This book is a look into the DIY part of my life, and so also doubles as an encyclopaedia of useful and not so useful things that will help every son of future generations to survive the credit crunch, the collapse of the banking system, the darkness of difficult times ahead, the .... Indeed, it is a reference book for all those who, like my dad was, are or are going to be poor middle class owners of homes. It shares a lifetime of experiences (mine and my dad's) with you and leaves you in no doubt as to how one should tackle life's little burdens, or how to avoid them in the first place. In the interests of being politically correct, the book may be bought and given as gifts by moms who have reason to believe that their daughters have an inclination towards DIY sort of things.
The organization of data is clearly of great importance in the design of high performance algorithms and architectures. Although there are several landmark papers on this subject, no comprehensive treatment has appeared. This monograph is intended to fill that gap. We introduce a model of computation for parallel computer architec- tures, by which we are able to express the intrinsic complexity of data or- ganization for specific architectures. We apply this model of computation to several existing parallel computer architectures, e.g., the CDC 205 and CRAY vector-computers, and the MPP binary array processor. The study of data organization in parallel computations was introduced as early as 1970. During the development of the ILLIAC IV system there was a need for a theory of possible data arrangements in interleaved mem- ory systems. The resulting theory dealt primarily with storage schemes also called skewing schemes for 2-dimensional matrices, i.e., mappings from a- dimensional array to a number of memory banks. By means of the model of computation we are able to apply the theory of skewing schemes to var- ious kinds of parallel computer architectures. This results in a number of consequences for both the design of parallel computer architectures and for applications of parallel processing.
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