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A code decompression architecture for VLIW processors
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Source International Symposium on Microarchitecture archive
Proceedings of the 34th annual ACM/IEEE international symposium on Microarchitecture table of contents
Austin, Texas
SESSION: Memory hierarchies table of contents
Pages: 66 - 75  
Year of Publication: 2001
ISBN ~ ISSN:1072-4451 , 0-7695-1369-7
Authors
Yuan Xie  Princeton University, Princeton, NJ
Wayne Wolf  Princeton University, Princeton, NJ
Haris Lekatsas  NEC USA, Princeton, NJ
Sponsors
: IEEE TC-MARCH
SIGMICRO: ACM Special Interest Group on Microarchitectural Research and Processing
Publisher
IEEE Computer Society  Washington, DC, USA
Bibliometrics
Downloads (6 Weeks): 5,   Downloads (12 Months): 15,   Citation Count: 13
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ABSTRACT

In embedded system design, memory has been one of the most restricted resources. Reducing program size has been an important goal when designing an embedded system. Most of the previous work on code compression has targeted RISC architectures. Recently VLIW processors became very popular, particularly for signal processing. Decompression speed is especially important for VLIW architectures given that the length of the instruction word is long. Furthermore, modern VLIW architectures use flexible instruction formats, which require new code compression approaches. Previous work has assumed that instruction positions within the long instruction word correspond to specific functional units. In contrast, our code compression algorithm is capable of compressing flexible instruction formats, where any functional unit can be used for any position in the instruction word. We demonstrate our methods by applying it to the TMS320C6x architecture. We also compare two techniques for decompressing the VLIW instruction packet to reduce the decompression time. A fast parallel decompression architecture is described, which is implemented in TSMC 0.25 technology.


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.

 
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Lekatsas. "Code Compression for Embedded Systems". Ph.D. dissertation, Princeton University,2000.
 
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Yuan Xie, H. Lekatsas and W. Wolf, "Compression Ratio and Decompression Overhead Tradeoffs in Code Compression for VLIW Architectures". Proceedings of International Conference on ASIC (ASION). October, 2001.
 
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CITED BY  13
 
 
 
 
 
 
Collaborative Colleagues:
Yuan Xie: colleagues
Wayne Wolf: colleagues
Haris Lekatsas: colleagues

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