Hardware/software partitioning with integrated hardware design space exploration
Proceedings of the conference on Design, automation and test in Europe
A Model and Methodology for Hardware-Software Codesign
IEEE Design & Test
A Hardware-Software Codesign Methodology for DSP Applications
IEEE Design & Test
Hardware-Software Cosynthesis for Digital Systems
IEEE Design & Test
Hardware-Software Cosynthesis for Microcontrollers
IEEE Design & Test
Exploring Test Space with Fuzzy Decision Making
IEEE Design & Test
Applying the Propose&Revise Strategy to the Hardware-Software Partitioning Problem
IEA/AIE '98 Proceedings of the 11th international conference on Industrial and engineering applications of artificial intelligence and expert systems: methodology and tools in knowledge-based systems
A Co-Design Methodology Based on Formal Specification and High-level Estimation
CODES '96 Proceedings of the 4th International Workshop on Hardware/Software Co-Design
On the hardware-software partitioning problem: System modeling and partitioning techniques
ACM Transactions on Design Automation of Electronic Systems (TODAES)
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Hardware-software co-design addresses the developmentof complex heterogeneous systems looking for the best tradeoffsamong the different solutions. The basic idea is to combine thehardware and software design cycles. This article shows howknowledge-based techniques can be used to solve thehardware-software partitioning problem, the co-design task thatmakes the decision on the best implementation of the differentcomponents of a digital system. In particular, a fuzzy-logic-based expert system, SHAPES, has been developed based on theCommonKADS methodology. This tool takes advantage of twoimportant artificial intelligence bases: the use of an expert‘sknowledge in the decision-making process and the possibility ofdealing with imprecise and usually uncertain values by thedefinition of fuzzy magnitudes.Expert system construction has adopted a knowledge modelingapproach, following the knowledge level and knowledge separationprinciples. This expertise model is the center ofthe knowledge-based system development. It isbased in the problem-solving method Propose and Revise with aprevious heuristic classification.