5 papers
CelloAI Benchmarks: Toward Repeatable Evaluation of AI Assistants
Mohammad Atif, Kriti Chopra, Fang-Ying Tsai +8
Large Language Models (LLM) are increasingly used for software development, yet existing benchmarks for LLM-based coding assistance do not reflect the constraints of High Energy Ph…
Evaluating Application Characteristics for GPU Portability Layer Selection
Mohammad Atif, Meghna Bhattacharya, Mark Dewing +12
GPUs have become the dominant source of computing power for high performance computing and are increasingly being used across the High Energy Physics computing landscape for a wide…
CelloAI: Leveraging Large Language Models for HPC Software Development in High Energy Physics
Mohammad Atif, Kriti Chopra, Ozgur Kilic +6
Next-generation High Energy Physics (HEP) experiments will generate unprecedented data volumes, necessitating High Performance Computing (HPC) integration alongside traditional hig…
A Microbenchmark Framework for Performance Evaluation of OpenMP Target Offloading
Mohammad Atif, Tianle Wang, Zhihua Dong +2
We present a framework based on Catch2 to evaluate performance of OpenMP's target offload model via micro-benchmarks. The compilers supporting OpenMP's target offload model for het…
Empirical Measurements of AI Training Power Demand on a GPU-Accelerated Node
Imran Latif, Alex C. Newkirk, Matthew R. Carbone +5
The expansion of artificial intelligence (AI) applications has driven substantial investment in computational infrastructure, especially by cloud computing providers. Quantifying t…