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Add a couple of bench scripts for cuda and cublas testing

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Gallo Alejandro 2022-09-12 19:53:50 +02:00
parent a5bb8f3d9c
commit 20c29ed815
4 changed files with 516 additions and 0 deletions
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10
bench/Makefile.am
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@ -1,3 +1,4 @@
AUTOMAKE_OPTIONS = subdir-objects
include $(top_srcdir)/atrip.mk include $(top_srcdir)/atrip.mk
AM_CPPFLAGS = -I$(top_srcdir)/include/ $(CTF_CPPFLAGS) AM_CPPFLAGS = -I$(top_srcdir)/include/ $(CTF_CPPFLAGS)
@ -19,4 +20,13 @@ endif
if WITH_CUDA if WITH_CUDA
test_main_CXXFLAGS = $(CUDA_CXXFLAGS) test_main_CXXFLAGS = $(CUDA_CXXFLAGS)
test_main_LDADD += $(CUDA_LDFLAGS) test_main_LDADD += $(CUDA_LDFLAGS)
AM_CXXFLAGS = $(CUDA_CXXFLAGS)
AM_LDFLAGS += $(CUDA_LDFLAGS)
bin_PROGRAMS += test-cublas-parallel-atrip
test_cublas_parallel_SOURCES = test-cublas-parallel-atrip.cxx
bin_PROGRAMS += test-cuda-sanity
test_cuda_sanity_SOURCES = test-cuda-sanity.cxx
endif endif

239
bench/test-cublas-parallel-atrip.cxx Normal file
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@ -0,0 +1,239 @@
#include <mpi.h>
#include <iostream>
#include <cassert>
#include <string.h>
#include <sstream>
#include <string>
#include <vector>
#include <cuda.h>
#include <chrono>
#include <map>
#include <cstdlib>
#include <unistd.h>
#include <CLI11.hpp>
#define CUBLASAPI
#include <cublas_api.h>
#include <cublas_v2.h>
struct Timer {
using Clock = std::chrono::high_resolution_clock;
using Event = std::chrono::time_point<Clock>;
std::chrono::duration<double> duration;
Event _start;
inline void start() noexcept { _start = Clock::now(); }
inline void stop() noexcept { duration += Clock::now() - _start; }
inline void clear() noexcept { duration *= 0; }
inline double count() const noexcept { return duration.count(); }
};
using Timings = std::map<std::string, Timer>;
#define _FORMAT(_fmt, ...) \
([&] (void) -> std::string { \
int _sz = std::snprintf(nullptr, 0, _fmt, __VA_ARGS__); \
std::vector<char> _out(_sz + 1); \
std::snprintf(&_out[0], _out.size(), _fmt, __VA_ARGS__); \
return std::string(_out.data()); \
})()
#define _CHECK_CUDA_SUCCESS(message, ...) \
do { \
CUresult result = __VA_ARGS__; \
printf("doing %s\n", message); \
if (result != CUDA_SUCCESS) { \
printf("\t!!CUDA_ERROR(%d): %s:%d %s\n", \
result, \
__FILE__, \
__LINE__, \
message); \
return 1; \
} \
} while (0)
#define _CHECK_CUBLAS_SUCCESS(message, ...) \
do { \
cublasStatus_t result = __VA_ARGS__; \
if (result != 0) { \
printf("\t!!CUBLAS_ERROR(%d): %s:%d %s\n", \
result, \
__FILE__, \
__LINE__, \
message); \
return 1; \
} \
} while (0)
int main(int argc, char** argv) {
using std::vector;
MPI_Init(NULL, NULL);
int rank, np, ngcards;
size_t no(10), nv(no * 10), its(2);
bool barrier = false;
MPI_Comm_rank(MPI_COMM_WORLD, &rank);
MPI_Comm_size(MPI_COMM_WORLD, &np);
CLI::App app{"Main bench for atrip"};
app.add_option("--no", no, "Occupied orbitals");
app.add_option("--nv", nv, "Virtual orbitals");
app.add_option("--its", its, "Number of iterations to be done");
app.add_option("--barrier", barrier, "Call a MPI_Barrier in every iteration?");
CLI11_PARSE(app, argc, argv);
const size_t oo = no * no, ooo = no * oo;
Timings timings;
MPI_Barrier(MPI_COMM_WORLD);
_CHECK_CUDA_SUCCESS("init for cuda",
cuInit(0));
_CHECK_CUDA_SUCCESS("get ncards",
cuDeviceGetCount(&ngcards));
CUcontext ctx;
CUdevice dev;
char hostname[256];
gethostname(hostname, 256);
printf("%s with rank %d gets card %d\n",
hostname,
rank,
rank % ngcards);
// set contexts
_CHECK_CUDA_SUCCESS("device get", cuDeviceGet(&dev, rank % ngcards));
_CHECK_CUDA_SUCCESS("creating context", cuCtxCreate(&ctx, 0, dev));
_CHECK_CUDA_SUCCESS("setting context", cuCtxSetCurrent(ctx));
_CHECK_CUDA_SUCCESS("synchronizing", cuCtxSynchronize());
MPI_Barrier(MPI_COMM_WORLD);
using host_slice_t = vector<double>;
vector<size_t> sizes = {nv * oo, nv * no , oo, oo * no, oo * no};
vector<CUdeviceptr> P_phh(3), P_ph(6) , H_hh(3), H_hhh(3), T_hhh(1);
vector<vector<CUdeviceptr>*> slices_d = {&P_phh, &P_ph , &H_hh, &H_hhh, &T_hhh};
vector<vector<host_slice_t>> slices_h(slices_d.size());
{
int i = -1;
for (auto& v: slices_d) {
i++;
for (auto& ptr: *v) {
_CHECK_CUDA_SUCCESS("malloc",
cuMemAlloc(&ptr,
sizes[i] * sizeof(double)));
slices_h[i].push_back(std::move(std::vector<double>(sizes[i])));
}
}
}
const double one = 1.0, zero = 0.0;
printf("its: %d\n", its);
printf("barrier: %d\n", barrier);
printf("no: %ld\n", no);
printf("nv: %ld\n", nv);
printf("SIZE %f GB\n", (3 * nv * oo
+ 6 * oo * nv
+ 3 * oo
+ 3 * ooo
+ 1 * ooo
) * sizeof(double) / 1024.0 / 1024.0 / 1024.0);
std::map<std::string, double> tflopss
{{ "dgemm", ooo * (no + nv) * 6.0 * 2.0 * its / 1e12},
{ "holes", ooo * no * 6.0 * 2.0 * its / 1e12},
{ "particles", ooo * nv * 6.0 * 2.0 * its / 1e12}};
cublasHandle_t handle;
_CHECK_CUBLAS_SUCCESS("handle create", cublasCreate(&handle));
printf("handle %ld\n", handle);
timings["dgemm"].start();
for (size_t i = 0; i < its; i++) {
if (barrier) {
MPI_Barrier(MPI_COMM_WORLD);
timings["memcpy"].start();
for (size_t _s = 0; _s < slices_d.size(); _s++) {
// for (size_t _b = 0; _b < slices_h[_s].size(); _b++) {
for (size_t _b = 0; _b < 1 ; _b++) {
auto device = (*slices_d[_s])[_b];
auto host = slices_h[_s][_b].data();
cuMemcpyHtoD(device, host, sizes[_s]);
}
}
timings["memcpy"].stop();
}
timings["holes"].start();
for (size_t j = 0; j < 3; j++) {
_CHECK_CUBLAS_SUCCESS(" > 'geming ...",
cublasDgemm(handle,
CUBLAS_OP_N,
CUBLAS_OP_N,
oo, no, no,
&one,
(double*)H_hhh[j], oo,
(double*)H_hh[j], no,
&zero,
(double*)T_hhh[0], oo));
_CHECK_CUBLAS_SUCCESS(" > 'geming ...",
cublasDgemm(handle,
CUBLAS_OP_N,
CUBLAS_OP_T,
oo, no, no,
&one,
(double*)H_hhh[j], oo,
(double*)H_hh[j], no,
&zero,
(double*)T_hhh[0], oo));
}
timings["holes"].stop();
timings["particles"].start();
for (size_t j = 0; j < 6; j++) {
_CHECK_CUBLAS_SUCCESS(" > 'geming ...",
cublasDgemm(handle,
CUBLAS_OP_T,
CUBLAS_OP_N,
oo, no, nv,
&one,
(double*)P_phh[j % 3], nv,
(double*)P_ph[j], nv,
&zero,
(double*)T_hhh[0], oo));
}
timings["particles"].stop();
cuCtxSynchronize();
}
timings["dgemm"].stop();
printf("Performance: \n");
for (auto name: {"holes", "particles", "dgemm"})
printf("%10s TFlops: %4.1f\n",
name,
tflopss[name]
/ timings[name].count());
printf("Timings: \n");
for (auto const& kv: timings)
printf("%10s: %10f\n", kv.first.c_str(), kv.second.count());
MPI_Finalize();
return 0;
}

163
bench/test-cublas-parallel.cxx Normal file
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@ -0,0 +1,163 @@
#include <mpi.h>
#include <iostream>
#include <cassert>
#include <string.h>
#include <sstream>
#include <string>
#include <vector>
#include <cuda.h>
#include <chrono>
#include <map>
#include <cstdlib>
#include <unistd.h>
#define CUBLASAPI
#include <cublas_api.h>
#include <cublas_v2.h>
struct Timer {
using Clock = std::chrono::high_resolution_clock;
using Event = std::chrono::time_point<Clock>;
std::chrono::duration<double> duration;
Event _start;
inline void start() noexcept { _start = Clock::now(); }
inline void stop() noexcept { duration += Clock::now() - _start; }
inline void clear() noexcept { duration *= 0; }
inline double count() const noexcept { return duration.count(); }
};
using Timings = std::map<std::string, Timer>;
#define _FORMAT(_fmt, ...) \
([&] (void) -> std::string { \
int _sz = std::snprintf(nullptr, 0, _fmt, __VA_ARGS__); \
std::vector<char> _out(_sz + 1); \
std::snprintf(&_out[0], _out.size(), _fmt, __VA_ARGS__); \
return std::string(_out.data()); \
})()
#define _CHECK_CUDA_SUCCESS(message, ...) \
do { \
CUresult result = __VA_ARGS__; \
printf("doing %s\n", message); \
if (result != CUDA_SUCCESS) { \
printf("\t!!CUDA_ERROR(%d): %s:%d %s\n", \
result, \
__FILE__, \
__LINE__, \
message); \
return 1; \
} \
} while (0)
#define _CHECK_CUBLAS_SUCCESS(message, ...) \
do { \
cublasStatus_t result = __VA_ARGS__; \
printf("CUBLAS: doing %s\n", message); \
if (result != 0) { \
printf("\t!!CUBLAS_ERROR(%d): %s:%d %s\n", \
result, \
__FILE__, \
__LINE__, \
message); \
return 1; \
} \
} while (0)
int main(int argc, char** argv) {
MPI_Init(NULL, NULL);
int rank, np, ngcards;
MPI_Comm_rank(MPI_COMM_WORLD, &rank);
MPI_Comm_size(MPI_COMM_WORLD, &np);
Timings timings;
MPI_Barrier(MPI_COMM_WORLD);
_CHECK_CUDA_SUCCESS("init for cuda",
cuInit(0));
_CHECK_CUDA_SUCCESS("get ncards",
cuDeviceGetCount(&ngcards));
const size_t N
= argc > 1
? atoi(argv[1])
: 30000
, dgemms
= argc > 2
? atoi(argv[2])
: 2
, flops = 2 * N * N * N * dgemms
;
CUcontext ctx;
CUdevice dev;
char hostname[256];
gethostname(hostname, 256);
printf("%s with rank %d gets card %d\n",
hostname,
rank,
rank % ngcards);
// set contexts
_CHECK_CUDA_SUCCESS("device get",
cuDeviceGet(&dev, rank % ngcards));
_CHECK_CUDA_SUCCESS("creating context",
cuCtxCreate(&ctx, 0, dev));
_CHECK_CUDA_SUCCESS("setting context",
cuCtxSetCurrent(ctx));
_CHECK_CUDA_SUCCESS("synchronizing",
cuCtxSynchronize());
MPI_Barrier(MPI_COMM_WORLD);
CUdeviceptr A, B, C;
const double one = 1.0;
printf("SIZE %f GB\n", N * N * sizeof(double) / 1024.0 / 1024.0 / 1024.0);
_CHECK_CUDA_SUCCESS("A", cuMemAlloc(&A, N * N * sizeof(double)));
_CHECK_CUDA_SUCCESS("B", cuMemAlloc(&B, N * N * sizeof(double)));
_CHECK_CUDA_SUCCESS("C", cuMemAlloc(&C, N * N * sizeof(double)));
cublasHandle_t handle;
cublasStatus_t stat;
_CHECK_CUBLAS_SUCCESS("handle create", cublasCreate(&handle));
printf("handle %ld\n", handle);
timings["dgemm"].start();
for (size_t i = 0; i < dgemms; i++) {
_CHECK_CUBLAS_SUCCESS(_FORMAT(" > 'geming %ld ...", i).c_str(),
cublasDgemm(handle,
CUBLAS_OP_N,
CUBLAS_OP_N,
N, N, N,
&one,
(double*)A, N,
(double*)B, N,
&one,
(double*)C, N));
}
cuCtxSynchronize();
timings["dgemm"].stop();
printf("dgemm Gflops: %f\n",
flops
/ timings["dgemm"].count()
/ 1024.0
/ 1024.0
/ 1024.0);
MPI_Finalize();
return 0;
}
// Local Variables:
// compile-command: "mpic++ \
// -pedantic -std=c++11 \
// -L./cudaroot/lib64 -lcuda \
// -L./cudaroot/lib64 -lcudart \
// -L./cudaroot/lib64 -lcublas \
// ./test-cublas-parallel.cxx -o test-cublas-parallel"
// End:

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bench/test-cuda-sanity.cxx Normal file
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@ -0,0 +1,104 @@
#include <mpi.h>
#include <iostream>
#include <cassert>
#include <string.h>
#include <sstream>
#include <string>
#include <vector>
#include <cuda.h>
#define _CHECK_CUDA_SUCCESS(message, ...) \
do { \
CUresult result = __VA_ARGS__; \
printf("doing %s\n", message); \
if (result != CUDA_SUCCESS) { \
printf("\t!!CUDA_ERROR(%d): %s:%d %s\n", \
result, \
__FILE__, \
__LINE__, \
message); \
return 1; \
} \
} while (0)
int main() {
int rank, np, ngcards;
MPI_Init(NULL, NULL);
MPI_Comm_rank(MPI_COMM_WORLD, &rank);
MPI_Comm_size(MPI_COMM_WORLD, &np);
_CHECK_CUDA_SUCCESS("init for cuda",
cuInit(0));
_CHECK_CUDA_SUCCESS("get ncards",
cuDeviceGetCount(&ngcards));
for (size_t rank = 0; rank < ngcards; rank++) {
CUcontext ctx;
CUdevice dev;
CUdevprop_st prop;
size_t _free, total, total2;
char *name = (char*)malloc(256);
printf("Setting contexts\n");
// set contexts
_CHECK_CUDA_SUCCESS("device get",
cuDeviceGet(&dev, rank));
_CHECK_CUDA_SUCCESS("creating context",
cuCtxCreate(&ctx, 0, dev));
_CHECK_CUDA_SUCCESS("setting context",
cuCtxSetCurrent(ctx));
_CHECK_CUDA_SUCCESS("synchronizing",
cuCtxSynchronize());
_CHECK_CUDA_SUCCESS("prop get",
cuDeviceGetProperties(&prop, dev));
_CHECK_CUDA_SUCCESS("meminfo get",
cuMemGetInfo(&_free, &total));
_CHECK_CUDA_SUCCESS("name get",
cuDeviceGetName(name, 256, dev));
_CHECK_CUDA_SUCCESS("totalmem get",
cuDeviceTotalMem(&total2, dev));
printf("\n"
"CUDA CARD RANK %d\n"
"=================\n"
"\tname: %s\n"
"\tShared Mem Per Block (KB): %f\n"
"\tFree/Total mem (GB): %f/%f\n"
"\total2 mem (GB): %f\n"
"\n",
dev,
name,
prop.sharedMemPerBlock / 1024.0,
_free / 1024.0 / 1024.0 / 1024.0 ,
total / 1024.0 / 1024.0 / 1024.0 ,
total2 / 1024.0 / 1024.0 / 1024.0
);
if (_free == 0 || total == 0 || total2 == 0)
return 1;
CUdeviceptr data;
_CHECK_CUDA_SUCCESS("memalloc 1",
cuMemAlloc(&data, sizeof(double) * 10000));
_CHECK_CUDA_SUCCESS("memalloc 2",
cuMemAlloc(&data, sizeof(double) * 10000));
}
MPI_Finalize();
return 0;
}
// Local Variables:
// compile-command: "mpic++ \
// -pedantic -std=c++11 \
// -L./cudaroot/lib64 -lcuda \
// -L./cudaroot/lib64 -lcudart \
// -L./cudaroot/lib64 -lcublas \
// ./mem.cxx -o mem"
// End: