Data Structures for Data-Parallel Architectures

University Of California-Davis, Davis CA

Investigators

Abstract

The project investigates the development of flexible, generic and high-performance data structures for commodity data-parallel architectures. The research will determine appropriate abstractions of data structures suitable for these architectures, determine efficient implementations for the data structures, and develop and build a framework for tuning them for different architectures. The research will address the issues in providing high-performance data structures for GPUs that can be tuned for different parallel architectures. The successful completion of this project will have significant impact in exploiting the growing trend towards multi-core and multi threaded parallel processing in commodity processors, by facilitating the development of parallel software in these environments.