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CASPER: Embedding Power Estimation and Hardware-Controlled Power Management in a Cycle-Accurate Micro-Architecture Simulation Platform for Many-Core Multi-Threading Heterogeneous Processors

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Author(s): Kushal Datta | Arindam Mukherjee | Guangyi Cao | Rohith Tenneti | Vinay Vijendra Kumar Lakshmi | Arun Ravindran | Bharat S. Joshi

Journal: Journal of Low Power Electronics and Applications
ISSN 2079-9268

Volume: 2;
Issue: 1;
Start page: 30;
Date: 2012;
Original page

Keywords: simulation | processor architectures | modeling | power consumption | performance evaluation and estimation | dynamic power management unit | hardware based power management | power estimation

ABSTRACT
Despite the promising performance improvement observed in emerging many-core architectures in high performance processors, high power consumption prohibitively affects their use and marketability in the low-energy sectors, such as embedded processors, network processors and application specific instruction processors (ASIPs). While most chip architects design power-efficient processors by finding an optimal power-performance balance in their design, some use sophisticated on-chip autonomous power management units, which dynamically reduce the voltage or frequencies of idle cores and hence extend battery life and reduce operating costs. For large scale designs of many-core processors, a holistic approach integrating both these techniques at different levels of abstraction can potentially achieve maximal power savings. In this paper we present CASPER, a robust instruction trace driven cycle-accurate many-core multi-threading micro-architecture simulation platform where we have incorporated power estimation models of a wide variety of tunable many-core micro-architectural design parameters, thus enabling processor architects to explore a sufficiently large design space and achieve power-efficient designs. Additionally CASPER is designed to accommodate cycle-accurate models of hardware controlled power management units, enabling architects to experiment with and evaluate different autonomous power-saving mechanisms to study the run-time power-performance trade-offs in embedded many-core processors. We have implemented two such techniques in CASPER–Chipwide Dynamic Voltage and Frequency Scaling, and Performance Aware Core-Specific Frequency Scaling, which show average power savings of 35.9% and 26.2% on a baseline 4-core SPARC based architecture respectively. This power saving data accounts for the power consumption of the power management units themselves. The CASPER simulation platform also provides users with complete support of SPARCV9 instruction set enabling them to run a full operating system software stack, and hence a wide variety of benchmarking applications.
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