ACM Home Page
Please provide us with feedback. Feedback
Code compression for VLIW processors using variable-to-fixed coding
Full text PdfPdf (120 KB)
Source International Symposium on Systems Synthesis archive
Proceedings of the 15th international symposium on System Synthesis table of contents
Kyoto, Japan
SESSION: Design methodologies based on instruction code table of contents
Pages: 138 - 143  
Year of Publication: 2002
ISBN:1-58113-576-9
Authors
Yuan Xie  Princeton University, Princeton, NJ, USA
Wayne Wolf  Princeton University, Princeton, NJ, USA
Haris Lekatsas  NEC USA, Princeton, NJ, USA
Sponsors
SIGDA: ACM Special Interest Group on Design Automation
IEEE-CS\DATC : IEEE Computer Society
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 11,   Downloads (12 Months): 37,   Citation Count: 10
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/581199.581231
What is a DOI?

ABSTRACT

Memory has been one of the most restricted resources in the embedded computing system domain. Code compression has been proposed as a solution to this problem. Previous work used fixed-to variable coding algorithms that translate fixed-length bit sequences into variable-length bit sequences. In this paper, we propose code compression schemes that use variable-to-fixed (V2F) length coding. We also propose an instruction bus encoding scheme, which can effectively reduce the bus power consumption. Though the code compression algorithm can be applied to any embedded processor, it favors VLIW architectures because VLIW architectures require a high-bandwidth instruction pre-fetch mechanism to supply multiple operations per cycle. Experiments show that the compression ratios using memoryless V2F coding for IA-64 and TMS320C6x are around 72.7% and 82.5% respectively. Markov V2F coding can achieve better compression ratio up to 56% and 70% for IA-64 and TMS320C6x respectively. A greedy algorithm for codeword assignment can reduce the bus power consumption and the reduction depends on the probability model used.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
 
2
N. Ishiura et al. Instruction Code Compression for Application Specific VLIW Processors Based on Automatic Field Partitioning. Proceedings of the Workshop on Synthesis and System Integration of Mixed Technologies,, pages 105--109, 1998.
 
3
 
4
H. Lekatsas and W. Wolf. SAMC: A Code Compression Algorithm for Embedded Processors. IEEE Transactions on Computer Aided Design, Vol. 18:1689--1701, December 1999.
 
5
 
6
S. Nam. Improving dictionary-based code compression in vliw architectures. IEICE trans. Fundamentals, November 1999.
 
7
B. Tunstall. Synthesis of Noiseless Compression Codes. PhD thesis, Georgia Institute of Technology, Atlanta, Georgia, September 1967.
8
 
9
 
10
Y.Xie, W.Wolf, and H.Lekatsas. Compression Ratio and Decompression Overhead Tradeoffs in Code Compression for VLIW Architectures. Proceedings of the 4th International Conference on ASIC,pages 337--341,2001.

CITED BY  11

Collaborative Colleagues:
Yuan Xie: colleagues
Wayne Wolf: colleagues
Haris Lekatsas: colleagues