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Dynamic management of scratch-pad memory space
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Source Annual ACM IEEE Design Automation Conference archive
Proceedings of the 38th annual Design Automation Conference table of contents
Las Vegas, Nevada, United States
Pages: 690 - 695  
Year of Publication: 2001
ISBN:1-58113-297-2
Authors
M. Kandemir  Microsystems Design Lab, The Pennsylvania State University, University Park, PA
J. Ramanujam  Department of ECE, Louisiana State University, Baton Rouge, LA
J. Irwin  Microsystems Design Lab, The Pennsylvania State University, University Park, PA
N. Vijaykrishnan  Microsystems Design Lab, The Pennsylvania State University, University Park, PA
I. Kadayif  Microsystems Design Lab, The Pennsylvania State University, University Park, PA
A. Parikh  Microsystems Design Lab, The Pennsylvania State University, University Park, PA
Sponsors
EDAC : Electronic Design Automation Consortium
IEEE-CAS : Circuits & Systems
SIGDA: ACM Special Interest Group on Design Automation
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 16,   Downloads (12 Months): 66,   Citation Count: 57
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ABSTRACT

Optimizations aimed at improving the efficiency of on-chip memories are extremely important. We propose a compiler-controlled dynamic on-chip scratch-pad memory (SPM) management framework that uses both loop and data transformations. Experimental results obtained using a generic cost model indicate significant reductions in data transfer activity between SPM and off-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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A. Agarwal, D. Kranz, and V. Natarajan. Automatic partitioning of parallel loops and data arrays for distributed shared memory multiprocessors. In Proc. International Conference on Parallel Processing, 1993.
 
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S. P. Amarasinghe, J. M. Anderson, M. S. Lam, and C. W. Tseng. The SUIF compiler for scalable parallel machines. In Proc. the Seventh SIAM Conference on Parallel Processing for Scientific Computing, February, 1995.
 
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Dinero IV Trace-Driven Uniprocessor Cache Simulator. URL: http://www.cs.wisc.edu/c markhill/DineroIV/
 
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CITED BY  57

Collaborative Colleagues:
M. Kandemir: colleagues
J. Ramanujam: colleagues
J. Irwin: colleagues
N. Vijaykrishnan: colleagues
I. Kadayif: colleagues
A. Parikh: colleagues