请选择 进入手机版 | 继续访问电脑版
 猿代码 — 科研/AI模型/高性能计算
0

优化效果明显,加速约1倍

摘要: 1)原始迭代时间it=3100, real error=0.043594, matrix error=0.000051it=3200, real error=0.038782, matrix error=0.000045it=3300, real error=0.034502, matrix error=0.000040it=3400, real error=0.030694, mat ...

1)
原始迭代时间


it=3100, real error=0.043594, matrix error=0.000051
it=3200, real error=0.038782, matrix error=0.000045
it=3300, real error=0.034502, matrix error=0.000040
it=3400, real error=0.030694, matrix error=0.000036
it=3500, real error=0.027307, matrix error=0.000032
it=3600, real error=0.024294, matrix error=0.000028
it=3700, real error=0.021614, matrix error=0.000025
it=3800, real error=0.019229, matrix error=0.000022
it=3900, real error=0.017107, matrix error=0.000020
it=4000, real error=0.015220, matrix error=0.000018
it=4100, real error=0.013541, matrix error=0.000016
it=4200, real error=0.012047, matrix error=0.000014
it=4300, real error=0.010718, matrix error=0.000013
it=4360, error=0.009993, 0.000012
converged ok!
Time: 119.867s   global max error = 0.009993

2)
优化后的迭代时间

init ok!
it= 100, real error=0.654022, matrix error=2.893340
it= 200, real error=0.260950, matrix error=2.893453
it= 300, real error=0.102420, matrix error=2.893476
it= 400, real error=0.040222, matrix error=2.893483
it= 500, real error=0.015807, matrix error=2.893486
it=2196, error=0.010000, 2.893486
converged ok!
Time: 51.1045s   global max error = 0.009953


说点什么...

已有0条评论

最新评论...

本文作者
2024-2-23 01:09
  • 0
    粉丝
  • 122
    阅读
  • 0
    回复
资讯幻灯片
热门评论
热门专题
排行榜
Copyright   ©2015-2023   猿代码-超算人才智造局 高性能计算|并行计算|人工智能      ( 京ICP备2021026424号-2 )