Excerpt from Automatic Storage Optimization
Most studies of optimization techniques for higher level languages have focused on improving execution time of generated programs, often at the expense of increased storage. When storage optimization has been addressed, it is usually in conjunction with time Optimization, such as in instruction-reducing code transformations. In Section two existing storage - Optimizing compilers are discussed.
The rising popularity of minicomputers and microprocessors suggests that the time has come to take a closer look at the problem of automatic storage optimization. Because lack of space has always been a problem in the small machine environ ment, the proliferation of small machines implies the increasing importance of the problem. Although the decreasing cost of memory may mitigate this trend, a variant of Murphy's law ensures that program size will always increase faster than the available storage; in short, programmers will always write programs that don't fit.
Even without the advent of the small computer, such an investigation would be warranted from a language point of view.
Today, almost all programming languages include the notionof storage in the concept of a variable, and most compilers maintain a one - to - one mapping between variables and storage This means that, in a tight storage situation, the programmer must overlap storage by deliberately using a single variable for more than one purpose, to the detriment of the clarity and reliability of the program. A desirable goal would be a language in which variables had no storage connotation, but where the processor performed all storage allocation deci sions, guaranteeing only the integrity of the variable. This is an important goal, since, unlike the case of time optimization, where the scope of a coding trick is relatively local, a storage-optimizing coding trick often obscures the entire program.
Storage optimization is also applicable in Virtual storage systems where a decrease in program size may result in a smaller page requirement for the object program, with consequent improvement in program execution time. The related question of organizing procedures of a given size so as to minimize interpage transitions has been treated by Kernighan (ker70, Ker71)
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Paperback. Condition: New. Print on Demand. This book is a significant study on automatic storage optimization. Specifically, the author looks at storage optimization in relation to several NP-complete problems, aiming to demonstrate both the plausibility and practicality of the technique. The author surveys past work on overlay heuristics and presents a family of heuristics that he has implemented in SOCRATES (the Storage Optimization Code Reorganization And Transformation Experimental System) to study the amenability of typical programs to various storage optimization techniques. The author finds that the problem of data overlay has a number of similarities to the Shipbuilding Problem and the Graph Coloring problem and demonstrates that, for array conflict graphs, a result by Alan Hoffman can be used to establish an upper bound for the extended chromatic number. Researchers with interests in compiler design, graph theory, and computer science will find much of interest in this book. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. Seller Inventory # 9781334016592_0
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # LX-9781334016592
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # LX-9781334016592
Quantity: 15 available