diff options
Diffstat (limited to 'src/benchmarks/larson.py')
| -rw-r--r-- | src/benchmarks/larson.py | 30 |
1 files changed, 16 insertions, 14 deletions
diff --git a/src/benchmarks/larson.py b/src/benchmarks/larson.py index a5c4a02..642901b 100644 --- a/src/benchmarks/larson.py +++ b/src/benchmarks/larson.py @@ -1,34 +1,36 @@ +"""Definition of the larson benchmark""" + import re from src.benchmark import Benchmark -throughput_re = re.compile("^Throughput =\\s*(?P<throughput>\\d+) operations per second.$") +THROUGHPUT_RE = re.compile("^Throughput =\\s*(?P<throughput>\\d+) operations per second.$") + + +class BenchmarkLarson(Benchmark): + """Larson server benchmark + This benchmark is courtesy of Paul Larson at Microsoft Research. It + simulates a server: each thread allocates and deallocates objects, and then + transfers some objects (randomly selected) to other threads to be freed. + """ -class Benchmark_Larson(Benchmark): def __init__(self): self.name = "larson" - self.descrition = """This benchmark is courtesy of Paul Larson at - Microsoft Research. It simulates a server: each - thread allocates and deallocates objects, and then - transfers some objects (randomly selected) to - other threads to be freed.""" # Parameters taken from the paper "Memory Allocation for Long-Running Server # Applications" from Larson and Krishnan self.cmd = "larson{binary_suffix} 1 8 {maxsize} 1000 50000 1 {threads}" - self.args = { - "maxsize": [64, 512, 1024], - "threads": Benchmark.scale_threads_for_cpus(2) - } + self.args = {"maxsize": [64, 512, 1024], + "threads": Benchmark.scale_threads_for_cpus(2)} self.requirements = ["larson"] super().__init__() def process_output(self, result, stdout, stderr, target, perm, verbose): - for l in stdout.splitlines(): - res = throughput_re.match(l) + for line in stdout.splitlines(): + res = THROUGHPUT_RE.match(line) if res: result["throughput"] = int(res.group("throughput")) return @@ -46,4 +48,4 @@ class Benchmark_Larson(Benchmark): filepostfix="cachemisses") -larson = Benchmark_Larson() +larson = BenchmarkLarson() |