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Energy- and area-efficient architectures through application clustering and architectural heterogeneity
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ACM Transactions on Architecture and Code Optimization (TACO) archive
Volume 6 ,  Issue 1  (March 2009) table of contents
Article No.: 4  
Year of Publication: 2009
ISSN:1544-3566
Authors
Lukasz Strozek  Harvard University, Massachusetts
David Brooks  Harvard University, Massachusetts
Publisher
ACM  New York, NY, USA
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ABSTRACT

Customizing architectures for particular applications is a promising approach to yield highly energy-efficient designs for embedded systems. This work explores the benefits of architectural customization for a class of embedded architectures typically used in energy- and area-constrained application domains, such as sensor nodes and multimedia processing. We implement a process flow that performs an automatic synthesis and evaluation of the different architectures based on runtime profiles of applications and determines an efficient architecture, with consideration for both energy and area constraints. An expressive architectural model, used by our engine, is introduced that takes advantage of efficient opcode allocation, several memory addressing modes, and operand types. By profiling embedded benchmarks from a variety of sensor and multimedia applications, we show that the energy savings resulting from various architectural optimizations relative to the base architectures (e.g., MIPS and MSP430) are significant and can reach 50%, depending on the application. We then identify the set of architectures that achieves near-optimal savings for a group of applications. Finally, we propose the use of heterogeneous ISA processors implementing those architectures as a solution to capitalize on energy savings provided by application customization while executing a range of applications efficiently.


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:
Lukasz Strozek: colleagues
David Brooks: colleagues