Speaker

Sudhanva Gurumurthi

Abstract

Server storage systems are often built using a large number of disks to meet the performance and capacity demands of data-intensive applications. However, such large storage systems can consume a significant amount of power, thereby increasing the power and cooling costs of a data center. In this talk, I will present a novel disk drive design, called "intra-disk parallelism", which can facilitate building high-performance, low-power enterprise storage systems. Intra- disk parallelism extends the conventional hard disk drive architecture by: (i) decoupling the way that the spindle and arm-assembly of a disk drive are used to service I/O requests, so that we can overlap disk seeks with rotational delays, and (ii) decoupling the multiplicity of the components within each of these two electro-mechanical systems to further enhance parallelism.

I will first provide a historical retrospective on intra-disk parallelism, discussing the similarities and key differences between our approach and the multi-actuator drives of the past. I will present an overview of the design space of intra-disk parallelism, identifying the locations within a disk drive where parallelism can be incorporated. Using a set of commercial workloads, I will provide an analysis of the performance and power characteristics of a specific design within this space and show that storage arrays built using such drives consume 40%-60% less power while delivering performance that is comparable to arrays built using conventional disk drives. Finally, I will discuss the key engineering and cost issues involved in building intra-disk parallel drives and show that intra-disk parallelism can be a practical approach to build energy-efficient enterprise storage systems.

Speaker Bio

Sudhanva Gurumurthi is an Assistant Professor in the Computer Science Department at the University of Virginia. Sudhanva's research area is computer architecture, with specialization in energy-efficient storage systems and silicon-reliability. He received his PhD in Computer Science and Engineering from Penn State in 2005 and has held research positions at the IBM Austin Research Lab and Intel Corporation. Sudhanva received the NSF CAREER Award in 2007, the CSE Research Assistant Award in 2004, and the Robert M. Owens Memorial Scholarship in 2003. He is a member of the ACM and the IEEE. More details about Sudhanva's research can be found on his home page.