Studying Storage-Recomputation Tradeoffs in Memory-Constrained Embedded Processing

Authors:
Mahmut Kandemir;Feihui Li;Guilin Chen;Guangyu Chen;Ozcan Ozturk
Affiliations:
The Pennsylvania State University, University Park, PA;The Pennsylvania State University, University Park, PA;The Pennsylvania State University, University Park, PA;The Pennsylvania State University, University Park, PA;The Pennsylvania State University, University Park, PA
Venue:
Proceedings of the conference on Design, Automation and Test in Europe - Volume 2
Year:
2005

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Abstract

Fueled by an unprecedented desire for convenience and self-service, consumers are embracing embedded technology solutions that enhance their mobile lifestyles. Consequently, we witness an unprecedented proliferation of embedded/mobile applications. Most of the environments that execute these applications have severe power, performance, and memory space constraints that need to be accounted for. In particular, memory limitations can present serious challenges to embedded software designers. The current solutions to this problem include sophisticated packaging techniques and code optimizations for effective memory utilization. While the first solution is not scalable, the second one is restricted by intrinsic data dependences in the code that prevent code restructuring. In this paper, we explore an alternate approach for reducing memory space requirements of embedded applications. The idea is to re-compute the result of a code block (potentially multiple times) instead of storing it in memory and performing a memory operation whenever needed. The main benefit of this approach is that it reduces memory space requirements, that is, no memory space is reserved for storing the result of the code block in question.