Enabling Heterogeneous Performance Analysis for Scientific Workloads
Fuente:
arXiv
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866911271565131776 |
|---|---|
| author | Graczyk, Maksymilian Desbiolles, Vincent Roiser, Stefan Guerrieri, Andrea |
| author_facet | Graczyk, Maksymilian Desbiolles, Vincent Roiser, Stefan Guerrieri, Andrea |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_13928 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Enabling Heterogeneous Performance Analysis for Scientific Workloads Graczyk, Maksymilian Desbiolles, Vincent Roiser, Stefan Guerrieri, Andrea Performance 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. |
| title | Enabling Heterogeneous Performance Analysis for Scientific Workloads |
| topic | Performance |
| url | https://arxiv.org/abs/2511.13928 |