1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134
|
import argparse
import sys
import torch
from .utils import Event, gen_sparse_coo, gen_sparse_coo_and_csr, gen_sparse_csr
def test_sparse_csr(m, nnz, test_count):
start_timer = Event(enable_timing=True)
stop_timer = Event(enable_timing=True)
csr = gen_sparse_csr((m, m), nnz)
vector = torch.randn(m, dtype=torch.double)
times = []
for _ in range(test_count):
start_timer.record()
csr.matmul(vector)
stop_timer.record()
times.append(start_timer.elapsed_time(stop_timer))
return sum(times) / len(times)
def test_sparse_coo(m, nnz, test_count):
start_timer = Event(enable_timing=True)
stop_timer = Event(enable_timing=True)
coo = gen_sparse_coo((m, m), nnz)
vector = torch.randn(m, dtype=torch.double)
times = []
for _ in range(test_count):
start_timer.record()
coo.matmul(vector)
stop_timer.record()
times.append(start_timer.elapsed_time(stop_timer))
return sum(times) / len(times)
def test_sparse_coo_and_csr(m, nnz, test_count):
start = Event(enable_timing=True)
stop = Event(enable_timing=True)
coo, csr = gen_sparse_coo_and_csr((m, m), nnz)
vector = torch.randn(m, dtype=torch.double)
times = []
for _ in range(test_count):
start.record()
coo.matmul(vector)
stop.record()
times.append(start.elapsed_time(stop))
coo_mean_time = sum(times) / len(times)
times = []
for _ in range(test_count):
start.record()
csr.matmul(vector)
stop.record()
times.append(start.elapsed_time(stop))
csr_mean_time = sum(times) / len(times)
return coo_mean_time, csr_mean_time
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="SpMV")
parser.add_argument("--format", default="csr", type=str)
parser.add_argument("--m", default="1000", type=int)
parser.add_argument("--nnz-ratio", "--nnz_ratio", default="0.1", type=float)
parser.add_argument("--outfile", default="stdout", type=str)
parser.add_argument("--test-count", "--test_count", default="10", type=int)
args = parser.parse_args()
if args.outfile == "stdout":
outfile = sys.stdout
elif args.outfile == "stderr":
outfile = sys.stderr
else:
outfile = open(args.outfile, "a")
test_count = args.test_count
m = args.m
nnz_ratio = args.nnz_ratio
nnz = int(nnz_ratio * m * m)
if args.format == "csr":
time = test_sparse_csr(m, nnz, test_count)
elif args.format == "coo":
time = test_sparse_coo(m, nnz, test_count)
elif args.format == "both":
time_coo, time_csr = test_sparse_coo_and_csr(m, nnz, test_count)
if args.format != "both":
print(
"format=",
args.format,
" nnz_ratio=",
nnz_ratio,
" m=",
m,
" time=",
time,
file=outfile,
)
else:
print(
"format=coo",
" nnz_ratio=",
nnz_ratio,
" m=",
m,
" time=",
time_coo,
file=outfile,
)
print(
"format=csr",
" nnz_ratio=",
nnz_ratio,
" m=",
m,
" time=",
time_csr,
file=outfile,
)
|