Towards a Strategy for Performance Prediction on Heterogeneous Architectures
| Autor: | Júlio Amaral, Rogerio Iope, Silvio Luiz Stanzani, Marco Gomes, Jefferson Fialho, Raphael Cóbe, Artur Baruchi |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
020203 distributed computing
Parallel processing (DSP implementation) Homogeneous Order (exchange) Computer science Distributed computing Rank (computer programming) 0202 electrical engineering electronic engineering information engineering Performance prediction Overhead (computing) 020207 software engineering 02 engineering and technology Architecture |
| Zdroj: | High Performance Computing for Computational Science – VECPAR 2018 ISBN: 9783030159955 VECPAR |
| DOI: | 10.1007/978-3-030-15996-2_18 |
| Popis: | Performance prediction of applications has always been a great challenge, even for homogeneous architectures. However, today’s trend is the design of cluster running in a heterogeneous architecture, which increases the complexity of new strategies to predict the behavior and time spent by an application to run. In this paper we present a strategy that predicts the performance of an application on different architectures and rank then according to the performance that the application can achieve on each architecture. The proposed strategy was able to correctly rank three of four applications tested without overhead implications. Our next step is to extend the metrics in order to increase the accuracy. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|