2 citations · 5 across the 13 of their papers we have counts for
14 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…
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…
Leveraging AI for Productive and Trustworthy HPC Software: Challenges and Research Directions
Keita Teranishi, Harshitha Menon, William F. Godoy +25
We discuss the challenges and propose research directions for using AI to revolutionize the development of high-performance computing (HPC) software. AI technologies, in particular…
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…
Testing the Unknown: A Framework for OpenMP Testing via Random Program Generation
Ignacio Laguna, Patrick Chapman, Konstantinos Parasyris +2
We present a randomized differential testing approach to test OpenMP implementations. In contrast to previous work that manually creates dozens of verification and validation tests…
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…
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…
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…
Machine Learning-Driven Adaptive OpenMP For Portable Performance on Heterogeneous Systems
Giorgis Georgakoudis, Konstantinos Parasyris, Chunhua Liao +3
Heterogeneity has become a mainstream architecture design choice for building High Performance Computing systems. However, heterogeneity poses significant challenges for achieving…
Reliabuild: Searching for High-Fidelity Builds Using Active Learning
Harshitha Menon, Konstantinos Parasyris, Tom Scogland +1
Modern software is incredibly complex. A typical application may comprise hundreds or thousands of reusable components. Automated package managers can help to maintain a consistent…
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…