collaborators

12 papers

cs.AR2026

HLSmith: An Expert-Guided Agentic Framework for C/C++-to-HLS Translation

Yuebo Luo, Ahmad Sedigh Baroughi, Philip Stachura +4

Application-specific FPGA accelerators offer substantial performance and energy-efficiency gains across many application domains, but developing them is costly, often requiring mon…

cs.AI2026

ParBench: A Benchmark for Reliable Evaluation of LLM Parallel Code Translation

Samyak Jhaveri, Erel Kaplan, Tom Yotam +4

Modern compute-intensive software must migrate across a changing ecosystem of accelerators, programming APIs, compiler stacks, and portability layers, including CUDA, OpenMP, OpenC…

cs.DC2026

Latent Reasoning Guidance for Parallel Code Translation

Tomer Bitan, Erel Kaplan, Roee Bar-Yadin +5

Tackling complex coding tasks often requires autonomous agents and iterative repair pipelines. These increasingly rely on large amounts of test-time computation, often spending man…

cs.PL2026

Beyond Code Pairs: Dialogue-Based Data Generation for LLM Code Translation

Le Chen, Nuo Xu, Winson Chen +7

Large language models (LLMs) have shown remarkable capabilities in code translation, yet their performance deteriorates in low-resource programming domains such as Fortran and emer…

cs.AI2026

An Agentic Evaluation Framework for AI-Generated Scientific Code in PETSc

Hong Zhang, Barry Smith, Satish Balay +4

While large language models have significantly accelerated scientific code generation, comprehensively evaluating the generated code remains a major challenge. Traditional benchmar…

cs.DC2026

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…