# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import subprocess
import sys
from concurrent.futures import as_completed
from pathlib import Path
from typing import Optional
from compiler_gym.datasets import Benchmark, TarDatasetWithManifest
from compiler_gym.datasets.benchmark import BenchmarkWithSource
from compiler_gym.datasets.uri import BenchmarkUri
from compiler_gym.envs.llvm.llvm_benchmark import ClangInvocation
from compiler_gym.util import thread_pool
from compiler_gym.util.filesystem import atomic_file_write
[docs]class AnghaBenchDataset(TarDatasetWithManifest):
"""A dataset of C programs curated from GitHub source code.
The dataset is from:
da Silva, Anderson Faustino, Bruno Conde Kind, José Wesley de Souza
Magalhaes, Jerônimo Nunes Rocha, Breno Campos Ferreira Guimaraes, and
Fernando Magno Quinão Pereira. "ANGHABENCH: A Suite with One Million
Compilable C Benchmarks for Code-Size Reduction." In 2021 IEEE/ACM
International Symposium on Code Generation and Optimization (CGO),
pp. 378-390. IEEE, 2021.
And is available at:
http://cuda.dcc.ufmg.br/angha/home
Installation
------------
The AnghaBench dataset consists of C functions that are compiled to LLVM-IR
on-demand and cached. The first time each benchmark is used there is an
overhead of compiling it from C to bitcode. This is a one-off cost.
"""
def __init__(
self,
site_data_base: Path,
sort_order: int = 0,
manifest_url: Optional[str] = None,
manifest_sha256: Optional[str] = None,
deprecated: Optional[str] = None,
name: Optional[str] = None,
):
manifest_url_, manifest_sha256_ = {
"darwin": (
"https://dl.fbaipublicfiles.com/compiler_gym/llvm_bitcodes-10.0.0-anghabench-v1-macos-manifest.bz2",
"96ead63da5f8efa07fd0370f0c6e452b59bed840828b8b19402102b1ce3ee109",
),
"linux": (
"https://dl.fbaipublicfiles.com/compiler_gym/llvm_bitcodes-10.0.0-anghabench-v1-linux-manifest.bz2",
"14df85f650199498cf769715e9f0d7841d09f9fa62a95b8ecc242bdaf227f33a",
),
}[sys.platform]
super().__init__(
name=name or "benchmark://anghabench-v1",
description="Compile-only C/C++ functions extracted from GitHub",
references={
"Paper": "https://homepages.dcc.ufmg.br/~fernando/publications/papers/FaustinoCGO21.pdf",
"Homepage": "http://cuda.dcc.ufmg.br/angha/",
},
license="Unknown. See: https://github.com/brenocfg/AnghaBench/issues/1",
site_data_base=site_data_base,
manifest_urls=[manifest_url or manifest_url_],
manifest_sha256=manifest_sha256 or manifest_sha256_,
tar_urls=[
"https://github.com/brenocfg/AnghaBench/archive/d8034ac8562b8c978376008f4b33df01b8887b19.tar.gz"
],
tar_sha256="85d068e4ce44f2581e3355ee7a8f3ccb92568e9f5bd338bc3a918566f3aff42f",
strip_prefix="AnghaBench-d8034ac8562b8c978376008f4b33df01b8887b19",
tar_compression="gz",
benchmark_file_suffix=".bc",
sort_order=sort_order,
deprecated=deprecated,
)
def benchmark_from_parsed_uri(self, uri: BenchmarkUri) -> Benchmark:
self.install()
benchmark_name = uri.path[1:]
if not benchmark_name:
raise LookupError(f"No benchmark specified: {uri}")
# The absolute path of the file, without an extension.
path_stem = self.dataset_root / benchmark_name
bitcode_abspath = Path(f"{path_stem}.bc")
c_file_abspath = Path(f"{path_stem}.c")
# If the file does not exist, compile it on-demand.
if not bitcode_abspath.is_file():
if not c_file_abspath.is_file():
raise LookupError(
f"Benchmark not found: {uri} (file not found: {c_file_abspath})"
)
with atomic_file_write(bitcode_abspath) as tmp_path:
compile_cmd = ClangInvocation.from_c_file(
c_file_abspath,
copt=[
"-ferror-limit=1", # Stop on first error.
"-w", # No warnings.
],
).command(outpath=tmp_path)
subprocess.check_call(compile_cmd, timeout=300)
return BenchmarkWithSource.create(
uri, bitcode_abspath, "function.c", c_file_abspath
)
def compile_all(self):
n = self.size
executor = thread_pool.get_thread_pool_executor()
# Since the dataset is lazily compiled, simply iterating over the full
# set of URIs will compile everything. Do this in parallel.
futures = (
executor.submit(self.benchmark, uri) for uri in self.benchmark_uris()
)
for i, future in enumerate(as_completed(futures), start=1):
future.result()
print(
f"\r\033[KCompiled {i} of {n} programs ({i/n:.1%} complete)",
flush=True,
end="",
)