Project: Study of Appropriate Algorithm Classes for State-Of-The-Art Hybrid Hardware Architectures

Team: Dr. Peter Tröger, Frank Feinbube

Research institution: HPI Potsdam

Abstract: Trends in hardware developments emphasize the every-increasing importance of hybrid computing for future computer architectures and software systems. Competitive applications need to leverage the performance opportunities provided by emerging generations of accelerator technology. With the introduction of its K20 architecture NVIDIA takes a big step towards a wider applicability of GPU computing by supporting new concepts like dynamic programming, on-device grid management, and direct data exchange. Intel's novel Xeon Phi accelerator, being a stand-alone PCIExpress card like GPUs, but still being x86 compatible is approaching the field of hybrid computing from the general purpose side. The purpose of this study is to survey suitable algorithms for the K20 architecture and the Xeon Phi accelerators.

Last modified 8 years ago Last modified on Sep 27, 2013 4:39:36 PM