Gem5-x: a gem5-based system level simulation framework to optimize many-core platforms



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Mahmood Qureshi, Yasir and Simon, William Andrew and Zapater, Marina and Atienza, David and Olcoz Herrero, Katzalin (2019) Gem5-x: a gem5-based system level simulation framework to optimize many-core platforms. In 2019 Spring Simulation Conference (SpringSim). IEEE, Nueva York. ISBN 978-1-5108-8388-8

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The rapid expansion of online-based services requires novel energy and performance efficient architectures to meet power and latency constraints. Fast architectural exploration has become a key enabler in the proposal of architectural innovation. In this paper, we present gem5-X, a gem5-based system level simulation framework, and a methodology to optimize many-core systems for performance and power. As real-life case studies of many-core server workloads, we use real-time video transcoding and image classification using convolutional neural networks (CNNs). Gem5-X allows us to identify bottlenecks and evaluate the potential benefits of architectural extensions such as in-cache computing and 3D stacked High Bandwidth Memory. For real-time video transcoding, we achieve 15% speed-up using in-order cores with in-cache computing when compared to a baseline in-order system and 76% energy savings when compared to an Out-of-Order system. When using HBM, we further accelerate real-time transcoding and CNNs by up to 7% and 8% respectively.

Item Type:Book Section
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©2019 IEEE
Spring Simulation Conference (SpringSim) (2019. Tucson, Arizona)
This work has been partially supported by the EC H2020 RECIPE (GA No. 801137) project, the ERC Consolidator Grant COMPUSAPIEN (GA No. 725657), the EU FEDER and the Spanish MINECO (GA No. TIN2015-65277-R).

Uncontrolled Keywords:Many-core; Architectural exploration; Gem5; In-cache; HBM
Subjects:Sciences > Computer science > Artificial intelligence
ID Code:58594
Deposited On:21 Jan 2020 19:08
Last Modified:21 Jan 2020 19:08

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