Title :
The potential of compression to improve memory system performance, power consumption, and cost
Author :
Mahapatra, Nihar R. ; Liu, Jiangjiang ; Sundaresan, Krishnan ; Dangeti, Srinivas ; Venkatrao, Balakrishna V.
Author_Institution :
Dept. of Comput. Sci & Eng, State Univ. of New York, Buffalo, NY, USA
Abstract :
The continuing exponential growth in processor performance, combined with technology, architecture, and application trends, places enormous demands on the memory system to allow information storage and exchange at a high-enough performance (i.e., to provide low latency and high bandwidth access to large amounts of information), at low power, and cost-effectively. The paper comprehensively analyzes the redundancy in the information (addresses, instructions, and data) stored and exchanged between the processor and the memory system and evaluates the potential of compression in improving performance, power consumption, and cost of the memory system. Traces obtained with Sun Microsystems´ simulator simulating SPARC executables of nine integer and six floating-point programs in the SPEC CPU2000 benchmark suite and analyzed using Markov entropy models, existing compression schemes, and CACTI 3.0 and SimplePower timing, power, and area models yield impressive results.
Keywords :
Markov processes; data compression; digital storage; entropy; power consumption; redundancy; storage management; Markov entropy models; computer system design; cost; information exchange; information redundancy; information storage; memory system performance; power consumption; Analytical models; Bandwidth; Costs; Delay; Energy consumption; Information analysis; Performance analysis; Power system modeling; Sun; System performance;
Conference_Titel :
Performance, Computing, and Communications Conference, 2003. Conference Proceedings of the 2003 IEEE International
Print_ISBN :
0-7803-7893-8
DOI :
10.1109/PCCC.2003.1203717