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[llvm_instcount] Leaderboard Submission: GATv2 with DD-PPO #728
[llvm_instcount] Leaderboard Submission: GATv2 with DD-PPO #728
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Codecov Report
@@ Coverage Diff @@
## development #728 +/- ##
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+ Coverage 88.67% 88.73% +0.06%
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Files 131 131
Lines 7936 7936
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+ Hits 7037 7042 +5
+ Misses 899 894 -5
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Hi @anthony0727, fantastic! Great to see a GNN-backed RL implementation. Couple of things:
Also, be sure to add an entry to the main README.md with your entry! BTW, the vocab file that I think you are looking for can be found here: https://zenodo.org/record/4247595 Cheers, |
Hey @ChrisCummins, resovled two bullets you told me! BTW, Thanks! |
triple check for trailing whitespace
Hi Anthony, Thanks for the fixes 🙂
Yes, just send us a PR when you have the new results to update your position on the leaderboard. One small comment about changing the walltime reported for greedy search. Other than, LGTM! Cheers, |
This adds entrypoint for model learnt from Programl observations.
Programl encoded with graph neural network, and align tasks in as much parallelism as possible to remove temporal correlation(just like replay buffer from Deep-Q Network). The model is optimized with PPOv2 loss.
The datasets used to train are ['cbench-v1', 'mibench-v1', 'blas-v0', 'npb-v0'] with limited node/edge counts(due to our shortage of resouce).
Anticipating better result with additional experiments(this has been halted from our internal server maintanance, and will be resumed when done).