Scalable Parallel Programming with CUDA

ABSTRACT

The advent of multicore CPUs and manycore GPUs means that mainstream processor chips are now parallel systems. Furthermore, their parallelism continues to scale with Moore's law. The challenge is to develop mainstream application software that transparently scales its parallelism to leverage the increasing number of processor cores, much as 3D graphics applications transparently scale their parallelism to manycore GPUs with widely varying numbers of cores.

REFERENCES

• 1: NVIDIA. 2007. CUDA Technology; http://www.nvidia.com/CUDA.
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INDEX TERMS

Primary Classification:
  D. Software
  D.1 PROGRAMMING TECHNIQUES
      D.1.3 Concurrent Programming
          Subjects: Parallel programming

Additional Classification:
  D. Software
  D.2 SOFTWARE ENGINEERING
      D.2.6 Programming Environments
          Subjects: Integrated environments

  F. Theory of Computation
  F.1 COMPUTATION BY ABSTRACT DEVICES
      F.1.2 Modes of Computation
          Subjects: Parallelism and concurrency

  I. Computing Methodologies
  I.3 COMPUTER GRAPHICS
      I.3.1 Hardware architecture
          Subjects: Parallel processing

General Terms:
Algorithms, Design