import multiprocessing

from src.benchmark import Benchmark


class Benchmark_Loop(Benchmark):
    def __init__(self):
        self.name = "loop"
        self.descrition = """This benchmark allocates and frees n blocks in t concurrent
                             threads."""

        self.cmd = "loop{binary_suffix} {nthreads} 1000000 {maxsize}"

        cpus = multiprocessing.cpu_count()
        steps = 1
        if cpus > 20:
            steps = 2
        if cpus > 50:
            steps = 5

        self.args = {"maxsize":  [2 ** x for x in range(6, 16)],
                     "nthreads": range(1, multiprocessing.cpu_count() * 2 + 1, steps)}

        self.requirements = ["loop"]
        super().__init__()

    def summary(self):
        # Speed
        self.plot_fixed_arg("perm.nthreads / (float({task-clock})/1000)",
                            ylabel='"MOPS/cpu-second"',
                            title='"Loop: " + arg + " " + str(arg_value)',
                            filepostfix="time")

        # Memusage
        self.plot_fixed_arg("int({VmHWM})",
                            ylabel='"VmHWM in kB"',
                            title='"Loop Memusage: " + arg + " " + str(arg_value)',
                            filepostfix="memusage")

        # L1 cache misses
        self.plot_fixed_arg("({L1-dcache-load-misses}/{L1-dcache-loads})*100",
                            ylabel='"L1 misses in %"',
                            title='"Loop l1 cache misses: " + arg + " " + str(arg_value)',
                            filepostfix="l1misses")

        # Speed Matrix
        self.write_best_doublearg_tex_table("perm.nthreads / (float({task-clock})/1000)",
                                            filepostfix="memusage.matrix")


loop = Benchmark_Loop()