3 citations · 10 across the 18 of their papers we have counts for
13 papers · 1 filter
ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation
Erel Kaplan, Tomer Bitan, Lian Ghrayeb +4
Parallel programming is central to HPC and AI, but producing code that is correct and fast remains challenging, especially for OpenMP GPU offload, where data movement and tuning do…
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…
UniPar: A Unified LLM-Based Framework for Parallel and Accelerated Code Translation in HPC
Tomer Bitan, Tal Kadosh, Erel Kaplan +5
Translating programs between various parallel programming languages is an important problem in the high-performance computing (HPC) community. Existing tools for this problem are e…
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…
ScalSALE: Scalable SALE Benchmark Framework for Supercomputers
Re'em Harel, Matan Rusanovsky, Ron Wagner +2
Supercomputers worldwide provide the necessary infrastructure for groundbreaking research. However, most supercomputers are not designed equally due to different desired figure of…
Assessing the Use Cases of Persistent Memory in High-Performance Scientific Computing
Yehonatan Fridman, Yaniv Snir, Matan Rusanovsky +5
As the High Performance Computing world moves towards the Exa-Scale era, huge amounts of data should be analyzed, manipulated and stored. In the traditional storage/memory hierarch…