import re

from src.benchmark import Benchmark

throughput_re = re.compile("^Throughput =\\s*(?P<throughput>\\d+) operations per second.$")


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.requirements = ["larson"]
        super().__init__()

    def process_output(self, result, stdout, stderr, target, perm, verbose):
        for l in stdout.splitlines():
            res = throughput_re.match(l)
            if res:
                result["throughput"] = int(res.group("throughput"))
                return

    def summary(self):
        # Plot threads->throughput and maxsize->throughput
        self.plot_fixed_arg("{throughput}/1000000",
                            ylabel="'MOPS/s'",
                            title="'Larson: ' + arg + ' ' + str(arg_value)",
                            filepostfix="throughput")

        self.plot_fixed_arg("({L1-dcache-load-misses}/{L1-dcache-loads})*100",
                            ylabel="'l1 cache misses in %'",
                            title="'Larson cache misses: ' + arg + ' ' + str(arg_value)",
                            filepostfix="cachemisses",
                            yerr=False)


larson = Benchmark_Larson()