9 papers
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…
Where Does Texture Evidence Live in SAM? Features, Proposal Masks, and Texture Segmentation
Nadav Orenstein, Aviad Cohen Zada, Shai Avidan +1
Texture segmentation stresses foundation segmentation because meaningful regions are defined by material or repeated appearance rather than object identity. Segment Anything Models…
Sub-Semantic Image Segmentation
Aviad Cohen Zada, Nadav Orenstein, Shai Avidan +1
Images can be segmented based on visual cues (i.e., texture segmentation) or into objects (i.e., semantic segmentation). We propose a new category of sub-semantic image segmentatio…
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…
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…