CAREER: Architectural Techniques and Tools for Adaptive Active Storage Systems

University Of Virginia Main Campus, Charlottesville VA

Investigators

Abstract

The ability to embed computation on the I/O path creates exciting possibilities for accelerating a wide spectrum of data intensive applications, ranging from content-based retrieval of images stored on a personal computer to fusion of massive geospatial datasets. The presence of processing power at the storage devices, coupled with the location of these devices in the system, also opens up the opportunity to provide storage-centric computing services that run directly on the I/O path. However, harnessing a large amount of processing power on the I/O path at a small energy cost requires extensive architectural support. This research project develops a storage-centric architecture in which the entire I/O path is treated as a programmable and reconfigurable computational substrate. The research addresses several cross-cutting issues in electro-mechanical design, processor microarchitecture, and parallel programming. An integral component of this project includes the development of simulation tools and a hardware testbed for research and education in the area of adaptive active storage systems.