I am a fourth year Ph.D. student in Computer Science working with the Systems and Networking Group at UC San Diego advised by Professor Amin Vahdat and Dr. George Porter. I received my Master of Science degree in Computer Science from UC San Diego in 2012 and my Bachelor of Science degree in Computer Science from Caltech in 2009. My research interests include large-scale distributed systems, I/O-intensive "big data" applications, and efficient, balanced computing.

Current Work

I am currently investigating driving big-data applications at high throughput on cluster hardware technology of the future. Data centers 5 years from now will likely consist of resource-dense servers containing very high-speed components such as non-volatile memory on a fast bus like PCIe. These servers will also be connected with high-speed networking like 40G ethernet. A key challenge is driving applications at the speed that the hardware is capable of. Ideally, an execution framework, such as Themis, should be able to provide 40 Gb/s of application throughput on these servers, but actually reaching these speeds is an interesting research challenge.

Themis

I developed Themis, the successor to TritonSort. Themis is an I/O efficient MapReduce implementation that achieves the minimum number of I/Os possible (2) when the amount of data greatly exceeds the amount of physical memory. Themis has been evaluated on a variety of common MapReduce jobs and performs at roughly the same record-breaking speed as its predecessor, TritonSort. Themis was published in SOCC 2012.

TritonSort

I developed the world's fastest sorting system, TritonSort. TritonSort achieves record speeds by focusing on per-disk and per-node efficiency. TritonSort aims to sort data at the speed of the disks by keeping all disks constantly reading or writing data in large contiguous chunks. TritonSort set world records in the 2010 and 2011 Sortbenchmark.org competitions. We hold a total of seven world records: 2010 Indy GraySort, 2010 Indy MinuteSort, 2011 Daytona GraySort, 2011 Indy GraySort, 2011 Indy MinuteSort, 2011 Daytona 100TB JouleSort, 2011 Indy 100TB JouleSort. Four of these are current world records.

Other Work

During summer of 2009, I investigated balanced systems within the MapReduce framework of Hadoop. Goals consisted of analyzing cluster resources during a MapReduce job, identifying bottlenecks, and classifying various types of jobs according to these bottlenecks with the hope of being able to utilize cluster resources more efficiently.

I held a Software Engineering Intern position at Google during the summer of 2011 working in the MapReduce group with my mentor Marian Dvorsky.

I held a Software Engineering Intern position at Google during the summer of 2010 working in the search infrastructure group with my mentor Alexander Yip.

TritonSort: A Balanced and Energy-Efficient Large-Scale Sorting System, Alexander Rasmussen, George Porter, Michael Conley, Harsha V. Madhyastha, Radhika Niranjan Mysore, Alexander Pucher, and Amin Vahdat, ACM Transactions on Computing Systems (TOCS), Volume 31 Issue 1, February 2013. Link to paper.

Themis: An I/O-Efficient MapReduce, Alexander Rasmussen, Michael Conley, Rishi Kapoor, Vinh The Lam, George Porter, and Amin Vahdat, Proceedings of the 3rd ACM Symposium on Cloud Computing (SOCC), San Jose, CA, October 2012. Link to paper.

TritonSort: A Balanced Large-Scale Sorting System, Alexander Rasmussen, George Porter, Michael Conley, Harsha V. Madhyastha, Radhika Niranjan Mysore, Alexander Pucher, and Amin Vahdat, Proceedings of the 8th ACM/USENIX Symposium on Networked Systems Design and Implementation (NSDI), Boston, MA, March 2011. Link to paper.

SortBenchmark 2011: TritonSort competed again in the Sort Benchmark competition in April 2011. This year we set 5 records (all wins, no ties): Indy 100TB GraySort, Daytona 100TB GraySort, Indy 60 second MinuteSort, Indy 100TB Joulesort, Daytona 100TB Joulesort. We built a general purpose MapReduce implementation with an initial sampling phase that enabled us to take the Daytona (general purpose) records. The SortBenchmark rules were updated this year to include a 100TB JouleSort category, which measures records/joule as the performance metric. As it turns out, focusing on cluster balance and resource utilization appears to be a viable means for power efficient computing. TritonSort's JouleSort performance is less than an order of magnitude off of the most efficient system in any of the other JouleSort categories. Keep in mind that energy efficiency was not a primary goal of the TritonSort project. You can read our submission document here.

SortBenchmark 2010: TritonSort, the world's fastest cluster based disk-to-disk sorting system, which we submitted to the Sort Benchmark competition in May 2010. TritonSort placed first in the Indy MinuteSort 60 second category and tied for first in the Indy GraySort 100TB category. TritonSort focuses on per-node efficiency and aims to achieve sorting throughput as close as possible to the sequential speed of the disks. See the SortBenchmark submission document here.

I was the teaching assistant for CSE 120: Principles of Operating Systems during Summer Session 1 2012.

I enjoy running, playing board games, and listening to electronic music. One of my goals for the near-future is to run a half marathon. My longest trail run was somewhere on the order of 6-7 miles, but I'm hoping to increase that mileage soon.