8 papers
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…
Counting Without Running: Evaluating LLMs' Reasoning About Code Complexity
Gregory Bolet, Giorgis Georgakoudis, Konstantinos Parasyris +4
Modern GPU software stacks demand developers who can anticipate performance bottlenecks before ever launching a kernel; misjudging floating-point workloads upstream can derail tuni…
LLMs as Packagers of HPC Software
Caetano Melone, Daniel Nichols, Konstantinos Parasyris +2
High performance computing (HPC) software ecosystems are inherently heterogeneous, comprising scientific applications that depend on hundreds of external packages, each with distin…
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…
Taking GPU Programming Models to Task for Performance Portability
Joshua H. Davis, Pranav Sivaraman, Joy Kitson +5
Portability is critical to ensuring high productivity in developing and maintaining scientific software as the diversity in on-node hardware architectures increases. While several…
Modeling Code: Is Text All You Need?
Daniel Nichols, Konstantinos Parasyris, Harshitha Menon +4
Code LLMs have become extremely popular recently for modeling source code across a variety of tasks, such as generation, translation, and summarization. However, transformer-based…