Detection of partially simultaneously alive signals in storage requirement estimation for d.pdf

Detection of partially simultaneously alive signals in storage requirement estimation for d.pdf

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Detection of partially simultaneously alive signals in storage requirement estimation for d

Detection of Partially Simultaneously Alive Signals in Storage Requirement Estimation for Data Intensive Applications Per Gunnar Kjeldsberg Norwegian University of Science and Technology Trondheim, Norway pgk@fysel.ntnu.no Francky Catthoor IMEC, Leuven, Belgium Also at EE.Dept. of Kath. Univ. Leuven catthoor@imec.be Einar J. Aas Norwegian University of Science and Technology Trondheim, Norway einar.aas@fysel.ntnu.no ABSTRACT In this paper, we propose a novel storage requirement estimation methodology for use in the early system design phases when the data transfer ordering is only partially fixed. At that stage, none of the existing estimation tools are adequate, as they either assume a fully specified execution order or ignore it completely. Using rep- resentative application demonstrators, we show how our technique can effectively guide the designer to achieve a transformed specifi- cation with low storage requirement. 1. INTRODUCTION Many integrated circuit systems, particularly in the multi-media and telecom domains, are inherently data dominant. For this class of applications, data transfer and storage largely determine cost and performance parameters. This is the case for chip size, since large memories are usually needed, performance, since accessing the memories may very well be the main bottleneck, and power consumption, since the memories and buses consume large quanti- ties of energy. Even for systems with caches, the overall storage requirement has vital impact on the performance and power con- sumption, since it greatly influences the number of slow and power expensive cache misses. For the system development process, the designer must hence concentrate first on exploring the data transfer and storage to achieve a cost optimized end product [4]. At the system level, no detailed information is available about the size of the memories required for storing data in the alternative realiza- tions of the application. To

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