1995
DOI: 10.1155/1995/28167
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PARTIF: Interactive System‐level Partitioning

Abstract: This paper presents a methodology and a tool box for system-level partitioning in the behavioral domain. The methodology is based on an extended finite state machine model. Partitioning is achieved interactively through the application of five system-level transformation primitives: MOVE, MERGE, SPLIT, CUT and MAP. This scheme allows an interactive exploration of the solution space. The result of the partitioning is a set of interconnected and heterogeneous sub-systems. The partitioning tool box which has been… Show more

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Cited by 4 publications
(3 citation statements)
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“…It would also be interesting to see how system partitioning techniques (e.g. [9,6,7,15]) can be applied on our customized architectures.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…It would also be interesting to see how system partitioning techniques (e.g. [9,6,7,15]) can be applied on our customized architectures.…”
Section: Discussionmentioning
confidence: 99%
“…Particularly error proned and timing consuming are the tasks of interfacing the hardware and software components together and providing communication between them. Designers currently spend a tremendous amount of time with low-level design details and extensive debugging to ensure correctness, thus leaving little room for optimization or explo- Most research efforts have focussed on higher level issues such as system behavioral modeling, system level transformations, and system partitioning [6,7,9,3,15,1,16,10,12,18]. Although these efforts have led to promising results, they are addressing largely complementary problems.…”
Section: Introductionmentioning
confidence: 99%
“…The most relevant system research subdomain is hardware-software partitioning [Barros et al 1994;Ernst et al 1993;Gajski et al 1994;Gupta and De Micheli 1993;Ismail et al 1994]. The goal of software partitioning is to identify parts of computations which should be implemented on programmable and ASIC platforms so that an overall optimization function is maximized.…”
Section: Related Workmentioning
confidence: 99%