pronesto commented on PR #16499:
URL: https://github.com/apache/tvm/pull/16499#issuecomment-1957660228

   Hi! I'd like to share some updates on the experiments conducted for this 
pull request. We've included the performance data for an RTX3080 in addition to 
the existing dataset in our 
[report](https://homepages.dcc.ufmg.br/~michaelcanesche/paper/bennu_paper.pdf). 
The report now uses four hardware configurations: AMD x86-64 R7, ARM aarch64 
A64FX, Nvidia A100, and Nvidia RTX3080. Across all these scenarios, reducing 
the number of trials for Ansor while using Droplet Search to exploit the best 
results tends to outperforms Ansor with 10,000 trials per model, considering 
both search time and model quality.
   
   We've also conducted a study on the impact of the model size on the 
combination of Ansor and AutoTVM's Droplet Search. That's Section 3.3 of the 
manuscript. Here are our conclusions:
   
   1. The larger the model, the fewer samples the combined approach needs to 
observe to outperform Ansor (in terms of the speed of the final model), when 
Ansor uses a budget of 10,000 samples.
   2. The larger the model, the less significant the benefit in terms of search 
time for the combined approach over Ansor, although there is still improvement.


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