Evaluating the Power of the Parallel MASC Model
Using Simulations
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The Multiple Associative Computing (MASC) model is multiple SIMD (Single Instruction stream Multiple Date stream) with an associative style parallel computation model. It offers a complete paradigm for general-purpose parallel computation. This book focuses on evaluating the power of the MASC model to provide a better understanding of associative SIMD computing. It consists of three parts. The first part is to justify the timing assumptions for the basic MASC associative operations, as these operations are used extensively in MASC algorithms. The second part creates simulations between MASC an...
The Multiple Associative Computing (MASC) model is
multiple SIMD (Single Instruction stream Multiple
Date stream) with an associative style parallel
computation model. It offers a complete paradigm for
general-purpose parallel computation. This book
focuses on evaluating the power of the MASC model to
provide a better understanding of associative SIMD
computing. It consists of three parts. The first
part is to justify the timing assumptions for the
basic MASC associative operations, as these
operations are used extensively in MASC algorithms.
The second part creates simulations between MASC and
well-known parallel enhanced mesh models, giving an
efficient way for transferring algorithms from
enhanced meshes to MASC. The third part involves
using the ASC model (i.e. MASC with one instruction
stream) to develop a polynomial time solution to the
real-time Air Traffic Control problem. This type of
real-time problem is currently considered to be
unsolvable in polynomial time using a MIMD computer.
Since the MIMD model is generally believed to be
more powerful than the SIMD model, our research work
suggests that this belief needs to be reconsidered.
multiple SIMD (Single Instruction stream Multiple
Date stream) with an associative style parallel
computation model. It offers a complete paradigm for
general-purpose parallel computation. This book
focuses on evaluating the power of the MASC model to
provide a better understanding of associative SIMD
computing. It consists of three parts. The first
part is to justify the timing assumptions for the
basic MASC associative operations, as these
operations are used extensively in MASC algorithms.
The second part creates simulations between MASC and
well-known parallel enhanced mesh models, giving an
efficient way for transferring algorithms from
enhanced meshes to MASC. The third part involves
using the ASC model (i.e. MASC with one instruction
stream) to develop a polynomial time solution to the
real-time Air Traffic Control problem. This type of
real-time problem is currently considered to be
unsolvable in polynomial time using a MIMD computer.
Since the MIMD model is generally believed to be
more powerful than the SIMD model, our research work
suggests that this belief needs to be reconsidered.
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