Treffer: Entropy-based low power data TLB design

Title:
Entropy-based low power data TLB design
Source:
CASES 2006 (International Conference on Compilers, Architecture, and Synthesis for Embedded Systems, October 22-25, 2006, Seoul, Korea, embedded systems week 2006). :304-311
Publisher Information:
New York NY: ACM Press, 2006.
Publication Year:
2006
Physical Description:
print, 17 ref 1
Original Material:
INIST-CNRS
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
School of ECE Georgia Institute of Technology, Atlanta, GA 30332, United States
College of Computing Georgia Institute of Technology, Atlanta, GA 30332, United States
Rights:
Copyright 2007 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.19105506
Database:
PASCAL Archive

Weitere Informationen

The Translation Look-aside Buffer (TLB), a content addressable memory, consumes significant power due to the associative search mechanism it uses in the virtual to physical address translation. Based on our analysis of the TLB accesses, we make two observations. First, the entropy or information content of the stack virtual page numbers is low due to high spatial locality of stack memory references. Second, the entropy of the higher order bits of global memory references is low since the size of the global data is determined and fixed during compilation of a program. Based on these two characteristics, we propose two techniques: an entropy-based speculative stack address TLB and a deterministic global address TLB to achieve energy reducing. Our results show an average of 47% energy savings in the data TLB with less than 1% overall performance impact.