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arXiv · 2511.13928

Enabling Heterogeneous Performance Analysis for Scientific Workloads

Maksymilian Graczyk·Vincent Desbiolles·Stefan Roiser·Andrea Guerrieri
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Abstract

Heterogeneous computing integrates diverse processing elements, such as CPUs, GPUs, and FPGAs, within a single system, aiming to leverage the strengths of each architecture to optimize performance and energy consumption. In this context, efficient performance analysis plays a critical role in determining the most suitable platform for dispatching tasks, ensuring that workloads are allocated to the processing units where they can execute most effectively. Adaptyst is a novel ongoing effort at CERN, with the aim to develop an open-source, architecture-agnostic performance analysis for scientific workloads. This study explores the performance and implementation complexity of two built-in eBPF-based methods such as Uprobes and USDT, with the aim of outlining a roadmap for future integration into Adaptyst and advancing toward heterogeneous performance analysis capabilities.

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Maksymilian Graczyk, Vincent Desbiolles, Stefan Roiser, Andrea Guerrieri. 2025-11-17. Enabling Heterogeneous Performance Analysis for Scientific Workloads. https://arxiv.org/abs/2511.13928

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