Пример #1
0
def print_pt(pt):
    print(pt[1]),
    print "\t\t\t",
    (navg, nstddev) = pt[2]
    print(
        human_readable.percent(navg) + "%\t\t\t" +
        human_readable.percent(nstddev) + "%\t\t\t" +
        human_readable.speedup(pt[3]) + "\t\t\t" +
        human_readable.speedup(pt[4]))
Пример #2
0
def print_compare_normalized(experiment_id, n_procs):
    problem_name = get.problem_name_of_experiment(experiment_id)
    print("Problem: " + problem_name)
    print("Number of Cores: " + str(n_procs))
    ((binput, bps, bspeedup, mltspeedup, mltlbsovhd, seqpmlcvsmlton, berror,
      lbs_ovhd, (bavg, bstddev)),
     norms) = compare_normalized(experiment_id, n_procs)
    print("Best splitting strategy: " + bps + " (Error= " +
          human_readable.percent(berror) + "%) (Speedup vs. SeqPMLC= " +
          human_readable.speedup(bspeedup) + ") (Speedup vs. mlton= " +
          human_readable.speedup(mltspeedup) + ")")
    print("Overhead of LBS vs. NS (PMLC)= " +
          human_readable.percent(lbs_ovhd)) + '%'
    print("Overhead of LBS vs. NS (mlton)= " +
          human_readable.percent(mltlbsovhd)) + '%'
    print("Sequential PMLC vs. mlton (both NS)= " +
          human_readable.percent(seqpmlcvsmlton) + "%")
    print(
        "Splitting strategy\t\tPct. slower\t\tError\t\t\tSpeedup vs. SeqPMLC\tSpeedup vs. mlton"
    )
    for norm in norms:
        print_pt(norm)
Пример #3
0
# Adam Shaw, November 2009
# run this with 'python speedup.py'

# Please see EDIT ME! below for customization.

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.font_manager as fm
import utils
import rope_splitting_experiment as r
import collect_data as get
import human_readable as h
import speedups as spds

for experiment_id in spds.ids:
    (maxtime, bl_avg, mlt_avg, mltlbsovhd, lbs_ovhd,
     norms) = r.compare_wall_clock(experiment_id, 48)
    problem_name = get.problem_name_of_experiment(experiment_id)
    problem_name = r.pretty_bench_name(problem_name)
    (input, ps, lbs_avg,
     lbs_std) = filter(lambda (input, ps, avg, err): r.is_lbs1(input),
                       norms)[0]
    lbs_speedup = bl_avg / lbs_avg
    print(problem_name + " & " + h.speedup(mlt_avg, digits=2) + " & " +
          h.speedup(bl_avg, digits=2) + " & " + h.speedup(lbs_ovhd, digits=2) +
          " & " + h.speedup(lbs_avg, digits=2) + " & " +
          h.speedup(lbs_speedup, digits=2) + "\\\\")