Hardware Partitioning for Big Data Analytics
Lisa Wu Wills, Raymond J. Barker, Martha A. Kim, Kenneth Andrew Ross · IEEE Micro · 2014
Targeted deployment of hardware accelerators can improve the throughput and energy efficiency of large-scale data processing. Data partitioning is a critical operation for manipulating large datasets and is often the limiting factor in database performance. A hardware-software streaming framework offers a seamless execution environment for streaming accelerators such as the Hardware-Accelerated Range Partitioner (HARP). Together, the streaming framework and HARP provide an order of magnitude improvement in partitioning and energy performance.