Feb. 15, 2024, 5:43 a.m. | Nadav Schneider, Niranjan Hasabnis, Vy A. Vo, Tal Kadosh, Neva Krien, Mihai Capot\u{a}, Abdul Wasay, Guy Tamir, Ted Willke, Nesreen Ahmed, Yuval Pinte

cs.LG updates on arXiv.org arxiv.org

arXiv:2402.09126v1 Announce Type: cross
Abstract: The imperative need to scale computation across numerous nodes highlights the significance of efficient parallel computing, particularly in the realm of Message Passing Interface (MPI) integration. The challenging parallel programming task of generating MPI-based parallel programs has remained unexplored. This study first investigates the performance of state-of-the-art language models in generating MPI-based parallel programs. Findings reveal that widely used models such as GPT-3.5 and PolyCoder (specialized multi-lingual code models) exhibit notable performance degradation, when generating …

arxiv code code generation cs.ai cs.cl cs.dc cs.lg cs.se domain language language models mpi through type

Software Engineer for AI Training Data (School Specific)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Python)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Tier 2)

@ G2i Inc | Remote

Data Engineer

@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania

Artificial Intelligence – Bioinformatic Expert

@ University of Texas Medical Branch | Galveston, TX

Lead Developer (AI)

@ Cere Network | San Francisco, US