Data parallel algorithms

  • Authors:
  • W. Daniel Hillis;Guy L. Steele, Jr.

  • Affiliations:
  • Thinking Machines Corporation, Cambridge, MA;Thinking Machines Corporation, Cambridge, MA

  • Venue:
  • Communications of the ACM - Special issue on parallelism
  • Year:
  • 1986

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Abstract

Parallel computers with tens of thousands of processors are typically programmed in a data parallel style, as opposed to the control parallel style used in multiprocessing. The success of data parallel algorithms—even on problems that at first glance seem inherently serial—suggests that this style of programming has much wider applicability than was previously thought.