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runtest.py
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runtest.py
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'''
Description:
Author: Shengle Lin
Date: 2022-04-23 12:53:36
LastEditors: Shengle Lin
LastEditTime: 2022-09-14 09:50:11
'''
import os
import sys
import numpy as np
# -----------------------------------
# -- 执行程序choltest_nnz --
# -----------------------------------
def runtest( func_name, file_name, option):
cmd1 = 'export OMP_NUM_THREADS=32'
cmd2 = "./%s %s %s" %(func_name, file_name, option)
cmd = cmd1 + "&&" + cmd2
val = os.system(cmd)
def runalldata (file_name):
print('--- Runtest Begin ---')
# file_name = 'sample.txt'
func_name = 'build/test/sparse_choltest_nnz'
total_data = open(file_name)
for line in total_data.readlines():
formLine = line.strip().split(' ')
dataname = formLine[0]
border = float( formLine[1])
GAMMA = np.linspace(-1*border,border,num=5)
# GAMMA = np.linspace(-1*border,border,num=3)
RELAXED = np.linspace(1.05,1.5,num=10)
for gamma in GAMMA:
for relaxed in RELAXED:
option = '%f %f' %(gamma, relaxed)
runtest(func_name, dataname, option)
print('--- Runtest Finished ---')
# 记录最优性能的 alpha, beta 选择
def dataprocess (filename):
print('--- Process Data Begin ---')
Fp = open(filename)
last_line = Fp.readline()
formlastLine = last_line.strip().split('\t')
min_data = [ formlastLine[0], formlastLine[-3], formlastLine[-2], formlastLine[-1]]
final_result=[]
for line in Fp.readlines():
currentLine = line.strip().split('\t')
# 如果是同一个数据集的结果, 才进行比较
if currentLine[0] == min_data[0]:
if float(currentLine[-1]) < float(min_data[-1]): # 这一行的时间更短
min_data[-3] = currentLine[-3]
min_data[-2] = currentLine[-2]
min_data[-1] = currentLine[-1]
else: # 新的数据集开始了，写之后存新的
# 保存当前数据的最小值结果
final_result.append(min_data)
# 写入新的数据集信息
min_data = []
min_data = [ currentLine[0], currentLine[-3], currentLine[-2], currentLine[-1]]
final_result.append(min_data)
dst_data = open('proceed.txt','a+')
for output in final_result:
dst_data.write("{} {} {} {}".format(output[0],output[1],output[2],output[3])+'\n')
print('--- Process Data Finished ---')
# 用于筛选出未完成计算的数据集
def supplement_data(file_all, file_finished):
result = []
Fp_all = open(file_all)
Fp_ready = open(file_finished)
lines_all = Fp_all.readlines()
lines_ready = Fp_ready.readlines()
# result = list (set(lines_all).difference(set(Fp_ready)))
for line_t in lines_all:
if line_t not in lines_ready:
result.append(line_t)
dst = open("supplementdata0516.txt",'a+')
dst.writelines(result)
# for output in result:
# dst.write()
# 原始生成的数据集存在问题，保存了全部的非零元， clean_data 用于生成仅保留三角部分的数据集
def clean_data(file_list):
print('--- Clean Data Begin ---')
File_listp = open(file_list)
for line in File_listp.readlines():
line = line.strip()
file_name = "/home/public/GEN_SYM/" + line +".mtx"
dst_name = "/home/public/GEN_CLEAN/" + line +".mtx"
# 打开原始的数据集
Fp = open(file_name,"r+")
Dstp = open(dst_name,'a+')
# 读写第一行的 banner
bannerline = Fp.readline()
Dstp.write("{}".format(bannerline))
# 读写第二行 head
headLine = Fp.readline().strip().split(' ')
m = int(headLine[0])
n = int(headLine[1])
nnz = int(headLine[2])
file_nnz = int((nnz + m)/2)
print(file_nnz)
Dstp.write("{} {} {}".format(m,n,file_nnz)+'\n')
for dataline in Fp.readlines():
data = dataline.strip().split(' ')
if int(data[0])>= int(data[1]):
Dstp.write("{}".format(dataline))
Dstp.close()
print('--- Clean Data Finish ---')
if __name__ == '__main__':
# clean_data('filelist.txt')
# 脚本， 大规模测试数据集
# runalldata('resdata0516.txt')
# 找每个数据集对应的最优解
# dataprocess('ARMcholesky.txt')
# 找出还未测试的数据集
# supplement_data('allgendata.txt', 'finished_dataset.txt')
# print('--- Runtest begin ---')
# funcname = 'build/test/sparse_choltest'
# 批量进行数据测试
# totalfile = open('dataset.txt')
# for line in totalfile.readlines():
# line = line.strip('\n')
# file_name = '/home/public/DATA_TEST/'+ line +'/'+ line + '.mtx'
# # print(file_name)
# GAMMA = 1.0
# RELAXED = np.linspace(80,100,num=21)
# for relaxed in RELAXED:
# option = '%f %f' %(GAMMA, relaxed)
# runtest(funcname, file_name, option)
# GAMMA = np.linspace(1,1.5,num=11)
# RELAXED = np.linspace(0.8,1.5,num=71)
# 单独数据测试
# filename = '/home/public/DATA_TEST/thermal2/thermal2.mtx'
# GAMMA = np.linspace(1,5,num=51)
# RELAXED = np.linspace(1.0,1.5,num=21)
# for gamma in GAMMA:
# for relaxed in RELAXED:
# option = '%f %f' %(0.363653884, relaxed)
# runtest(funcname, filename, option)
# val = os.system('ls -al')
# print ("val = %d" %(val))