Abstract
An accurate performance predictor to identify the most suitable core-architecture to execute each thread/workload in a heterogeneous many-core structure is proposed. The devised predictor is based on a linear regression model that considers several different parameters of the many-core processor architectures, including the cache size, issue-width, re-order buffer size, load/store queues size, etc. The devised predictor is easily integrated in most system schedulers, providing the ability to periodically determine whether a certain thread is running in the most efficient core-architecture. The obtained experimental results show that the devised model is able to identify the correct core-architecture in a large majority of the cases, leading to average performance differences as low as 7% when compared with an oracle scheduling solution.
This work was partially supported by national funds through Fundação para a Ciência e a Tecnologia (FCT), under project UID/CEC/50021/2013.
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Pinheiro, R., Roma, N., Tomás, P. (2017). A Cross-Core Performance Model for Heterogeneous Many-Core Architectures. In: Dutra, I., Camacho, R., Barbosa, J., Marques, O. (eds) High Performance Computing for Computational Science – VECPAR 2016. VECPAR 2016. Lecture Notes in Computer Science(), vol 10150. Springer, Cham. https://doi.org/10.1007/978-3-319-61982-8_11
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