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Application-specific memory management for embedded systems using software-controlled caches
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Source Annual ACM IEEE Design Automation Conference archive
Proceedings of the 37th conference on Design automation table of contents
Los Angeles, California, United States
Pages: 416 - 419  
Year of Publication: 2000
ISBN:1-58113-187-9
Authors
Derek Chiou  Department of EECS, Massachusetts Institute of Technology, Cambridge, MA
Prabhat Jain  Department of EECS, Massachusetts Institute of Technology, Cambridge, MA
Larry Rudolph  Department of EECS, Massachusetts Institute of Technology, Cambridge, MA
Srinivas Devadas  Department of EECS, Massachusetts Institute of Technology, Cambridge, MA
Sponsors
SIGDA: ACM Special Interest Group on Design Automation
EDAC : Electronic Design Automation Consortium
IEEE-CAS : Circuits & Systems
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): n/a,   Downloads (12 Months): n/a,   Citation Count: 11
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ABSTRACT

We propose a way to improve the performance of embedded processors running data-intensive applications by allowing software to allocate on-chip memory on an application-specific basis. On-chip memory in the form of cache can be made to act like scratch-pad memory via a novel hardware mechanism, which we call column caching. Column caching enables dynamic cache partitioning in software, by mapping data regions to a specified sets of cache “columns” or “ways.” When a region of memory is exclusively mapped to an equivalent sized partition of cache, column caching provides the same functionality and predictability as a dedicated scratchpad memory for time-critical parts of a real-time application. The ratio between scratchpad size and cache size can be easily and quickly varied for each application, or each task within an application. Thus, software has much finer software control of on-chip memory, providing the ability to dynamically tradeoff performance for on-chip memory.


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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CITED BY  11
 
 
 
 
 

Collaborative Colleagues:
Derek Chiou: colleagues
Prabhat Jain: colleagues
Larry Rudolph: colleagues
Srinivas Devadas: colleagues

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