We are at an interesting crossroads in
computer architecture. Over the past two decades, there have been several
advances in processor design, from microarchitectural techniques to boost
instruction- and thread-level parallelism, to the shift from the use of
single-core to multicore processors. The number of cores on the die is expected
to continue growing in the future, thereby providing a tremendous amount of
processing power within a single chip. At the same time, applications are also
becoming more data intensive. There already exist several applications that
handle massive amounts of data and are used by millions of people every day.
These include traditional data intensive applications, such as transaction
processing, email, and search engines as well as newer applications spanning
areas such as social networking, photo and video sharing. The number of such
applications is growing all the time and so is the amount of data they handle.
This confluence of trends in architecture and applications requires computer
architecture support to facilitate the storage of massive amounts of data and
providing efficient access to them and also to efficiently transport the data
between storage and the processors. Designing such computer architectures in an
energy-efficient manner is a major challenge.
The goal of this project is to design energy-efficient storage systems and storage-centric architectures for data intensive applications, as well as develop techniques for designing and configuring storage systems to boost energy efficiency. A few contributions of this project to date include Dynamic RPM modulation to provide multiple performance/energy operating points for disk drives, Intra-Disk Parallelism to exploit I/O parallelism inside a disk drive, sensitivity-based optimization to craft storage energy management policies, and active storage architectures that facilitate storage-centric computation to be offloaded to processors closer to the storage devices.
S. Sankar, S. Gurumurthi, M.R. Stan, Intra-Disk Parallelism: An Idea Whose Time Has Come, Proceedings of the International Symposium on Computer Architecture (ISCA), June 2008.
S. Sankar, S. Gurumurthi, M.R. Stan, Sensitivity Based Power Management of Enterprise Storage Systems, International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS), September 2008.
C.W. Smullen, S.R. Tarapore, S. Gurumurthi, P. Ranganathan, M. Uysal, Active Storage Revisited: The Case for Power and Performance Benefits for Unstructured Data Processing Applications, Proceedings of the ACM International Conference on Computing Frontiers (CF), May 2008.
Y. Zhang, S. Gurumurthi, M.R. Stan, SODA: Sensitivity Based Optimization of Disk Architecture, Proceedings of the Design Automation Conference (DAC), pages 865-870, June 2007.
S. Gurumurthi, A. Sivasubramaniam, M. Kandemir, H. Franke, DRPM: Dynamic Speed Control for Power Management in Server Class Disks, In the Proceedings of the International Symposium on Computer Architecture (ISCA), pages 169-179, June 2003.