Parallel thinking

Thinking in Parallel: Some Basic Data-Parallel Algorithms and Techniques

∗Copyright 1992-2009, Uzi Vishkin. These class notes reflect the theorertical part in the Parallel Algorithms course at UMD. The parallel programming part and its computer architecture context within the PRAM-On-Chip Explicit Multi-Threading (XMT) platform is provided through the XMT home page www.umiacs.umd.edu/users/vishkin/XMT and the class home page. Comments are welcome: please write to me...

Teaching Parallel Thinking to the Next Generation of Programmers

Most collegiate programs in Computer Science offer an introductory course in programming, primarily devoted to communicating the foundational principles of software design and development. Methodologies for solving problems within a discrete computational context are presented. Logical thinking is highlighted, guided primarily by a sequential approach to algorithm development and made manifest ...

CS 554 / CSE 512: Parallel Numerical Algorithms Lecture Notes Chapter 2: Parallel Thinking

A common partition/communicate/agglomerate/map methodology is effective for parallelization of many numerical and data-intensive algorithms [17]. We develop this methodology in general and provide a few typical examples. A model of the cost and execution time of these algorithms is then derived using the communication and execution models from the previous chapter. These models provide a lens f...

Dimensions for Thinking About Thinking

We start by making a distinction between mind and cognition, and by positing that cognition is an aspect of mind. We propose as a working hypothesis a Separability Hypothesis which posits that we can factor off an architecture for cognition from a more general architecture for mind, thus avoiding a number of philosophical objections that have been raised about the "Strong AI" hypothesis. We the...

Critical Thinking about 'critical Thinking'