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【静态图性能优化】Share event by AndSonder · Pull Request #55650 · PaddlePaddle/Paddle · GitHub
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【静态图性能优化】Share event #55650
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【静态图性能优化】Share event #55650
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From00
reviewed
Jul 25, 2023
| // Note(sonder): Share build results don't work for new IR now. | ||
| if (type_to_first_id.count(job_type) != 0 && | ||
| !FLAGS_enable_new_ir_in_executor) { | ||
| interpretercores_[job_idx]->ShareBuildResultsFrom( |
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当type_to_first_id[job_type]==job_idx时，interpretercore自己跟自己share，是否会有问题？
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当
type_to_first_id[job_type]==job_idx时，interpretercore自己跟自己share，是否会有问题？
不会，在ShareBuildResults里有判断
if (is_shared_results_build_ || !src.IsSharedResultsBuild()) {
return;
}
| for (size_t i = 1; i < ids.size(); ++i) { | ||
| interpretercores_[ids[i]]->ShareBuildResultsFrom( | ||
| interpretercores_[ids[0]]); | ||
| if (type_to_first_id.count(jobs[job_idx]->Type()) == 0) { |
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计算type_to_first_id时，是否需要从job_idx=0开始遍历？
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计算
type_to_first_id时，是否需要从job_idx=0开始遍历？
有直接将job_idx=0的job_type加入到 unordered_map 中
type_to_first_id[jobs[0]->Type()] = 0;
for (size_t job_idx = 1; job_idx < jobs.size(); ++job_idx) {
interpretercores_[job_idx]->ShareWorkQueueFrom(interpretercores_[0]);
...
From00
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Jul 26, 2023
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LGTM
wz1qqx
pushed a commit
to wz1qqx/Paddle
that referenced
this pull request
Jul 31, 2023
* add sharing event info * add sharing event info * fix * remove const * add flag * fix
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jinjidejinmuyan
pushed a commit
to jinjidejinmuyan/Paddle
that referenced
this pull request
Aug 30, 2023
* add sharing event info * add sharing event info * fix * remove const * add flag * fix
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PR types
Performance optimization
PR changes
Others
Description
Paddle 的 Event 机制主要用于多流之间的同步，在预分析阶段需要根据
op_func_node去分析相关的信息。对于相同子图的Interpretercore，Event分析的结果可以共享。 本 PR 实现了相同子图Interpretercore之间Event分析信息的共享。详细介绍见Issue：