Processors

MapCG: Writing Parallel Program Portable Between CPU and GPU

Free registration required

Executive Summary

Graphics Processing Units (GPU) have been playing an important role in the general purpose computing market recently. The common approach to program GPU today is to write GPU specific code with low level GPU APIs such as CUDA. Although this approach can achieve very good performance, it raises serious portability issues: programmers are required to write a specific version of code for each potential target architecture. It results in high development and maintenance cost.

  • Format: PDF
  • Size: 349.1 KB