Abstract
Power consumption has become the major bottleneck for modern high-performance architectures, which typically contain large numbers of modules. to suppress leakage power, sleep transistors have been extensively used, and wake-up scheduling is needed to determine the wake-up times and order of these sleep transistors. Most existing works on wake-up scheduling are based on sleep transistors and delay buffers in daisy-chains; they work well for the gate-level scheduling within a module when all the gates need to be turned on. Yet, for state-of-the-art designs, the number of modules that need to be turned on and their locations may vary depending on the task to be performed at runtime. Accordingly, we cannot extend the existing gate-level scheduling algorithms to decide the module-level wake-up order. to address the problem, we propose to first off-line construct a multi-conflict graph (MCG) based on the noise constraints; based on the graph, we then develop an on-line algorithm to decide the wake-up order. Experimental results show that on average, the wake-up latency from our approach is not only 46.01% shorter compared with the existing work but also conservatively only 0.45% longer than that from a Monte Carlo Search-Based evaluation, which is orders of magnitude slower. to the best of our knowledge, this is the first in-depth study on on-line module-level wake-up scheduling for high-performance architectures. Copyright 2012 ACM.
Recommended Citation
M. C. Lee et al., "Efficient On-line Module-level Wake-up Scheduling for High Performance Multi-module Designs," Proceedings of the International Symposium on Physical Design, pp. 97 - 103, Association for Computing Machinery (ACM), May 2012.
The definitive version is available at https://doi.org/10.1145/2160916.2160939
Department(s)
Electrical and Computer Engineering
Keywords and Phrases
Module-level; Power gating; System-level; Wakeup scheduling
International Standard Book Number (ISBN)
978-145031167-0
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Association for Computing Machinery, All rights reserved.
Publication Date
01 May 2012