• Computer Science > Distributed, Parallel, and Cluster Computing [Submitted on 25 Feb 2026] Title:PASTA: A Modular Program Analysis Tool Framework for Accelerators View PDF HTML (experimental)Abstract:The increasing complexity and diversity of hardware accelerators in modern computing systems demand flexible, low-overhead program analysis tools • We present PASTA, a low-overhead and modular Program AnalysiS Tool Framework for Accelerators • PASTA abstracts over low-level profiling APIs and diverse deep learning frameworks, offering users a unified interface to capture and analyze runtime events at multiple levels • Its extensible design enables researchers and practitioners to rapidly prototype custom tools with minimal overhead • We demonstrate the utility of PASTA by developing several analysis tools, including a deep learning workload characterization tool and a UVM optimization tool • Through extensive evaluation on mainstream deep learning workloads tested on NVIDIA and AMD GPUs under both single- and multi-GPU scenarios, we demonstrate PASTA’s broad applicability

Article Summaries:

  • Computer Science > Distributed, Parallel, and Cluster Computing [Submitted on 25 Feb 2026] Title:PASTA: A Modular Program Analysis Tool Framework for Accelerators View PDF HTML (experimental)Abstract:The increasing complexity and diversity of hardware accelerators in modern computing systems demand flexible, low-overhead program analysis tools. We present PASTA, a low-overhead and modular Program AnalysiS Tool Framework for Accelerators. PASTA abstracts over low-level profiling APIs and diverse deep learning frameworks, offering users a unified interface to capture and analyze runtime events a

Sources: