7377

GPGPU-Accelerated Instruction Accurate and Fast Simulation of Thousand-core Platforms

Shivani Raghav, Martino Ruggiero, David Atienza, Christian Pinto, Andrea Marongiu, Luca Benini
ESL – EPFL, Lausanne, CH
Workshop on Micro Power Management for Macro Systems on Chip (uPM2SoC), Held in conjunction with Design, Automation and Test in Europe Conference, Grenoble, France, March 18th, 2011

@article{raghav2012gpgpu,

   title={GPGPU-Accelerated Instruction Accurate and Fast Simulation of Thousand-core Platforms},

   author={Raghav, S. and Pinto, C. and Ruggiero, M. and Marongiu, A. and Atienza, D. and Benini, L.},

   year={2012}

}

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Future architectures will feature hundreds to thousands of simple processors and on-chip memories connected through a network-on-chip. Architectural simulators will remain primary tools for design space exploration, performance (and power) evaluation of these massively parallel architectures. However, architectural simulation performance is a serious concern, as virtual platforms and simulation technology are not able to tackle the complexity of 1,000-core future scenarios. The main contribution of this paper is the development of a simulator for 1,000-core processors which exploits the enormous parallel processing capability of low-cost and widely available General Purpose Graphic Processing Units (GPGPU). We demonstrate our GPGPU simulator on a target architecture composed by several cores (i.e. ARM ISA based), with instruction and data caches, connected trough a Networkon-Chip (NoC). Our experiments confirm the feasibility of our approach. Currently, our ongoing work is focused on developing the power models within the simulation engine.
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