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Creating Code LLMs for HPC: It’s LLMs All the Way Down
DescriptionLarge language models (LLMs) are being used increasingly by software developers, researchers, and students to assist them in coding tasks. While newer LLMs have been improving their coding abilities with regards to serial coding tasks, they consistently perform worse when it comes to parallelism and HPC-related coding tasks. Bridging this gap and creating HPC-capable code LLMs could drastically improve the quality and quantity of code research software developers can write. The current poor performance of LLMs on HPC-related problems can be partially attributed to the lack of significant HPC data in their training, which is what we address in this poster. We present HPC Coder v2, a new LLM created by fine-tuning a previous code LLM using HPC synthetic data. We demonstrate that it is one of the most capable open-source LLMs for generating parallel code to date.
Event Type
ACM Student Research Competition: Graduate Poster
ACM Student Research Competition: Undergraduate Poster
Doctoral Showcase
Posters
TimeTuesday, 19 November 202412pm - 5pm EST
LocationB302-B305
Registration Categories
TP
XO/EX