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wasmscore.py
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wasmscore.py
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#!/usr/bin/python3.8
""" WasmScore Benchmark """
import os
import sys
from datetime import datetime
import argparse
import subprocess
import textwrap
import logging
import pandas as pd
import numpy as np
from termcolor import colored
import yaml
# Command line options
parser = argparse.ArgumentParser(
formatter_class=argparse.RawDescriptionHelpFormatter,
epilog=textwrap.dedent(
"""
available engines: Wasmtime (default), Native
available benchmarks: See list
available suites: See list
available tests: WasmScore (default), SimdScore
"""
),
)
parser.add_argument("-b", "--benchmarks", nargs="+", help="Benchmarks to run")
parser.add_argument(
"-s",
"--suites",
nargs="+",
help="Suite to run (ignored if individual benchmark(s) specified)",
)
parser.add_argument(
"-t",
"--tests",
nargs="+",
help="Test to run (ignored if suite or individual benchmark(s) specified)",
)
group = parser.add_mutually_exclusive_group()
group.add_argument(
"-n",
"--native",
action="store_true",
help="Run the benchmark(s) natively. Not all benchmarks supported",
)
group.add_argument(
"-no-n",
"--no-native",
action="store_true",
help="Will disable running the benchmark(s) natively if done so by default",
)
parser.add_argument(
"-q",
"--quiet",
action="store_true",
help="Turn off printing of scores",
)
parser.add_argument(
"--list",
action="store_true",
help="List all available suites and individual benchmarks to run",
)
parser.add_argument(
"-log",
"--loglevel",
default="ERROR",
help="Provide logging level. Example --loglevel debug, default=ERROR",
)
parser.add_argument(
"-d",
"--dump",
action="store_true",
help="Dump run results to the screen",
)
parser.add_argument(
"-df",
"--dumpfile",
type=argparse.FileType("w"),
help="Dump run results to the given file",
)
parser.add_argument(
"-v",
"--version",
action="store_true",
help="Check the build version",
)
# Global Variables
args = parser.parse_args()
ARGS_DICT = vars(args)
DATE_TIME = datetime.now().strftime("%Y-%m-%d")
logging.basicConfig(
format="%(asctime)s %(levelname)-8s [%(filename)s:%(lineno)d] %(message)s",
datefmt="%Y-%m-%d:%H:%M:%S",
level=args.loglevel.upper(),
)
DEFAULT_BENCH_PROCESS_NUM = 3
SG_BENCHMARKS_BASE = "/sightglass/benchmarks/"
BENCHMARK_DF = None
SUITE_DF = None
WASMSCORE_CONSTANT = 10000000000
# Dictionaries
sg_benchmarks_wasm = {
"blake3-scalar": "blake3-scalar/benchmark.wasm",
"blake3-simd": "blake3-simd/benchmark.wasm",
"blind-sig": "blind-sig/benchmark.wasm",
"bzip2": "bz2/benchmark.wasm",
"hex-simd": "hex-simd/benchmark.wasm",
# "image-classification": "image-classification/image-classification-benchmark.wasm",
"tract_mobilenet_v2_onnx": "inference_tract/mobile_net_v2_onnx_benchmark.wasm",
"tract_mobilenet_v2_tensorflow": "inference_tract/mobile_net_v2_tensorflow_benchmark.wasm",
"intgemm-simd": "intgemm-simd/benchmark.wasm",
"libsodium-aead_aes256gcm": "libsodium/libsodium-aead_aes256gcm.wasm",
"libsodium-aead_aes256gcm2": "libsodium/libsodium-aead_aes256gcm2.wasm",
"libsodium-aead_chacha20poly1305": "libsodium/libsodium-aead_chacha20poly1305.wasm",
"libsodium-aead_chacha20poly13052": "libsodium/libsodium-aead_chacha20poly13052.wasm",
"libsodium-aead_xchacha20poly1305": "libsodium/libsodium-aead_xchacha20poly1305.wasm",
"libsodium-auth": "libsodium/libsodium-auth.wasm",
"libsodium-auth2": "libsodium/libsodium-auth2.wasm",
"libsodium-auth3": "libsodium/libsodium-auth3.wasm",
"libsodium-auth5": "libsodium/libsodium-auth5.wasm",
"libsodium-auth6": "libsodium/libsodium-auth6.wasm",
"libsodium-auth7": "libsodium/libsodium-auth7.wasm",
"libsodium-box": "libsodium/libsodium-box.wasm",
"libsodium-box2": "libsodium/libsodium-box2.wasm",
"libsodium-box7": "libsodium/libsodium-box7.wasm",
"libsodium-box8": "libsodium/libsodium-box8.wasm",
"libsodium-box_easy": "libsodium/libsodium-box_easy.wasm",
"libsodium-box_easy2": "libsodium/libsodium-box_easy2.wasm",
"libsodium-box_seal": "libsodium/libsodium-box_seal.wasm",
"libsodium-box_seed": "libsodium/libsodium-box_seed.wasm",
"libsodium-chacha20": "libsodium/libsodium-chacha20.wasm",
"libsodium-codecs": "libsodium/libsodium-codecs.wasm",
"libsodium-core1": "libsodium/libsodium-core1.wasm",
"libsodium-core2": "libsodium/libsodium-core2.wasm",
"libsodium-core3": "libsodium/libsodium-core3.wasm",
"libsodium-core4": "libsodium/libsodium-core4.wasm",
"libsodium-core5": "libsodium/libsodium-core5.wasm",
"libsodium-core6": "libsodium/libsodium-core6.wasm",
"libsodium-core_ed25519": "libsodium/libsodium-core_ed25519.wasm",
"libsodium-core_ristretto255": "libsodium/libsodium-core_ristretto255.wasm",
"libsodium-ed25519_convert": "libsodium/libsodium-ed25519_convert.wasm",
"libsodium-generichash": "libsodium/libsodium-generichash.wasm",
"libsodium-generichash2": "libsodium/libsodium-generichash2.wasm",
"libsodium-generichash3": "libsodium/libsodium-generichash3.wasm",
"libsodium-hash": "libsodium/libsodium-hash.wasm",
"libsodium-hash3": "libsodium/libsodium-hash3.wasm",
"libsodium-kdf": "libsodium/libsodium-kdf.wasm",
"libsodium-keygen": "libsodium/libsodium-keygen.wasm",
"libsodium-kx": "libsodium/libsodium-kx.wasm",
"libsodium-metamorphic": "libsodium/libsodium-metamorphic.wasm",
"libsodium-misuse": "libsodium/libsodium-misuse.wasm",
"libsodium-onetimeauth": "libsodium/libsodium-onetimeauth.wasm",
"libsodium-onetimeauth2": "libsodium/libsodium-onetimeauth2.wasm",
"libsodium-onetimeauth7": "libsodium/libsodium-onetimeauth7.wasm",
"libsodium-pwhash_argon2i": "libsodium/libsodium-pwhash_argon2i.wasm",
"libsodium-pwhash_argon2id": "libsodium/libsodium-pwhash_argon2id.wasm",
"libsodium-pwhash_scrypt": "libsodium/libsodium-pwhash_scrypt.wasm",
"libsodium-pwhash_scrypt_ll": "libsodium/libsodium-pwhash_scrypt_ll.wasm",
"libsodium-randombytes": "libsodium/libsodium-randombytes.wasm",
"libsodium-scalarmult": "libsodium/libsodium-scalarmult.wasm",
"libsodium-scalarmult2": "libsodium/libsodium-scalarmult2.wasm",
"libsodium-scalarmult5": "libsodium/libsodium-scalarmult5.wasm",
"libsodium-scalarmult6": "libsodium/libsodium-scalarmult6.wasm",
"libsodium-scalarmult7": "libsodium/libsodium-scalarmult7.wasm",
"libsodium-scalarmult8": "libsodium/libsodium-scalarmult8.wasm",
"libsodium-scalarmult_ed25519": "libsodium/libsodium-scalarmult_ed25519.wasm",
"libsodium-scalarmult_ristretto255": "libsodium/libsodium-scalarmult_ristretto255.wasm",
"libsodium-secretbox": "libsodium/libsodium-secretbox.wasm",
"libsodium-secretbox2": "libsodium/libsodium-secretbox2.wasm",
"libsodium-secretbox7": "libsodium/libsodium-secretbox7.wasm",
"libsodium-secretbox8": "libsodium/libsodium-secretbox8.wasm",
"libsodium-secretbox_easy": "libsodium/libsodium-secretbox_easy.wasm",
"libsodium-secretbox_easy2": "libsodium/libsodium-secretbox_easy2.wasm",
"libsodium-secretstream": "libsodium/libsodium-secretstream.wasm",
"libsodium-shorthash": "libsodium/libsodium-shorthash.wasm",
"libsodium-sign": "libsodium/libsodium-sign.wasm",
"libsodium-siphashx24": "libsodium/libsodium-siphashx24.wasm",
"libsodium-sodium_core": "libsodium/libsodium-sodium_core.wasm",
"libsodium-sodium_utils": "libsodium/libsodium-sodium_utils.wasm",
"libsodium-sodium_utils2": "libsodium/libsodium-sodium_utils2.wasm",
"libsodium-sodium_utils3": "libsodium/libsodium-sodium_utils3.wasm",
"libsodium-sodium_version": "libsodium/libsodium-sodium_version.wasm",
"libsodium-stream": "libsodium/libsodium-stream.wasm",
"libsodium-stream2": "libsodium/libsodium-stream2.wasm",
"libsodium-stream3": "libsodium/libsodium-stream3.wasm",
"libsodium-stream4": "libsodium/libsodium-stream4.wasm",
"libsodium-verify1": "libsodium/libsodium-verify1.wasm",
"libsodium-xchacha20": "libsodium/libsodium-xchacha20.wasm",
"meshoptimizer": "meshoptimizer/benchmark.wasm",
"pulldown-cmark": "pulldown-cmark/benchmark.wasm",
"ackermann": "shootout/shootout-ackermann.wasm",
"base64": "shootout/shootout-base64.wasm",
"ctype": "shootout/shootout-ctype.wasm",
"ed25519": "shootout/shootout-ed25519.wasm",
"fibonacci": "shootout/shootout-fib2.wasm",
"gimli": "shootout/shootout-gimli.wasm",
"heapsort": "shootout/shootout-heapsort.wasm",
"keccak": "shootout/shootout-keccak.wasm",
"matrix": "shootout/shootout-matrix.wasm",
"memmove": "shootout/shootout-memmove.wasm",
"minicsv": "shootout/shootout-minicsv.wasm",
"nestedloop": "shootout/shootout-nestedloop.wasm",
"random": "shootout/shootout-random.wasm",
"ratelimit": "shootout/shootout-ratelimit.wasm",
"seqhash": "shootout/shootout-seqhash.wasm",
"sieve": "shootout/shootout-sieve.wasm",
"switch": "shootout/shootout-switch.wasm",
"xblabla20": "shootout/shootout-xblabla20.wasm",
"xchacha20": "shootout/shootout-xchacha20.wasm",
"spidermonkey": "spidermonkey/benchmark.wasm",
}
sg_benchmarks_native = {
"meshoptimizer": "meshoptimizer/codecbench-simd.so",
"tract_mobilenet_v2_onnx": "inference_tract/mobile_net_v2_onnx_benchmark.so",
"tract_mobilenet_v2_tensorflow": "inference_tract/mobile_net_v2_tensorflow_benchmark.so",
"ackermann": "shootout/shootout-ackermann.so",
"base64": "shootout/shootout-base64.so",
"ctype": "shootout/shootout-ctype.so",
"ed25519": "shootout/shootout-ed25519.so",
"fibonacci": "shootout/shootout-fib2.so",
"gimli": "shootout/shootout-gimli.so",
"heapsort": "shootout/shootout-heapsort.so",
"keccak": "shootout/shootout-keccak.so",
"matrix": "shootout/shootout-matrix.so",
"memmove": "shootout/shootout-memmove.so",
"minicsv": "shootout/shootout-minicsv.so",
"nestedloop": "shootout/shootout-nestedloop.so",
"random": "shootout/shootout-random.so",
"ratelimit": "shootout/shootout-ratelimit.so",
"seqhash": "shootout/shootout-seqhash.so",
"sieve": "shootout/shootout-sieve.so",
"switch": "shootout/shootout-switch.so",
"xblabla20": "shootout/shootout-xblabla20.so",
"xchacha20": "shootout/shootout-xchacha20.so",
}
sg_benchmarks_native_build = {
"tract_mobilenet_v2_onnx": "./build_mobile_net_v2_onnx_native.sh",
"tract_mobilenet_v2_tensorflow": "./build_mobile_net_v2_tensorflow_native.sh",
"meshoptimizer": "./build-native.sh",
"ackermann": "./build-native.sh",
"base64": "./build-native.sh",
"ctype": "./build-native.sh",
"ed25519": "./build-native.sh",
"fibonacci": "./build-native.sh",
"gimli": "./build-native.sh",
"heapsort": "./build-native.sh",
"keccak": "./build-native.sh",
"matrix": "./build-native.sh",
"memmove": "./build-native.sh",
"minicsv": "./build-native.sh",
"nestedloop": "./build-native.sh",
"random": "./build-native.sh",
"ratelimit": "./build-native.sh",
"seqhash": "./build-native.sh",
"sieve": "./build-native.sh",
"switch": "./build-native.sh",
"xblabla20": "./build-native.sh",
"xchacha20": "./build-native.sh",
}
perf_suites = {
"app-wasmscore": ["meshoptimizer"],
"core-wasmscore": ["ackermann", "ctype", "fibonacci"],
"crypto-wasmscore": ["base64", "ed25519", "seqhash"],
"ai-wasmscore": ["tract_mobilenet_v2_onnx", "tract_mobilenet_v2_tensorflow"],
"regex-wasmscore": [],
"shootout": [
"base64",
"ctype",
"fibonacci",
"gimli",
"heapsort",
"keccak",
"matrix",
"memmove",
"minicsv",
"nested-loop",
"random",
"ratelimit",
"seqhash",
"sieve",
"switch",
"xblahblah20",
"xchacha20",
],
"libsodium": [
"libsodium-aead_aes256gcm",
"libsodium-aead_aes256gcm2",
"libsodium-aead_chacha20poly1305",
"libsodium-aead_chacha20poly13052",
"libsodium-aead_xchacha20poly1305",
"libsodium-auth",
"libsodium-auth2",
"libsodium-auth3",
"libsodium-auth5",
"libsodium-auth6",
"libsodium-auth7",
"libsodium-box",
"libsodium-box2",
"libsodium-box7",
"libsodium-box8",
"libsodium-box_easy",
"libsodium-box_easy2",
"libsodium-box_seal",
"libsodium-box_seed",
"libsodium-chacha20",
"libsodium-codecs",
"libsodium-core1",
"libsodium-core2",
"libsodium-core3",
"libsodium-core4",
"libsodium-core5",
"libsodium-core6",
"libsodium-core_ed25519",
"libsodium-core_ristretto255",
"libsodium-ed25519_convert",
"libsodium-generichash",
"libsodium-generichash2",
"libsodium-generichash3",
"libsodium-hash",
"libsodium-hash3",
"libsodium-kdf",
"libsodium-keygen",
"libsodium-kx",
"libsodium-metamorphic",
"libsodium-misuse",
"libsodium-onetimeauth",
"libsodium-onetimeauth2",
"libsodium-onetimeauth7",
"libsodium-pwhash_argon2i",
"libsodium-pwhash_argon2id",
"libsodium-pwhash_scrypt",
"libsodium-pwhash_scrypt_ll",
"libsodium-randombytes",
"libsodium-scalarmult",
"libsodium-scalarmult2",
"libsodium-scalarmult5",
"libsodium-scalarmult6",
"libsodium-scalarmult7",
"libsodium-scalarmult8",
"libsodium-scalarmult_ed25519",
"libsodium-scalarmult_ristretto255",
"libsodium-secretbox",
"libsodium-secretbox2",
"libsodium-secretbox7",
"libsodium-secretbox8",
"libsodium-secretbox_easy",
"libsodium-secretbox_easy2",
"libsodium-secretstream",
"libsodium-shorthash",
"libsodium-sign",
"libsodium-siphashx24",
"libsodium-sodium_core",
"libsodium-sodium_utils",
"libsodium-sodium_utils2",
"libsodium-sodium_utils3",
"libsodium-sodium_version",
"libsodium-stream",
"libsodium-stream2",
"libsodium-stream3",
"libsodium-stream4",
"libsodium-verify1",
"libsodium-xchacha20",
],
"scalar-simdscore": ["blake3-scalar"],
"simd-simdscore": ["blake3-simd"],
}
perf_tests = [
"WasmScore",
"SimdScore",
"Quickrun-WasmScore",
"Quickrun-SimdScore",
"Quickrun-All",
]
# Build dictionaries based on cmd flags and directory file structure
def run_benchmarks(benchmark, run_native=False):
"""Runs the benchmark"""
logging.info("Running benchmark ...")
logging.info("Run native ... %s", run_native)
results_dir = f"{SG_BENCHMARKS_BASE}/results/"
create_results_path_cmd_string = f"mkdir -p {results_dir}"
try:
logging.info(
"Trying mkdir for results_path ... %s", create_results_path_cmd_string
)
output = subprocess.check_output(
create_results_path_cmd_string,
shell=True,
text=True,
stderr=subprocess.STDOUT,
)
logging.debug("%s", output)
except subprocess.CalledProcessError as error:
print(f"mkdir for build folder failed with error code {error.returncode}")
sys.exit(error.returncode)
native_df = None
if run_native and sg_benchmarks_native[benchmark]:
print_verbose(f"Collecting Native ({benchmark}).")
native_benchmark_dir = os.path.dirname(
f"{SG_BENCHMARKS_BASE}" + sg_benchmarks_native[benchmark]
)
logging.debug("native_benchmark_dir ... %s", native_benchmark_dir)
native_benchmark_path = (
f"{SG_BENCHMARKS_BASE}" + sg_benchmarks_native[benchmark]
)
logging.debug("native_benchmark_path ... %s", native_benchmark_path)
results_path = f"{results_dir}/{benchmark}" + "_native_results.csv"
logging.debug("results_path ... %s", results_path)
results_summarized_path = (
f"{SG_BENCHMARKS_BASE}/results/{benchmark}"
+ "_results_native_summarized.csv"
)
logging.debug("results_summarized_path ... %s", results_summarized_path)
results_summarized_transposed_path = (
f"{SG_BENCHMARKS_BASE}/results/{benchmark}"
+ "_results_native_summarized_transposed.csv"
)
logging.debug(
"results_summarized_transposed_path ... %s",
results_summarized_transposed_path,
)
native_build_cmd_string = sg_benchmarks_native_build[benchmark];
logging.debug("native_benchmark_build_path ... %s", native_build_cmd_string);
try:
logging.info("Trying native build ... ")
output = subprocess.check_output(
native_build_cmd_string.split(),
shell=True,
text=True,
cwd=f"{native_benchmark_dir}",
stderr=subprocess.STDOUT,
)
logging.debug("%s", output)
except subprocess.CalledProcessError as error:
print(
f"Building native benchmark ({benchmark}) failed with error code {error.returncode}"
)
sys.exit(error.returncode)
if not os.path.basename(f"{native_benchmark_path}") == "benchmark.so":
native_build_cp_string = f"cp {native_benchmark_path} ./benchmark.so"
try:
logging.info("Trying native cp ... ")
output = subprocess.check_output(
native_build_cp_string.split(),
shell=False,
text=True,
cwd=f"{native_benchmark_dir}",
stderr=subprocess.STDOUT,
)
logging.debug("%s", output)
except subprocess.CalledProcessError as error:
print(f"Building native failed with error code {error.returncode}")
sys.exit(error.returncode)
cli_cmd_string = (
"LD_LIBRARY_PATH=/sightglass/engines/native/ "
"/sightglass/target/release/sightglass-cli benchmark "
f"{native_benchmark_path} --engine "
f"/sightglass/engines/native/libengine.so --processes={DEFAULT_BENCH_PROCESS_NUM} --raw "
f"--output-format csv --output-file {results_path}"
)
try:
logging.info(
"Trying sightglass-cli benchmark command for native ... %s",
cli_cmd_string,
)
output = subprocess.check_output(
cli_cmd_string,
shell=True,
text=True,
cwd=f"{native_benchmark_dir}",
stderr=subprocess.STDOUT,
executable="/bin/bash",
)
logging.debug("%s", output)
except subprocess.CalledProcessError as error:
print(
f"Running sightglass-cli benchmark ({benchmark}) failed with error code {error.returncode}"
)
sys.exit(error.returncode)
cli_summarize_string = (
f"/sightglass/target/release/sightglass-cli summarize --input-format csv "
f"--output-format csv -f {results_path} > {results_summarized_path}"
)
try:
logging.info(
"Trying sightglass-cli summarize command for native ... %s",
cli_summarize_string,
)
output = subprocess.check_output(
cli_summarize_string,
shell=True,
text=True,
cwd=f"{native_benchmark_dir}",
stderr=subprocess.STDOUT,
executable="/bin/bash",
)
logging.debug("%s", output)
except subprocess.CalledProcessError as error:
print(
f"Running sightglass-cli summarize failed with error code {error.returncode}"
)
sys.exit(error.returncode)
if os.stat(results_summarized_path).st_size == 0:
print("Native execution did not run properly ... exiting")
sys.exit(1)
else:
logging.info("Trying printing native benchmark results ...")
os.system(
f'grep -v "cycles" {results_summarized_path} > results/tmpfile '
f"&& mv results/tmpfile {results_summarized_path}"
)
pd.read_csv(
results_summarized_path, usecols=["phase", "mean"], header=0
).to_csv(results_summarized_transposed_path, header=True, index=False)
native_df = pd.read_csv(
results_summarized_path,
usecols=["wasm", "arch", "engine", "phase", "mean"],
)[["wasm", "arch", "engine", "phase", "mean"]]
native_df = native_df.rename(columns={"wasm": "benchmark"})
native_df.loc[:, ["engine"]] = "Native"
native_df.loc[:, ["benchmark"]] = f"{benchmark}"
os.system(f"sed -i 1d {results_summarized_transposed_path}")
if not ARGS_DICT["quiet"]:
termgraph_title = f"{benchmark} native time(ns)"
os.system(
f"termgraph {results_summarized_transposed_path} "
f'--title "{termgraph_title}" --color blue'
)
else:
if isinstance(native_df, pd.DataFrame):
print(native_df.to_csv(index=False, header=None, sep=","))
os.system("cd /sightglass".format(native_benchmark_dir))
elif run_native:
print_verbose(f"Native {benchmark} is not supported")
print_verbose(f"Collecting Wasm ({benchmark}).")
wasm_benchmark_dir = os.path.dirname(
f"{SG_BENCHMARKS_BASE}" + sg_benchmarks_wasm[benchmark]
)
logging.debug("wasm_benchmark_dir ... %s", wasm_benchmark_dir)
wasm_benchmark_path = f"{SG_BENCHMARKS_BASE}" + sg_benchmarks_wasm[benchmark]
logging.debug("wasm_benchmark_path ... %s", wasm_benchmark_path)
results_path = f"{results_dir}/{benchmark}" + "_wasm_results.csv"
logging.debug("results_path ... %s", results_path)
results_summarized_path = (
f"{SG_BENCHMARKS_BASE}/results/{benchmark}" + "_results_wasm_summarized.csv"
)
logging.debug("results_summarized_path ... %s", results_summarized_path)
results_summarized_transposed_path = (
f"{SG_BENCHMARKS_BASE}/results/{benchmark}"
+ "_results_wasm_summarized_transposed.csv"
)
logging.debug(
"results_summarized_transposed_path ... %s",
results_summarized_transposed_path,
)
termgraph_title = f"{benchmark} wasm time(ns)"
cli_cmd_string = (
f"/sightglass/target/release/sightglass-cli benchmark "
f"--processes={DEFAULT_BENCH_PROCESS_NUM} --engine "
f"/sightglass/engines/wasmtime/libengine.so --raw --output-format csv --output-file "
f"{results_path} -- {wasm_benchmark_path}"
)
try:
logging.info(
"Trying sightglass-cli benchmark command for wasm ... %s", cli_cmd_string
)
output = subprocess.check_output(
cli_cmd_string,
shell=True,
text=True,
cwd=f"{wasm_benchmark_dir}",
stderr=subprocess.STDOUT,
)
logging.debug("%s", output)
except subprocess.CalledProcessError as error:
print(
f"Running sightglass-cli benchmark failed with error code {error.returncode}"
)
sys.exit(error.returncode)
cli_summarize_string = (
f"/sightglass/target/release/sightglass-cli summarize --input-format csv "
f"--output-format csv -f {results_path} > {results_summarized_path}"
)
try:
logging.info(
"Trying sightglass-cli summarize command for wasm ... %s",
cli_summarize_string,
)
output = subprocess.check_output(
cli_summarize_string,
shell=True,
text=True,
cwd=f"{wasm_benchmark_dir}",
stderr=subprocess.STDOUT,
)
logging.debug("%s", output)
except subprocess.CalledProcessError as error:
print(
f"Running sightglass-cli summarize failed with error code {error.returncode}"
)
sys.exit(error.returncode)
os.system(
f'grep -v "cycles" {results_summarized_path} > results/tmpfile && '
f"mv results/tmpfile {results_summarized_path}"
)
pd.read_csv(results_summarized_path, usecols=["phase", "mean"], header=0).to_csv(
results_summarized_transposed_path, header=True, index=False
)
wasm_df = pd.read_csv(
results_summarized_path, usecols=["wasm", "arch", "engine", "phase", "mean"]
)[["wasm", "arch", "engine", "phase", "mean"]]
wasm_df = wasm_df.rename(columns={"wasm": "benchmark"})
wasm_df.loc[:, ["engine"]] = "Wasmtime"
wasm_df.loc[:, ["benchmark"]] = f"{benchmark}"
benchmark_df = wasm_df.copy()
if isinstance(native_df, pd.DataFrame):
logging.info("Getting efficiency ... ")
native_mean = native_df[native_df["phase"].str.match("Execution")].iloc[0][
"mean"
]
wasm_mean = wasm_df[wasm_df["phase"].str.match("Execution")].iloc[0]["mean"]
benchmark_df["efficiency"] = float("NaN")
benchmark_df = pd.concat([native_df, benchmark_df])
benchmark_df.loc[
(benchmark_df["phase"] == "Execution")
& (benchmark_df["engine"] == "Wasmtime"),
"efficiency",
] = (
native_mean / wasm_mean
)
benchmark_df.loc[
(benchmark_df["phase"] == "Execution")
& (benchmark_df["engine"] == "Native"),
"efficiency",
] = (
wasm_mean / native_mean
)
os.system(f"sed -i 1d {results_summarized_transposed_path}")
if not ARGS_DICT["quiet"]:
os.system(
f'termgraph {results_summarized_transposed_path} --title "{termgraph_title}" --color blue'
)
else:
if isinstance(wasm_df, pd.DataFrame):
print(wasm_df.to_csv(index=False, header=None, sep=","))
if isinstance(benchmark_df, pd.DataFrame):
global BENCHMARK_DF
BENCHMARK_DF = pd.concat([BENCHMARK_DF, benchmark_df])
return benchmark_df
def geo_mean_overflow(iterable):
"""Helper function to avoid overflow errors during geo-mean calculation"""
calc = np.log(iterable)
return np.exp(calc.mean())
def run_suites(suite_name, run_native=False):
"""Benchmark a suite"""
logging.info("Running suite ...")
print_verbose("")
print_verbose(
colored(
f"Benchmarking {suite_name}: {perf_suites[suite_name]}",
"green",
attrs=["bold"],
)
)
suite_df = None
suite_wasm_efficiency_avg = None
suite_wasm_time_mean = None
for benchmark in perf_suites[suite_name]:
if ARGS_DICT["native"] or run_native:
benchmark_df = run_benchmarks(benchmark, True)
else:
benchmark_df = run_benchmarks(benchmark)
suite_df = pd.concat([suite_df, benchmark_df])
if not isinstance(suite_df, pd.DataFrame):
return [None, None]
suite_wasm_time_slice_df = pd.DataFrame(
suite_df.loc[
(suite_df["phase"] == "Execution") & (suite_df["engine"] == "Wasmtime"),
"mean",
]
)
suite_wasm_time_mean = geo_mean_overflow(suite_wasm_time_slice_df.loc[:, "mean"])
suite_summary_df = pd.DataFrame(
[[f"{suite_name}", suite_wasm_time_mean]], columns=["suite", "time"]
)
suite_df.insert(0, "suite", f"{suite_name}")
if "efficiency" in suite_df:
suite_wasm_efficiency_avg = suite_df.loc[
(suite_df["engine"] == "Wasmtime") & (suite_df["phase"] == "Execution"),
"efficiency",
].mean()
suite_summary_df["efficiency"] = [suite_wasm_efficiency_avg]
if isinstance(benchmark_df, pd.DataFrame):
global SUITE_DF
SUITE_DF = pd.concat([SUITE_DF, suite_df])
return suite_summary_df
def run_wasmscore():
"""WasmScore test. Runs a collection of suites, both Wasm and native benchmarks
by default, and reports out a Wasm performance score based a geo-mean of the
performances of the benchmark suites. The test also reports a Wasm efficiency based
on Wasm's performance relative to native."""
logging.info("Running WasmScore test ... ")
wasmscore_summary_df = None
for suite in [
"ai-wasmscore",
"app-wasmscore",
"core-wasmscore",
"crypto-wasmscore",
"regex-wasmscore",
]:
suite_summary_df = run_suites(suite, not ARGS_DICT["no_native"])
if isinstance(suite_summary_df, pd.DataFrame):
wasmscore_summary_df = pd.concat([wasmscore_summary_df, suite_summary_df])
if isinstance(wasmscore_summary_df, pd.DataFrame):
print_verbose("")
print_verbose(
colored(
wasmscore_summary_df.reset_index(drop=True), "green", attrs=["bold"]
)
)
print_verbose("")
if "efficiency" in wasmscore_summary_df:
print(
colored(
"Wasm Efficiency Score (Higher Better): {:.2f}".format(
wasmscore_summary_df.loc[:, "efficiency"].mean()
),
"green",
attrs=["bold"],
)
)
print(
colored(
"Wasm Execution Score (Higher Better): {:.2f}".format(
1
/ geo_mean_overflow(wasmscore_summary_df.loc[:, "time"])
* WASMSCORE_CONSTANT
),
"green",
attrs=["bold"],
)
)
print("")
def run_simdscore():
"""SimdScore test: Benchmarks scalar and simd version of select benchmarks and
reports a Wasm's scalar and simd performance score based on a geo-mean of
the performances of the benchmarks. The test also reports a Wasm simd efficiency
score calculated using Wasm's simd speed-up relative to native."""
logging.info("Running SimdScore test ...")
simdscore_summary_df = None
for suite in [
"scalar-simdscore",
"simd-simdscore",
]:
#suite_summary_df = run_suites(suite, not ARGS_DICT["no_native"])
suite_summary_df = run_suites(suite, False)
if isinstance(suite_summary_df, pd.DataFrame):
simdscore_summary_df = pd.concat([simdscore_summary_df, suite_summary_df])
if isinstance(simdscore_summary_df, pd.DataFrame):
print_verbose("")
print_verbose(
colored(
simdscore_summary_df.reset_index(drop=True).to_string(index=False), "green", attrs=["bold"]
)
)
print_verbose("")
def run_quickrun_wasmscore():
"""SimdScore test: Benchmarks scalar and simd version of select benchmarks and
reports a Wasm's scalar and simd performance score based on a geo-mean of
the performances of the benchmarks. The test also reports a Wasm simd efficiency
score calculated using Wasm's simd speed-up relative to native."""
logging.info("Running QuickRun-WasmScore ...")
global DEFAULT_BENCH_PROCESS_NUM
DEFAULT_BENCH_PROCESS_NUM = 1
run_wasmscore()
def run_quickrun_simdscore():
"""SimdScore test: Benchmarks scalar and simd version of select benchmarks and
reports a Wasm's scalar and simd performance score based on a geo-mean of
the performances of the benchmarks. The test also reports a Wasm simd efficiency
score calculated using Wasm's simd speed-up relative to native."""
logging.info("Running QuickRun-SimdScore ...")
global DEFAULT_BENCH_PROCESS_NUM
DEFAULT_BENCH_PROCESS_NUM = 1
run_simdscore()
def run_quickrun_all():
"""SimdScore test: Benchmarks scalar and simd version of select benchmarks and
reports a Wasm's scalar and simd performance score based on a geo-mean of
the performances of the benchmarks. The test also reports a Wasm simd efficiency
score calculated using Wasm's simd speed-up relative to native."""
logging.info("Running QuickRun-All ...")
global DEFAULT_BENCH_PROCESS_NUM
DEFAULT_BENCH_PROCESS_NUM = 1
for bench in sg_benchmarks_native.keys():
run_benchmarks(bench, True)
for bench in sg_benchmarks_wasm.keys():
if bench not in sg_benchmarks_native:
run_benchmarks(bench, False)
def print_verbose(string):
"""Print verbose score details"""
if not ARGS_DICT["quiet"]:
print(string)
def check_version():
"""Check the version of the sightglass-cli"""
build_version = subprocess.check_output(
"grep 'IMAGE_VERSION' config.inc | cut -d '\"' -f 2 ",
shell=True,
text=True,
stderr=subprocess.STDOUT,
).strip()
print(f"Version: {build_version}")
build_sha = subprocess.check_output(
"grep 'IMAGE_VERSION' config.inc | cut -d '\"' -f 2 | cut -c 2- | cut -d '.' -f 4",
shell=True,
text=True,
stderr=subprocess.STDOUT,
).strip()
print_order = subprocess.check_output(
"find . -type f -name '*.wasm' | sort -d | xargs -I{} sha1sum add_time_metric.diff build.sh requirements.txt Dockerfile wasmscore.py {}",
shell=True,
text=True,
stderr=subprocess.STDOUT,
).strip()
#print(f"Sha Order:\n{print_order}")
calculated_build_sha = subprocess.check_output(
"find . -type f -name '*.wasm' | sort -d | xargs -I{} sha1sum add_time_metric.diff build.sh requirements.txt Dockerfile wasmscore.py {} | sha1sum | cut -c 1-7 | awk '{print $1}'",
shell=True,
text=True,
stderr=subprocess.STDOUT,
).strip()
if (build_sha == calculated_build_sha):
print(f"Build sha: {build_sha} vs {calculated_build_sha} (calculated) (run is valid)")
else:
print(f"Build SHA: {build_sha} vs {calculated_build_sha} (calculated) (run is invalid)")
return (build_sha == calculated_build_sha)
def main():
"""Top level entry"""
print_verbose("")
print_verbose("WasmScore")
check_version()
if ARGS_DICT["version"]:
print("")
return
if ARGS_DICT["list"]:
print("")
print("Tests\n------")
print(yaml.dump(perf_tests, sort_keys=True, default_flow_style=False))
print("Suites\n------")
print(yaml.dump(perf_suites, sort_keys=True, default_flow_style=False))
return
if ARGS_DICT["benchmarks"]:
for benchmark in ARGS_DICT["benchmarks"]:
if benchmark in sg_benchmarks_wasm:
if ARGS_DICT["native"]:
run_benchmarks(benchmark, True)
else:
run_benchmarks(benchmark)
else:
print(f"Benchmark {benchmark} is not valid")
elif ARGS_DICT["suites"]:
for suite in ARGS_DICT["suites"]:
if suite in perf_suites:
if ARGS_DICT["native"]:
run_suites(suite, True)
else:
run_suites(suite)
else:
print(f"Suite {suite} is not valid")
elif ARGS_DICT["tests"]:
for test in ARGS_DICT["tests"]:
if test.lower() == "wasmscore":
run_wasmscore()
elif test.lower() == "simdscore":
run_simdscore()
elif test.lower() == "quickrun_wasmscore":
run_quickrun_wasmscore()
elif test.lower() == "quickrun_simdscore":
run_quickrun_simdscore()
elif test.lower() == "quickrun_all":
run_quickrun_all()
else:
print(f"Test {test} is not valid")
else:
run_quickrun_wasmscore()
if ARGS_DICT["dump"]:
if isinstance(SUITE_DF, pd.DataFrame):
print("")
print(SUITE_DF.to_string(index=False))
print("")
elif isinstance(BENCHMARK_DF, pd.DataFrame):
print("")
print(BENCHMARK_DF.to_string(index=False))
print("")
if ARGS_DICT["dumpfile"]:
if isinstance(SUITE_DF, pd.DataFrame):
SUITE_DF.to_csv(ARGS_DICT["dumpfile"], sep=",", index=False)
elif isinstance(BENCHMARK_DF, pd.DataFrame):