup_iters; iter++) {
TESTCHECK(startColl(args, type, op, root, 0, iter));
}
TESTCHECK(completeColl(args));
// Benchmark
long repeat = run_cycles;
do {
for (size_t size = args->minbytes; size<=args->maxbytes; size = ((args->stepfactor > 1) ? size*args->stepfactor : size+args->stepbytes)) {
setupArgs(size, type, args);
char rootName[100];
sprintf(rootName, "%6i", root);
PRINT("%12li %12li %8s %6s %6s", max(args->sendBytes, args->expectedBytes), args->nbytes / wordSize(type), typeName, opName, rootName);
TESTCHECK(BenchTime(args, type, op, root, 0));
TESTCHECK(BenchTime(args, type, op, root, 1));
PRINT("\n");
}
} while (--repeat);
return testSuccess;
}
testResult_t threadRunTests(struct threadArgs* args) {
// Set device to the first of our GPUs. If we don't do that, some operations
// will be done on the current GPU (by default : 0) and if the GPUs are in
// exclusive mode those operations will fail.
CUDACHECK(cudaSetDevice(args->gpus[0]));
TESTCHECK(ncclTestEngine.runTest(args, ncclroot, (ncclDataType_t)nccltype, test_typenames[nccltype], (ncclRedOp_t)ncclop, test_opnames[ncclop]));
return testSuccess;
}
testResult_t threadInit(struct threadArgs* args) {
char hostname[1024];
getHostName(hostname, 1024);
int nranks = args->nProcs*args->nThreads*args->nGpus;
//set main thread again
is_main_thread = (is_main_proc && args->thread == 0) ? 1 : 0;
NCCLCHECK(ncclGroupStart());
for (int i=0; i<args->nGpus; i++) {
int rank = args->proc*args->nThreads*args->nGpus + args->thread*args->nGpus + i;
CUDACHECK(cudaSetDevice(args->gpus[i]));
NCCLCHECK(ncclCommInitRank(args->comms+i, nranks, args->ncclId, rank));
}
NCCLCHECK(ncclGroupEnd());
#if NCCL_VERSION_CODE >= NCCL_VERSION(2,19,0)
void **sendRegHandles = (local_register) ? (void **)malloc(sizeof(*sendRegHandles)*args->nGpus) : NULL;
void **recvRegHandles = (local_register) ? (void **)malloc(sizeof(*recvRegHandles)*args->nGpus) : NULL;
for (int i=0; i<args->nGpus; i++) {
if (local_register) NCCLCHECK(ncclCommRegister(args->comms[i], args->sendbuffs[i], args->maxbytes, &sendRegHandles[i]));
if (local_register) NCCLCHECK(ncclCommRegister(args->comms[i], args->recvbuffs[i], args->maxbytes, &recvRegHandles[i]));
}
#endif
TESTCHECK(threadRunTests(args));
for (int i=0; i<args->nGpus; i++) {
#if NCCL_VERSION_CODE >= NCCL_VERSION(2,19,0)
if (local_register) NCCLCHECK(ncclCommDeregister(args->comms[i], sendRegHandles[i]));
if (local_register) NCCLCHECK(ncclCommDeregister(args->comms[i], recvRegHandles[i]));
#endif
NCCLCHECK(ncclCommDestroy(args->comms[i]));
}
return testSuccess;
}
void* threadLauncher(void* thread_) {
struct testThread* thread = (struct testThread*)thread_;
thread->ret = thread->func(&thread->args);
return NULL;
}
testResult_t threadLaunch(struct testThread* thread) {
pthread_create(&thread->thread, NULL, threadLauncher, thread);
return testSuccess;
}
testResult_t AllocateBuffs(void **sendbuff, size_t sendBytes, void **recvbuff, size_t recvBytes, void **expected, size_t nbytes) {
#if NCCL_VERSION_CODE >= NCCL_VERSION(2,19,0)
NCCLCHECK(ncclMemAlloc(sendbuff, nbytes));
NCCLCHECK(ncclMemAlloc(recvbuff, nbytes));
if (datacheck) NCCLCHECK(ncclMemAlloc(expected, recvBytes));
#else
CUDACHECK(cudaMalloc(sendbuff, nbytes));
CUDACHECK(cudaMalloc(recvbuff, nbytes));
if (datacheck) CUDACHECK(cudaMalloc(expected, recvBytes));
#endif
return testSuccess;
}
testResult_t run(); // Main function
int main(int argc, char* argv[]) {
// Make sure everyline is flushed so that we see the progress of the test
setlinebuf(stdout);
#if NCCL_VERSION_CODE >= NCCL_VERSION(2,4,0)
ncclGetVersion(&test_ncclVersion);
#else
test_ncclVersion = NCCL_VERSION_CODE;
#endif
//printf("# NCCL_VERSION_CODE=%d ncclGetVersion=%d\n", NCCL_VERSION_CODE, test_ncclVersion);
#if NCCL_VERSION_CODE >= NCCL_VERSION(2,0,0)
test_opnum = 4;
test_typenum = 9;
if (NCCL_VERSION_CODE >= NCCL_VERSION(2,10,0) && test_ncclVersion >= NCCL_VERSION(2,10,0)) {
test_opnum++; // ncclAvg
#if defined(__CUDA_BF16_TYPES_EXIST__)
test_typenum++; // bfloat16
#endif
}
if (NCCL_VERSION_CODE >= NCCL_VERSION(2,11,0) && test_ncclVersion >= NCCL_VERSION(2,11,0)) {
test_opnum++; // PreMulSum
}
#endif
// Parse args
double parsed;
int longindex;
static struct option longopts[] = {
{"nthreads", required_argument, 0, 't'},
{"ngpus", required_argument, 0, 'g'},
{"minbytes", required_argument, 0, 'b'},
{"maxbytes", required_argument, 0, 'e'},
{"stepbytes", required_argument, 0, 'i'},
{"stepfactor", required_argument, 0, 'f'},
{"iters", required_argument, 0, 'n'},
{"agg_iters", required_argument, 0, 'm'},
{"warmup_iters", required_argument, 0, 'w'},
{"run_cycles", required_argument, 0, 'N'},
{"parallel_init", required_argument, 0, 'p'},
{"check", required_argument, 0, 'c'},
{"op", required_argument, 0, 'o'},
{"datatype", required_argument, 0, 'd'},
{"root", required_argument, 0, 'r'},
{"blocking", required_argument, 0, 'z'},
{"stream_null", required_argument, 0, 'y'},
{"timeout", required_argument, 0, 'T'},
{"cudagraph", required_argument, 0, 'G'},
{"report_cputime", required_argument, 0, 'C'},
{"average", required_argument, 0, 'a'},
{"local_register", required_argument, 0, 'R'},
{"help", no_argument, 0, 'h'},
{}
};
while(1) {
int c;
c = getopt_long(argc, argv, "t:g:b:e:i:f:n:m:w:N:p:c:o:d:r:z:y:T:hG:C:a:R:", longopts, &longindex);
if (c == -1)
break;
switch(c) {
case 't':
nThreads = strtol(optarg, NULL, 0);
break;
case 'g':
nGpus = strtol(optarg, NULL, 0);
break;
case 'b':
parsed = parsesize(optarg);
if (parsed < 0) {
fprintf(stderr, "invalid size specified for 'minbytes'\n");
return -1;
}
minBytes = (size_t)parsed;
break;
case 'e':
parsed = parsesize(optarg);
if (parsed < 0) {
fprintf(stderr, "invalid size specified for 'maxbytes'\n");
return -1;
}
maxBytes = (size_t)parsed;
break;
case 'i':
parsed = parsesize(optarg);
if (parsed < 0) {
fprintf(stderr, "invalid size specified for 'stepBytes'\n");
return -1;
}
stepBytes = (size_t)parsed;
break;
case 'f':
stepFactor = strtol(optarg, NULL, 0);
break;
case 'n':
iters = (int)strtol(optarg, NULL, 0);
break;
case 'm':
#if NCCL_MAJOR > 2 || (NCCL_MAJOR >= 2 && NCCL_MINOR >= 2)
agg_iters = (int)strtol(optarg, NULL, 0);
#else
fprintf(stderr, "Option -m not supported before NCCL 2.2. Ignoring\n");
#endif
break;
case 'w':
warmup_iters = (int)strtol(optarg, NULL, 0);
break;
case 'N':
run_cycles = (int)strtol(optarg, NULL, 0);
break;
case 'c':
datacheck = (int)strtol(optarg, NULL, 0);
break;
case 'p':
parallel_init = (int)strtol(optarg, NULL, 0);
break;
case 'o':
ncclop = ncclstringtoop(optarg);
break;
case 'd':
nccltype = ncclstringtotype(optarg);
break;
case 'r':
ncclroot = strtol(optarg, NULL, 0);
break;
case 'z':
blocking_coll = strtol(optarg, NULL, 0);
break;
case 'y':
streamnull = strtol(optarg, NULL, 0);
break;
case 'T':
timeout = strtol(optarg, NULL, 0);
break;
case 'G':
#if (NCCL_MAJOR > 2 || (NCCL_MAJOR >= 2 && NCCL_MINOR >= 9)) && CUDART_VERSION >= 11030
cudaGraphLaunches = strtol(optarg, NULL, 0);
#else
printf("Option -G (CUDA graph) not supported before NCCL 2.9 + CUDA 11.3. Ignoring\n");
#endif
break;
case 'C':
report_cputime = strtol(optarg, NULL, 0);
break;
case 'a':
average = (int)strtol(optarg, NULL, 0);
break;
case 'R':
#if NCCL_VERSION_CODE >= NCCL_VERSION(2,19,0)
if ((int)strtol(optarg, NULL, 0)) {
local_register = 1;
}
#else
printf("Option -R (register) is not supported before NCCL 2.19. Ignoring\n");
#endif
break;
case 'h':
default:
if (c != 'h') printf("invalid option '%c'\n", c);
printf("USAGE: %s \n\t"
"[-t,--nthreads <num threads>] \n\t"
"[-g,--ngpus <gpus per thread>] \n\t"
"[-b,--minbytes <min size in bytes>] \n\t"
"[-e,--maxbytes <max size in bytes>] \n\t"
"[-i,--stepbytes <increment size>] \n\t"
"[-f,--stepfactor <increment factor>] \n\t"
"[-n,--iters <iteration count>] \n\t"
"[-m,--agg_iters <aggregated iteration count>] \n\t"
"[-w,--warmup_iters <warmup iteration count>] \n\t"
"[-N,--run_cycles <cycle count> run & print each cycle (default: 1; 0=infinite)] \n\t"
"[-p,--parallel_init <0/1>] \n\t"
"[-c,--check <check iteration count>] \n\t"
#if NCCL_VERSION_CODE >= NCCL_VERSION(2,11,0)
"[-o,--op <sum/prod/min/max/avg/mulsum/all>] \n\t"
#elif NCCL_VERSION_CODE >= NCCL_VERSION(2,10,0)
"[-o,--op <sum/prod/min/max/avg/all>] \n\t"
#else
"[-o,--op <sum/prod/min/max/all>] \n\t"
#endif
"[-d,--datatype <nccltype/all>] \n\t"
"[-r,--root <root>] \n\t"
"[-z,--blocking <0/1>] \n\t"
"[-y,--stream_null <0/1>] \n\t"
"[-T,--timeout <time in seconds>] \n\t"
"[-G,--cudagraph <num graph launches>] \n\t"
"[-C,--report_cputime <0/1>] \n\t"
"[-a,--average <0/1/2/3> report average iteration time <0=RANK0/1=AVG/2=MIN/3=MAX>] \n\t"
"[-R,--local_register <1/0> enable local buffer registration on send/recv buffers (default: disable)] \n\t"
"[-h,--help]\n",
basename(argv[0]));
return 0;
}
}
if (minBytes > maxBytes) {
fprintf(stderr, "invalid sizes for 'minbytes' and 'maxbytes': %llu > %llu\n",
(unsigned long long)minBytes,
(unsigned long long)maxBytes);
return -1;
}
#ifdef MPI_SUPPORT
MPI_Init(&argc, &argv);
#endif
TESTCHECK(run());
return 0;
}
testResult_t run() {
int totalProcs = 1, proc = 0, ncclProcs = 1, ncclProc = 0, color = 0;
int localRank = 0;
char hostname[1024];
getHostName(hostname, 1024);
#ifdef MPI_SUPPORT
MPI_Comm_size(MPI_COMM_WORLD, &totalProcs);
MPI_Comm_rank(MPI_COMM_WORLD, &proc);
uint64_t hostHashs[totalProcs];
hostHashs[proc] = getHostHash(hostname);
MPI_Allgather(MPI_IN_PLACE, 0, MPI_DATATYPE_NULL, hostHashs, sizeof(uint64_t), MPI_BYTE, MPI_COMM_WORLD);
for (int p=0; p<totalProcs; p++) {
if (p == proc) break;
if (hostHashs[p] == hostHashs[proc]) localRank++;
}
char* str = getenv("NCCL_TESTS_SPLIT_MASK");
uint64_t mask = str ? strtoul(str, NULL, 16) : 0;
MPI_Comm mpi_comm;
color = proc & mask;
MPI_Comm_split(MPI_COMM_WORLD, color, proc, &mpi_comm);
MPI_Comm_size(mpi_comm, &ncclProcs);
MPI_Comm_rank(mpi_comm, &ncclProc);
#endif
is_main_thread = is_main_proc = (proc == 0) ? 1 : 0;
PRINT("# nThread %d nGpus %d minBytes %ld maxBytes %ld step: %ld(%s) warmup iters: %d iters: %d agg iters: %d validation: %d graph: %d\n",
nThreads, nGpus, minBytes, maxBytes,
(stepFactor > 1)?stepFactor:stepBytes, (stepFactor > 1)?"factor":"bytes",
warmup_iters, iters, agg_iters, datacheck, cudaGraphLaunches);
if (blocking_coll) PRINT("# Blocking Enabled: wait for completion and barrier after each collective \n");
if (parallel_init) PRINT("# Parallel Init Enabled: threads call into NcclInitRank concurrently \n");
PRINT("#\n");
PRINT("# Using devices\n");
#define MAX_LINE 2048
char line[MAX_LINE];
int len = 0;
size_t maxMem = ~0;
char* envstr = getenv("NCCL_TESTS_DEVICE");
int gpu0 = envstr ? atoi(envstr) : -1;
for (int i=0; i<nThreads*nGpus; i++) {
int cudaDev = (gpu0 != -1 ? gpu0 : localRank*nThreads*nGpus) + i;
int rank = proc*nThreads*nGpus+i;
cudaDeviceProp prop;
CUDACHECK(cudaGetDeviceProperties(&prop, cudaDev));
len += snprintf(line+len, MAX_LINE-len, "# Rank %2d Group %2d Pid %6d on %10s device %2d [0x%02x] %s\n",
rank, color, getpid(), hostname, cudaDev, prop.pciBusID, prop.name);
maxMem = std::min(maxMem, prop.totalGlobalMem);
}
#if MPI_SUPPORT
char *lines = (proc == 0) ? (char *)malloc(totalProcs*MAX_LINE) : NULL;
// Gather all output in rank order to root (0)
MPI_Gather(line, MAX_LINE, MPI_BYTE, lines, MAX_LINE, MPI_BYTE, 0, MPI_COMM_WORLD);
if (proc == 0) {
for (int p = 0; p < totalProcs; p++)
PRINT("%s", lines+MAX_LINE*p);
free(lines);
}
MPI_Allreduce(MPI_IN_PLACE, &maxMem, 1, MPI_LONG, MPI_MIN, MPI_COMM_WORLD);
#else
PRINT("%s", line);
#endif
// We need sendbuff, recvbuff, expected (when datacheck enabled), plus 1G for the rest.
size_t memMaxBytes = (maxMem - (1<<30)) / (datacheck ? 3 : 2);
if (maxBytes > memMaxBytes) {
maxBytes = memMaxBytes;
if (proc == 0) printf("#\n# Reducing maxBytes to %ld due to memory limitation\n", maxBytes);
}
ncclUniqueId ncclId;
if (ncclProc == 0) {
NCCLCHECK(ncclGetUniqueId(&ncclId));
}
#ifdef MPI_SUPPORT
MPI_Bcast(&ncclId, sizeof(ncclId), MPI_BYTE, 0, mpi_comm);
MPI_Barrier(MPI_COMM_WORLD); // Ensure Bcast is complete for HCOLL
#endif
int gpus[nGpus*nThreads];
cudaStream_t streams[nGpus*nThreads];
void* sendbuffs[nGpus*nThreads];
void* recvbuffs[nGpus*nThreads];
void* expected[nGpus*nThreads];
size_t sendBytes, recvBytes;
ncclTestEngine.getBuffSize(&sendBytes, &recvBytes, (size_t)maxBytes, (size_t)ncclProcs*nGpus*nThreads);
envstr = getenv("NCCL_TESTS_DEVICE");
gpu0 = envstr ? atoi(envstr) : -1;
for (int i=0; i<nGpus*nThreads; i++) {
gpus[i] = (gpu0 != -1 ? gpu0 : localRank*nThreads*nGpus) + i;
CUDACHECK(cudaSetDevice(gpus[i]));
TESTCHECK(AllocateBuffs(sendbuffs+i, sendBytes, recvbuffs+i, recvBytes, expected+i, (size_t)maxBytes));
if (streamnull)
streams[i] = NULL;
else
CUDACHECK(cudaStreamCreateWithFlags(streams+i, cudaStreamNonBlocking));
}
//if parallel init is not selected, use main thread to initialize NCCL
ncclComm_t* comms = (ncclComm_t*)malloc(sizeof(ncclComm_t)*nThreads*nGpus);
#if NCCL_VERSION_CODE >= NCCL_VERSION(2,19,0)
void **sendRegHandles = NULL;