canesche opened a new pull request, #16499: URL: https://github.com/apache/tvm/pull/16499
## Description This pull request aims to enhance model optimization by combining parts of Ansor and AutoTVM. The proposed approach involves the following steps: 1. Execution of Ansor over an end-to-end model that requires optimization. 2. Selection of the best implementation identified by Ansor for the given model. 3. Utilization of AutoTVM's Droplet Search to exploit the selected candidate. By integrating Ansor with AutoTVM's Droplet Search ([droplet paper](https://homepages.dcc.ufmg.br/~fernando/publications/papers/DropletSearch.pdf)), we anticipate a reduction in the number of trials explored by Ansor while still achieving faster kernel performance. Our experimentation has demonstrated significant improvements in kernel speed with reduced search times across various architectures, including Nvidia A100, Nvidia 3080, AMD x86, and ARM A64FX. The results can be found in this report: [bennu paper](https://homepages.dcc.ufmg.br/~michaelcanesche/paper/bennu_paper.pdf) ## Proposed Changes - Integration of Ansor and Droplet Search methodologies. - Utilization of Droplet Search to exploit the best candidates identified by Ansor. ## Motivation The motivation behind this pull request is to streamline the model optimization process by leveraging the complementary strengths of Ansor and Droplet Search. By combining these techniques, we aim to enhance the efficiency and effectiveness of kernel search and optimization, ultimately improving overall model performance across different hardware architectures. ## Testing and Validation Extensive testing has been conducted to validate the efficacy and performance improvements achieved through the integration of Ansor and Droplet Search. Benchmarking tests have been performed across Nvidia A100, AMD x86, and ARM A64FX architectures to assess the impact on kernel speed and search time reduction compared with 10,000 trials from Ansor execution. These results are available in Section 3 of this manuscript: [bennu paper](https://homepages.dcc.ufmg.br/~michaelcanesche/paper/bennu_paper.pdf) ## Additional Notes This pull request builds upon prior research and experimentation in model optimization. The proposed approach improves end-to-end models across diverse hardware platforms while still reducing Ansor's search time. We welcome the community’s feedback, suggestions, and contributions to further refine and enhance these methodologies. Thank you. Sincerely, Michael Canesche, Gaurav Verma, and Fernando Pereira -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
