Ridgeline: A 2D Roofline Model for Distributed Systems
Fuente:
arXiv
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Preprint |
| Published: |
2022
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866918204243181568 |
|---|---|
| author | Checconi, Fabio Tithi, Jesmin Jahan Petrini, Fabrizio |
| author_facet | Checconi, Fabio Tithi, Jesmin Jahan Petrini, Fabrizio |
| contents | In this short paper, we introduce the Ridgeline model, an extension of the Roofline model [4] for distributed systems. The Roofline model targets shared memory systems, bounding the performance of a kernel based on its operational intensity, and the peak compute throughput and memory bandwidth of the execution system. In a distributed setting, with multiple communicating compute entities, the network must be taken into account to model the system behavior accurately. The Ridgeline aggregates information on compute, memory, and network limits in one 2D plot to show, in an intuitive way, which of the resources is the expected bottleneck. We show the applicability of the Ridgeline in a case study based on a data-parallel Multi-Layer Perceptron (MLP) instance. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2209_01368 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Ridgeline: A 2D Roofline Model for Distributed Systems Checconi, Fabio Tithi, Jesmin Jahan Petrini, Fabrizio Distributed, Parallel, and Cluster Computing Performance In this short paper, we introduce the Ridgeline model, an extension of the Roofline model [4] for distributed systems. The Roofline model targets shared memory systems, bounding the performance of a kernel based on its operational intensity, and the peak compute throughput and memory bandwidth of the execution system. In a distributed setting, with multiple communicating compute entities, the network must be taken into account to model the system behavior accurately. The Ridgeline aggregates information on compute, memory, and network limits in one 2D plot to show, in an intuitive way, which of the resources is the expected bottleneck. We show the applicability of the Ridgeline in a case study based on a data-parallel Multi-Layer Perceptron (MLP) instance. |
| title | Ridgeline: A 2D Roofline Model for Distributed Systems |
| topic | Distributed, Parallel, and Cluster Computing Performance |
| url | https://arxiv.org/abs/2209.01368 |