Blelloch G.E. Vector Models for Data-Parallel Computing

MIT Press, 1990. — 268 p."Vector Models for Data-Parallel Computing "describes a model of parallelism that extends and formalizes the Data-Parallel model on which the Connection Machine and other supercomputers are based. It presents many algorithms based on the model, ranging from graph algorithms to numerical algorithms, and argues that data-parallel models are not only practical and can be applied to a surprisingly wide variety of problems, they are also well suited for very-high-level languages and lead to a concise and clear description of algorithms and their complexity. Many of the author's ideas have been incorporated into the instruction set and into algorithms currently running on the Connection Machine.The book includes the definition of a parallel vector machine; an extensive description of the uses of the scan (also called parallel-prefix) operations; the introduction of segmented vector operations; parallel data structures for trees, graphs, and grids; many parallel computational-geometry, graph, numerical and sorting algorithms; techniques for compiling nested parallelism; a compiler for Paralation Lisp; and details on the implementation of the scan operations.Part I Models.
Parallel Vector Models.
The Scan Primitives.
The Scan Vector Model.
Part II Algorithms.
Data Structures.
Computational-Geometry Algorithms.
Graph Algorithms.
Numerical Algorithms.
Part III Languages and Compilers.
Collection-Oriented Languages.
Flattening Nested Parallelism.
A Compiler for Paralation Lisp.
Part IV Architecture.
Implementing Parallel Vector Models.
Implementing the Scan Primitives.A: Glossary.
B: Code.
C: Paralation-Lisp Code.