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Vijay Chidambaram
Assistant Professor, |
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I lead the UT Systems and Storage Lab. I am also a part of the LASR research group. I am broadly interested in systems-ish stuff: operating systems and distributed systems. Most of the work I've done so far has been in file systems, distributed systems, and storage. Recent interests: key-value stores, non-volatile memory, and verification. I am interested in recruiting new PhD students. I am not currently hiring Masters students. If you are interested in working with me, please check out my page for prospective students and send me an email (after reading this!). Make sure to apply to the PhD program by the deadline (December 15). If you are a student considering grad school or applying for grad school, these links may be useful (advice on contacting profs, getting letters of recommendation, etc.) I maintain the SOSP/OSDI Hall of Fame and the FAST Hall of Fame. These pages indicate who has published the most at these premier venues, and who has been publishing recently. These are good guides for grad students trying to decide which professor to work with! My research is supported by NSF, VMware, Facebook, and Google. I am an Affiliated Researcher at VMware Research. Students
Alumni
TeachingSpring 2018: Distributed Systems: CS 380DFall 2017: Virtualization: CS 378 Fall 2016: Graduate Operating Systems: CS 380L Fall 2014: Back at Wisconsin: Introduction to Operating Systems (CS 537)
ServicePC Member for:
Reviewer for TOCS, TACO, TDSC, TOS NSF Panelist in 2018 NewsMar 2018: I was awarded a Google Faculty Research Award to work on write-optimized infrastructure!Feb 2018: Our work on Protocol-Aware Recovery was featured in the Morning Paper! Feb 2018: Our work on protocol-aware recovery was awarded one of the best Best Paper Awards at FAST 2018! Jan 2018: Awarded the NSF CAREER Award for project on building IO-efficient infrastructure! Dec 2017: Ashlie Martinez, the undergrad leading the CrashMonkey project, was selected as one of the three awardees of the CRA Best Undergraduate Award 2018! Congratulations Ashlie! Dec 2017: Our paper on protocol-aware recovery in consensus-based distributed storage systems was accepted to FAST 2018! Oct 2017: Invited to attend Facebook Systems and Networking Faculty Summit! Excited to tour the Fort Worth datacenter. Sep 2017: Students Pandian Raju and Jayashree Mohan were awarded scholarships to attend SOSP 2017. Congratulations! Sep 2017: Our poster on IO Amplification in Linux file systems was awarded Best Poster at ApSys 17! Congratulations Jayashree and Rohan! Sep 2017: Jayashree presented our work on the complexities in benchmarking SQLite at ApSys 17. Aug 2017: PebblesDB, our work on reducing IO amplification in key-value stores, was accepted to SOSP 2017!
TalksNov 2017. Presented PebblesDB at the Austin Industry-Academia Partnership.Nov 2017. Presented at Austin Liberal Arts and Science Academy (LASA) about the many facets of computer science. Jul 2017. Presented at NetApp, VMware, Uber, Facebook, and Google about reducing write amplification in LSM-based key-value stores. Jun 2017. Spoke to high school students as part of the First Bytes program! May 2017. Guest Lecture on Storage at Simon Peter's undergrad class on Multicore Operating Systems Implementation. Mar 2017. Talked about "Grad School and Research" to undergrads at the College of Engineering, Guindy (my alma mater). Mar 2017. Guest lecture on Optimistic Crash Consistency at Chris Rossbach's Advanced OS class. Dec 2016. Presented NVMove to HP engineers. Oct 2016. Guest Lecture on Storage at Simon Peter's graduate class on Multicore Operating Systems Implementation.
Awards
Awards won by members of research group
Work in ProgressAnalyzing IO Amplification in Linux File SystemsJayashree Mohan, Rohan Kadekodi, Vijay Chidambaram Poster at ApSys 17 ArXiV Preprint Best Poster Award Recent Publications (All)
TxFS: Leveraging File-System Crash Consistency to Provide
ACID Transactions
vFiber: Virtualizing Unused Optical Fibers (Extended Abstract)
Protocol-Aware Recovery for Consensus-Based Storage
PebblesDB: Building Key-Value Stores using Fragmented
Log-Structured Merge Trees
The Dangers and Complexities of Benchmarking SQLite
CrashMonkey: A Framework to Systematically Test File-System Crash Consistency
CC-Log: Drastically Reducing Storage Requirements for Robots
Using Classification and Compression
From Crash Consistency to Transactions
Application Crash Consistency and Performance with CCFS
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