6 papers · 1 filter
Record-Remix-Replay: Hierarchical GPU Kernel Optimization using Evolutionary Search
Daniel Nichols, Konstantinos Parasyris, Caetano Melone +3
As high-performance computing and AI workloads become increasingly dependent on GPUs, maintaining high performance across rapidly evolving hardware generations has become a major c…
Integrating Performance Tools in Model Reasoning for GPU Kernel Optimization
Daniel Nichols, Konstantinos Parasyris, Charles Jekel +2
Language models are now prevalent in software engineering with many developers using them to automate tasks and accelerate their development. While language models have been tremen…
ParEval-Repo: A Benchmark Suite for Evaluating LLMs with Repository-level HPC Translation Tasks
Joshua H. Davis, Daniel Nichols, Ishan Khillan +1
GPGPU architectures have become significantly more diverse in recent years, which has led to an emergence of a variety of specialized programming models and software stacks to supp…
HPC-Coder-V2: Studying Code LLMs Across Low-Resource Parallel Languages
Aman Chaturvedi, Daniel Nichols, Siddharth Singh +1
Large Language Model (LLM) based coding tools have been tremendously successful as software development assistants, yet they are often designed for general purpose programming task…
Can Large Language Models Write Parallel Code?
Daniel Nichols, Joshua H. Davis, Zhaojun Xie +2
Large language models are increasingly becoming a popular tool for software development. Their ability to model and generate source code has been demonstrated in a variety of conte…
Performance-Aligned LLMs for Generating Fast Code
Daniel Nichols, Pranav Polasam, Harshitha Menon +3
Optimizing scientific software is a difficult task because codebases are often large and complex, and performance can depend upon several factors including the algorithm, its imple…