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Time-SpaceTrade-OffsinParallelandNeuralComputing Razvan Andonie
 

Summary: Time-SpaceTrade-OffsinParallelandNeuralComputing
Razvan Andonie
Computer Science Department, Wayne State University
431 State Hall, Detroit, MI 48202, USA
andonie@cs.wayne.edu
on leave of absence from:
Department of Electronics and Computers
Transylvania University, 2200 Brasov, Romania
Abstract
To which extend can we speak about time-space trade-
offs in the sense that, for a given problem, a faster
algorithm requires more space than a slower algorithm?
Furthermore, to which extend can we speak about such
trade-offs in the context of parallel or neural computing?
This paper aims to give an insight to these problems. The
parallel computation thesis, first proposed in print in
[Ch.S.76], is a relation between parallel time and
sequential space. The thesis holds for the parallel model P
if parallel time is polynomially related to sequential
space. How should we state a "neural computation

  

Source: Andonie, Razvan - Department of Computer Science, Central Washington University

 

Collections: Computer Technologies and Information Sciences