Knowledge-Based Code Selection Methods in Retargetable Microcode Synthesis

Mueller, Robert A.; Varghese, Joseph

doi:10.1109/mdt.1985.294723

Cited by 10 publications

(3 citation statements)

References 18 publications

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“…The so-called means-ends analysis [79] lies at the center of these methods (see also Section III-A). Means-ends analysis was employed by, among others, [77] in the domain of automatic program synthesis, and by [34] in designing room configurations.…”

Section: G the Ai Design Paradigmmentioning

confidence: 99%

The design process: properties, paradigms, and structure

Braha

Maimon

1997

IEEE Trans. Syst., Man, Cybern. A

104

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In this paper, we examine the logic and methodology of engineering design from the perspective of the philosophy of science. The fundamental characteristics of design problems and design processes are discussed and analyzed. These characteristics establish the framework within which different design paradigms are examined. Following the discussions on descriptive properties of design, and the prescriptive role of design paradigms, we advocate the plausible hypothesis that there is a direct resemblance between the structure of design processes and the problem solving of scientific communities. The scientific community metaphor has been useful in guiding the development of general purpose highly effective design process meta-tools [73], [125]. His research within engineering design focuses on developing methods to help the designer move from the conceptual phase to the realization of the physical device. To achieve this objective, he has developed the formal general design theory (FGDT), which is a mathematical theory of design. He has developed methods to solve routine design with group technology, genetic algorithms, and simulated annealing, to define computerized architecture, structure, and databases for the conceptual design process, and to develop a framework of logic decomposition and case-based reasoning methodology for mechanical design. He is also co-authoring, with O. Maimon, a book on the foundations of engineering design. Additional interests include real-time scheduling of flexible manufacturing systems, inventory management, risk and decision analyses, and group technology. His papers have been published in several journals, including the IEEE

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Section: G the Ai Design Paradigmmentioning

confidence: 99%

The design process: properties, paradigms, and structure

Braha

Maimon

1997

IEEE Trans. Syst., Man, Cybern. A

104

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show abstract

“…The kind of problems encountered in the instruction-selection phase are of such a nature, that a mathematically sound translation is only feasible by providing the code-generator with a semantic knowledgebase (as in [45]) and (interactive) theoremproving tools. This would entail, that a user of such a system would have to enter and verify properties relating dtifferent operations during the code-generation process (and thus let verification help code-generation).…”

Section: Examplementioning

confidence: 99%

Verification of microprogrammed computer architectures in the S*-system: a case study

Damm¹,

Dohmen²

1985

Proceedings of the 18th Annual Workshop on Microprogramming

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“…Detailed discussions of the other components of the retargetable system shown in Figure 1 are given elsewhere.' The use of knowledgebased methods to achieve retargetability in the Colorado State University (CSU) system is the subject of [33]. This paper is organized into two major sections and a summary.…”

Section: Introductionmentioning

confidence: 99%

Retargetable microcode synthesis

Mueller

Varghese²

1987

ACM Trans. Program. Lang. Syst.

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Most work on automating the translation of high-level microprogramming languages into microcode has dealt with lexical and syntactic analysis and the use of manually produced macro tables for code generation. We describe an approach to and some results on the formalization and automation of the more difficult problem of retargeting local code generation in a machine-independent, optimizing microcode synthesis system. Whereas this problem is similar in many ways to that of retargeting local code generation in high-level language compilers, there are some major differences that call for new approaches.The primary issues addressed in this paper are the representation of target microprogrammable machines, the intermediate representation of local microprogram function, and general algorithmic methods for deriving local microcode from target machine and microcode function specifications. Of particular interest are the use of formal semantics and data flow principles in achieving both a general and reasonably efficient solution. Examples of the modeling of a representative horizontal machine (the PUMA) and the generation of microcode for the PUMA machine model from our working implementation are presented.

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Knowledge-Based Code Selection Methods in Retargetable Microcode Synthesis

Cited by 10 publications

References 18 publications

The design process: properties, paradigms, and structure

The design process: properties, paradigms, and structure

Verification of microprogrammed computer architectures in the S*-system: a case study

Retargetable microcode synthesis

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