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Measures of ideal execution architectures

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2 Author(s)
Flynn, M. ; Stanford University, Computer Systems Laboratory, Electrical Engineering Department, California 94305, USA ; Hoevel, Lee W.

This paper is a study in ideal computer architectures or program representations. We define measures of “ideal” architectures that are related to the higher-level representation used to describe a program at the source language level. Traditional machine architectures name operations and objects which are presumed to be present in the host machine: a memory space of certain size, ALU operations, etc. An ideal language-based architecture is based on a specific higher-level (source) language, and uses the operations in that language to describe transformations over objects in that language. The notion of ideal is necessarily constrained. The object program representation must be easily decompilable (i.e., the source is readily reconstructable). It is assumed that the source itself is a good representation for the original problem; thus any nonassignment operation present in the source program statement appears as a single instruction (operation) in the ideal representation. All named objects are defined with respect to the scope of definition of the source program. For simplicity of discussion, statistical behavior of the program and language is assumed to be unknown; Huffman codes are not used. From the above, canonic interpretive (CI) measures are developed. CI measures apply to both the space needed to represent a program and the time needed to interpret it. Example-based CI measures are evaluated for a variety of contemporary architectures, both host-and language-oriented, as well as a CI-derived language-oriented architecture.

Note: The Institute of Electrical and Electronics Engineers, Incorporated is distributing this Article with permission of the International Business Machines Corporation (IBM) who is the exclusive owner. The recipient of this Article may not assign, sublicense, lease, rent or otherwise transfer, reproduce, prepare derivative works, publicly display or perform, or distribute the Article.  

Published in:

IBM Journal of Research and Development  (Volume:28 ,  Issue: 4 )

Date of Publication:

July 1984

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