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20212026
most citedLeveraging AI for Productive and Trustworthy HPC Software: Challenges and Research Directions

2 citations · 5 across the 13 of their papers we have counts for

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8 papers · 1 filter

cs.DC2026

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…

cs.DC2025

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…

cs.DC2025

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…

cs.DC2025

Can Large Language Models Predict Parallel Code Performance?

Gregory Bolet, Giorgis Georgakoudis, Harshitha Menon +5

Accurate determination of the performance of parallel GPU code typically requires execution-time profiling on target hardware -- an increasingly prohibitive step due to limited acc…

cs.DC2024

HPAC-ML: A Programming Model for Embedding ML Surrogates in Scientific Applications

Zane Fink, Konstantinos Parasyris, Praneet Rathi +3

Recent advancements in Machine Learning (ML) have substantially improved its predictive and computational abilities, offering promising opportunities for surrogate modeling in scie…

cs.DC2024★ 1 cited

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…

cs.DC2023

HPAC-Offload: Accelerating HPC Applications with Portable Approximate Computing on the GPU

Zane Fink, Konstantinos Parasyris, Giorgis Georgakoudis +1

The end of Dennard scaling and the slowdown of Moore's law led to a shift in technology trends toward parallel architectures, particularly in HPC systems. To continue providing per…

cs.DC2021

MATCH: An MPI Fault Tolerance Benchmark Suite

Luanzheng Guo, Giorgis Georgakoudis, Konstantinos Parasyris +2

MPI has been ubiquitously deployed in flagship HPC systems aiming to accelerate distributed scientific applications running on tens of hundreds of processes and compute nodes. Main…