ciyongch commented on issue #15429: Operator Performance Regression on CPU
URL: 
https://github.com/apache/incubator-mxnet/issues/15429#issuecomment-508095935
 
 
   @roywei I looked at the table, except a few ops with big variances, most of 
the degraded ops listed in the table dropped into **mshadow**. I did some 
further analysis, and found that the performance regression is caused by the 
commit of `6e94643` (https://github.com/dmlc/mshadow/pull/371), which changed 
the data type for `index_t`. Seems the quick fix in that PR didn't work for 
these ops, and a better solution is required for the type changing.
   
   Here's some perf data collected on my local machine (SKX-8180), you can have 
a try on your platform :)
   
   | Operator    | Avg Forward Time (ms) 1.4.1 | Avg Forward Time (ms) 1.5.0 | 
Regression | Avg Forward Time (ms) 1.5.0 (revert 6e94643) | Updated Regression 
| data shape           |
   
|-------------|-----------------------------|-----------------------------|------------|----------------------------------------------|------------|----------------------|
   | relu        | 0.0047                      | 0.0107                      | 
127.7%     | 0.0057                                       | 21.3%      | 
{'data': (10000, 1)} |
   | relu        | 0.0065                      | 0.0143                      | 
120.0%     | 0.005                                        | -23.1%     | 
{'data': (10000, 1)} |
   | relu        | 0.005                       | 0.0144                      | 
188.0%     | 0.0051                                       | 2.0%       | 
{'data': (10000, 1)} |
   | relu        | 0.0052                      | 0.0115                      | 
121.2%     | 0.0066                                       | 26.9%      | 
{'data': (10000, 1)} |
   | relu        | 0.005                       | 0.0138                      | 
176.0%     | 0.0061                                       | 22.0%      | 
{'data': (10000, 1)} |
   | logical_not | 0.005                       | 0.0221                      | 
342.0%     | 0.0057                                       | 14.0%      | 
{'data': (10000, 1)} |
   | logical_not | 0.0051                      | 0.0214                      | 
319.6%     | 0.0056                                       | 9.8%       | 
{'data': (10000, 1)} |
   | logical_not | 0.0054                      | 0.0215                      | 
298.1%     | 0.0056                                       | 3.7%       | 
{'data': (10000, 1)} |
   | logical_not | 0.0051                      | 0.0214                      | 
319.6%     | 0.0057                                       | 11.8%      | 
{'data': (10000, 1)} |
   | logical_not | 0.0051                      | 0.0216                      | 
323.5%     | 0.0056                                       | 9.8%       | 
{'data': (10000, 1)} |
   | softsign    | 0.0054                      | 0.0166                      | 
207.4%     | 0.0059                                       | 9.3%       | 
{'data': (10000, 1)} |
   | softsign    | 0.0053                      | 0.0166                      | 
213.2%     | 0.006                                        | 13.2%      | 
{'data': (10000, 1)} |
   | softsign    | 0.0058                      | 0.0163                      | 
181.0%     | 0.006                                        | 3.4%       | 
{'data': (10000, 1)} |
   | softsign    | 0.0053                      | 0.0162                      | 
205.7%     | 0.006                                        | 13.2%      | 
{'data': (10000, 1)} |
   | softsign    | 0.0054                      | 0.0164                      | 
203.7%     | 0.0062                                       | 14.8%      | 
{'data': (10000, 1)} |
   

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