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SOMA: a tool for synthesizing and optimizing memory accesses in ASICs
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Source International Conference on Hardware Software Codesign archive
Proceedings of the 3rd IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis table of contents
Jersey City, NJ, USA
SESSION: Memory access and virtualization techniques for performance table of contents
Pages: 231 - 236  
Year of Publication: 2005
ISBN:1-59593-161-9
Authors
Girish Venkataramani  Carnegie Mellon University, Pittsburgh, PA
Tiberiu Chelcea  Carnegie Mellon University, Pittsburgh, PA
Seth Copen Goldstein  Carnegie Mellon University, Pittsburgh, PA
Tobias Bjerregaard  TU Denmark, Lyngby, Denmark
Sponsors
SIGDA: ACM Special Interest Group on Design Automation
SIGBED: ACM Special Interest Group on Embedded Systems
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Arbitrary memory dependencies and variable latency memory systems are major obstacles to the synthesis of large-scale ASIC systems in high-level synthesis. This paper presents SOMA, a synthesis framework for constructing Memory Access Network (MAN) architectures that inherently enforce memory consistency in the presence of dynamic memory access dependencies. A fundamental bottleneck in any such network is arbitrating between concurrent accesses to a shared memory resource. To alleviate this bottleneck, SOMA uses an application-specific concurrency analysis technique to predict the dynamic memory parallelism profile of the application. This is then used to customize the MAN architecture. Depending on the parallelism profile, the MAN may be optimized for latency, throughput or both. The optimized MAN is automatically synthesized into gate-level structural Verilog using a flexible library of network building blocks. SOMA has been successfully integrated into an automated C-to-hardware synthesis flow, which generates standard cell circuits from unrestricted ANSI-C programs. Post-layout experiments demonstrate that application specific MAN construction significantly improves power and performance.


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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Collaborative Colleagues:
Girish Venkataramani: colleagues
Tiberiu Chelcea: colleagues
Seth Copen Goldstein: colleagues
Tobias Bjerregaard: colleagues