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Upgrade intel gemm conv tests #103

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Upgrade intel gemm conv tests #103

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89cee33
code/intel: Modify code to work better with automated testing environ…
Mar 21, 2018
f101923
fixup makefiles to remove my funky setup
Jun 19, 2018
e030e64
intel/gemm: Add in bindings to test OpenBLAS
Apr 23, 2018
a03af16
intel/convolution/mkl: Fixup typo introduced by previous commit
Jun 20, 2018
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8 changes: 4 additions & 4 deletions code/intel/convolution/mkl_conv/Makefile
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Original file line number Diff line number Diff line change
Expand Up @@ -30,10 +30,10 @@ ifeq ($(MKLLIB), mklml_intel)
EXTRALIB = -L$(MKLROOT)/lib -lmklml_intel
endif
ifeq ($(MKLLIB), mkl_rt)
EXTRALIB = -L$(MKLROOT)/lib/intel64/ -lmkl_rt \
EXTRALIB = -L$(MKLROOT)/lib -lmkl_rt \
-Wl,-rpath,$(MKLROOT)/lib/intel64
endif
EXTRALIB += -liomp5 -lpthread -lm -ldl
EXTRALIB += -L$(MKLROOT)/lib -liomp5 -lpthread -lm -ldl
endif

ifeq ($(CONVLIB),MKLDNN)
Expand All @@ -43,7 +43,7 @@ ifeq ($(MKLDNNROOT),)
to the install directory.)
endif
EXTRACXXFLAGS = -I$(MKLDNNROOT)/include -DUSE_MKLDNN
EXTRALIB = -L$(MKLDNNROOT)/lib -lmkldnn -Wl,-rpath,$(MKLDNNROOT)/lib
EXTRALIB = -L$(MKLDNNROOT)/lib -lmkldnn -lmklml_intel -Wl,-rpath,$(MKLDNNROOT)/lib
endif

ifeq ($(DEBUG), 1)
Expand All @@ -53,7 +53,7 @@ OPTFLAGS = -O3
endif

CXX = icpc
CXXFLAGS = -Wall -std=c++11 $(OPTFLAGS) $(EXTRACXXFLAGS) -fopenmp -I../../../kernels
CXXFLAGS = -Wall -std=c++11 $(OPTFLAGS) $(EXTRACXXFLAGS) -fopenmp -I../../../kernelss
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LFLAGS = -lrt
OBJS = std_conv_bench.o

Expand Down
272 changes: 209 additions & 63 deletions code/intel/convolution/mkl_conv/std_conv_bench.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -18,11 +18,13 @@
#include <float.h>
#include <time.h>
#include <assert.h>
#include <getopt.h>

#include <stdexcept>
#include <tuple>
#include <vector>
#include <string>
#include <iostream>

struct conv_problem {
int minibatch;
Expand Down Expand Up @@ -51,8 +53,6 @@ struct conv_problem {
#define INFERENCE_SERVER 1
#define INFERENCE_DEVICE 2

#define ITERS 1000

// Calculates convolution output dimension using the definition from Caffe
static inline int calc_out_dim(
int input_dim, int filter_dim, int padd, int stride)
Expand Down Expand Up @@ -352,10 +352,6 @@ static void usage()
printf(
"Usage: <executable> [OPTIONS]\n"
"\n"
"Output control:\n"
" --csv-output Produce CSV output\n"
" --original-output Produce output in the original format\n"
"\n"
"Control flops calculations:\n"
" --no-skip-padding Count ops with padding zeroes (default)\n"
" --skip-padding Do not count ops with padding zeroes\n"
Expand All @@ -367,8 +363,21 @@ static void usage()
" (AVX512_4VNNI CPUs)\n"
"Problem set control:\n"
" --training Training data set (default)\n"
" --inference-server Server inference data set\n"
" --inference-device Device inference data set\n"
" --inference Server inference data set\n"
" --device Device inference data set\n"
"Custom convolution definition:\n"
" --w Width\n"
" --h Height\n"
" --c \n"
" --n \n",
" --k \n",
" --filter_w \n",
" --filter_h \n",
" --pad_w \n",
" --pad_h \n",
" --wstride \n",
" --hstride \n",
" --repeat Number of times to test convolution (default: 50)\n",
"\n"
);
exit(-1);
Expand All @@ -377,36 +386,185 @@ static void usage()
int main(int argc, char **argv)
{
bool skip_padding = false;
bool csv_output = false;
int precision = PREC_F32;
std::vector<int> modes
= {FWD_CONVOLUTION, BWD_F_CONVOLUTION, BWD_D_CONVOLUTION};
std::vector<int> modes = {FWD_CONVOLUTION};
int problem_set = TRAINING;

for(argc--, argv++; argc; argv++, argc--) {
if (*argv == std::string("--csv-output"))
csv_output = true;
else if (*argv == std::string("--original-output"))
csv_output = false;
else if (*argv == std::string("--skip-padding"))
skip_padding = true;
else if (*argv == std::string("--no-skip-padding"))
skip_padding = false;
else if (*argv == std::string("--f32"))
precision = PREC_F32;
else if (*argv == std::string("--u8s8u8"))
precision = PREC_U8S8U8;
else if (*argv == std::string("--s16s16s32"))
precision = PREC_S16S16S32;
else if (*argv == std::string("--inference-device"))
problem_set = INFERENCE_DEVICE;
else if (*argv == std::string("--inference-server"))
problem_set = INFERENCE_SERVER;
else if (*argv == std::string("--training"))
problem_set = TRAINING;
else
usage();
}
// DEFAULTS
int ITERS = 50;
std::vector<std::tuple<unsigned int, unsigned int, unsigned int, unsigned int,
unsigned int, unsigned int, unsigned int,
unsigned int, unsigned int, unsigned int, unsigned int> > *problems = nullptr;
unsigned int w, h, c, n, k, filter_w, filter_h, pad_w, pad_h, wstride, hstride;
w = 151; h = 40; c = 1; n = 1; k = 32; filter_w = 20;
filter_h = 5; pad_w = 8; pad_h = 8; wstride = 8; hstride = 2;

// Use getopt_long here to allow for either driving the benchmark using
// built in tests, or make it a gemm tester
static struct option long_options[] = {
{"training", no_argument, 0, 0}, // These will run the full tests and override customization
{"inference", no_argument, 0, 0},
{"device", no_argument, 0, 0},
{"repeat", required_argument, 0, 0},
{"w", required_argument, 0, 0},
{"h", required_argument, 0, 0},
{"c", required_argument, 0, 0},
{"n", required_argument, 0, 0},
{"k", required_argument, 0, 0},
{"filter_w", required_argument, 0, 0},
{"filter_h", required_argument, 0, 0},
{"pad_w", required_argument, 0, 0},
{"pad_h", required_argument, 0, 0},
{"wstride", required_argument, 0, 0},
{"hstride", required_argument, 0, 0},
{"no-skip-padding", no_argument, 0, 0},
{"skip-padding", no_argument, 0, 0},
{"f32", no_argument, 0, 0},
{"u8s8u8", no_argument, 0, 0},
{"s16s16s32", no_argument, 0, 0},
{0, 0, 0, 0}
};

int opt;
do {
int option_index = 0;
opt = getopt_long(argc, argv, "", long_options, &option_index);
switch (opt) {
case -1:
break;
case 0:
switch (option_index) {
case 0:
if (problems == nullptr) {
problems = &training_set;
modes = {FWD_CONVOLUTION, BWD_F_CONVOLUTION, BWD_D_CONVOLUTION};
std::cout << "Running the training benchmark set" << std::endl;
}
break;
case 1:
if (problems == nullptr) {
problems = &inference_server_set;
std::cout << "Running the inference server set" << std::endl;
}
break;
case 2:
if (problems == nullptr) {
problems = &inference_device_set;
std::cout << "Running the inference device set" << std::endl;
}
break;
case 3:
ITERS = std::atoi(optarg);
if (ITERS <= 0) {
std::cerr << "Invalid repeat parameter spec'ed" << std::endl;
return 0;
}
break;
case 4:
w = std::atoi(optarg);
if (w <= 0) {
std::cerr << "Invalid w parameter spec'ed" << std::endl;
return 0;
}
break;
case 5:
h = std::atoi(optarg);
if (h <= 0) {
std::cerr << "Invalid h parameter spec'ed" << std::endl;
return 0;
}
break;
case 6:
c = std::atoi(optarg);
if (c <= 0) {
std::cerr << "Invalid c parameter spec'ed" << std::endl;
return 0;
}
break;
case 7:
n = std::atoi(optarg);
if (n <= 0) {
std::cerr << "Invalid n parameter spec'ed" << std::endl;
return 0;
}
break;
case 8:
k = std::atoi(optarg);
if (k <= 0) {
std::cerr << "Invalid k parameter spec'ed" << std::endl;
return 0;
}
break;
case 9:
filter_w = std::atoi(optarg);
if (filter_w <= 0) {
std::cerr << "Invalid filter_w paramter spec'ed" << std::endl;
return 0;
}
break;
case 10:
filter_h = std::atoi(optarg);
if (filter_h <= 0) {
std::cerr << "Invalid filter_h parameter spec'ed" << std::endl;
return 0;
}
break;
case 11:
pad_w = std::atoi(optarg);
if (pad_w < 0) {
std::cerr << "Invalid pad_w parameter spec'ed" << std::endl;
return 0;
}
break;
case 12:
pad_h = std::atoi(optarg);
if (pad_h < 0) {
std::cerr << "Invalid pad_h parameter spec'ed" << std::endl;
return 0;
}
break;
case 13:
wstride = std::atoi(optarg);
if (wstride <= 0) {
std::cerr << "Invalid wstride parameter spec'ed" << std::endl;
return 0;
}
break;
case 14:
hstride = std::atoi(optarg);
if (hstride <= 0) {
std::cerr << "Invalid hstride parameter spec'ed" << std::endl;
return 0;
}
break;
case 15:
skip_padding = false;
break;
case 16:
skip_padding = true;
break;
case 17:
precision = PREC_F32;
break;
case 18:
precision = PREC_U8S8U8;
break;
case 19:
precision = PREC_S16S16S32;
break;
default:
break;
}
break;
case '?':
usage();
return 0;
break;
default:
usage();
return 0;
break;
}
} while (opt != -1);

#ifdef USE_MKL
if (precision != PREC_F32) {
Expand All @@ -416,43 +574,31 @@ int main(int argc, char **argv)
}
#endif

#ifdef USE_MKLDNN
if (precision != PREC_F32 || problem_set != TRAINING)
modes = {FWD_CONVOLUTION};
#endif
if (problems == nullptr) {
problems = new std::vector<std::tuple<unsigned int, unsigned int, unsigned int, unsigned int,
unsigned int, unsigned int, unsigned int,
unsigned int, unsigned int, unsigned int, unsigned int> >();
problems->push_back(std::tuple<unsigned int, unsigned int, unsigned int, unsigned int,
unsigned int, unsigned int, unsigned int,
unsigned int, unsigned int, unsigned int, unsigned int>(w, h, c, n, k, filter_w,
filter_h, pad_w, pad_h, wstride, hstride));
}

const char *conv_mode_strs[] = {"FWD", "BWD_F", "BWD_D"};
const char *skip_padding_strs[]
= {"w/ padding in flops", "w/o padding in flops"};

const auto &problems = (problem_set == TRAINING
? training_set
: (problem_set == INFERENCE_DEVICE
? inference_device_set
: inference_server_set));
= {"w/ padding in flops", "w/o padding in flops"};

printf("OP,w,h,c,n,k,filter_w,filter_h,pad_w,pad_h,wstride,hstride,usecs,gops\n");
for (auto m : modes) {
if (!csv_output)
printf(" %s Convolution\n", conv_mode_strs[m]);
for (const auto& problem : problems) {
for (const auto& problem : *problems) {
conv_problem p;
std::tie(p.w, p.h, p.ic, p.minibatch, p.oc, p.fw, p.fh,
p.pad_w, p.pad_h, p.stride_w, p.stride_h) = problem;
p.iters = ITERS;
auto r = bench_conv(p, m, precision, skip_padding);
if (csv_output)
printf("%s,%d,%d,%d,%d,%d,%d,%d,%d,%d,%d,%d,%d,%e,%e,%e,%e\n",
conv_mode_strs[m], skip_padding,
p.minibatch, p.w, p.h, p.ic, p.oc, p.fw, p.fh,
p.stride_w, p.stride_h, p.pad_w, p.pad_h,
r.min_ms, r.max_gflops, r.avg_ms, r.avg_gflops);
else
printf("W=%d, H=%d, C=%d, N=%d, K=%d, S=%d, R=%d | "
"%s %s min(ms) %.2f; max(gflop/s) %.2f;"
"avg(ms) %.2f; avg(gflop/s) %.2f;\n",
p.w, p.h, p.ic, p.minibatch, p.oc, p.fw, p.fh,
conv_mode_strs[m], skip_padding_strs[skip_padding],
r.min_ms, r.max_gflops, r.avg_ms, r.avg_gflops);
printf("%s,%d,%d,%d,%d,%d,%d,%d,%d,%d,%d,%d,%f,%f\n",
conv_mode_strs[m], p.w, p.h, p.ic, p.minibatch, p.oc,
p.fw, p.fh,p.pad_w,p.pad_h,p.stride_h,p.stride_w,r.avg_ms*1000.0, r.avg_gflops);
fflush(0);
}
}
Expand Down
6 changes: 3 additions & 3 deletions code/intel/gemm/Makefile
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Original file line number Diff line number Diff line change
Expand Up @@ -15,11 +15,11 @@
# ******************************************************************************

CC = icc
CFLAGS = -O2 -Wall -I$(MKLROOT)/include -I../../kernels -qopenmp -std=c++11
CFLAGS = -O2 -Wall -I$(MKLROOT)/include -I../../kernels -fopenmp -std=c++11

EXTRALIB = -Wl,--start-group $(MKLROOT)/lib/intel64/libmkl_intel_lp64.a $(MKLROOT)/lib/intel64/libmkl_intel_thread.a $(MKLROOT)/lib/intel64/libmkl_core.a -Wl,--end-group -liomp5 -lpthread -lm -ldl
EXTRALIB = -Wl,--start-group $(MKLROOT)/lib/libmkl_intel_lp64.a $(MKLROOT)/lib/libmkl_intel_thread.a $(MKLROOT)/lib/libmkl_core.a -Wl,--end-group -L$(MKLROOT)/lib/ -liomp5 -lpthread -lm -ldl

all : sbench sbench_pack
all : sbench sbench_pack ibench_s8u8s32

ibench_s8u8s32 : ibench_s8u8s32.o
$(CC) $(CFLAGS) $^ $(EXTRALIB) -o $@
Expand Down
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