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Keval Vora

Assistant Professor
School of Computing Science
Simon Fraser University
TASC 1 9419, 8888 University Drive
Burnaby, BC V5A 1S6
Canada
Email: keval@sfu.ca
Tel: (778) 782-5295
Open positions: I am looking for Ph.D. students interested in systems research, at the intersection of parallel/distributed computing and big data processing. If you are interested in building scalable software solutions for challenging problems in large-scale and high-performance computing, please email me a brief description about your work interests along with a copy of your CV.
My research area is Parallel & Distributed Computing with focus on issues related to Performance, Scalability, Programmability and Fault Tolerance. My current work lies at an intersection of Large-Scale Graph Processing Systems and (Relaxed) Consistency Semantics.
I received my PhD in Computer Science from University of California, Riverside, where my PhD advisor was Rajiv Gupta. I also worked as a visitng student researcher at University of California, Irvine where I worked with Harry Xu.
SELECTED PUBLICATIONS
(Click here for complete list of publications.)
  1. [EuroSys'20] Peregrine: A Pattern-Aware Graph Mining System (18.4%)
  2. [ATC'19] Lumos: Dependency-Driven Disk-based Graph Processing (19.9%)
  3. [EuroSys'19] GraphBolt: Dependency-Driven Synchronous Processing of Streaming Graphs (21.7%)
  4. [ASPLOS'19] PnP: Pruning and Prediction for Point-To-Point Iterative Graph Analytics (21.14%)
  5. [ASPLOS'17] KickStarter: Fast and Accurate Computations on Streaming Graphs via Trimmed Approximations (17.45%)
  6. [ASPLOS'17] CoRAL: Confined Recovery in Distributed Asynchronous Graph Processing (17.45%)
  7. [ATC'16] Load the Edges You Need: A Generic I/O Optimization for Disk-based Graph Processing (17.67%)
  8. [TACO'16] Synergistic Analysis of Evolving Graphs
  9. [HPDC'16] Efficient Processing of Large Graphs via Input Reduction (15.5%)
  10. [OOPSLA'14] ASPIRE: Exploiting Asynchronous Parallelism in Iterative Algorithms using a Relaxed Consistency based DSM (27.96%)
  11. [HPDC'14] CuSha: Vertex-Centric Graph Processing on GPUs (16.15%)
SOFTWARE
(Click here for PDCL on GitHub.)
1.  Peregrine
2.  Lumos
3.  GraphBolt
4.  KickStarter (now part of GraphBolt)
5.  OMR
    TEACHING
    • Fall 2019: CMPT 886: Parallel & Distributed Computing
    • Fall 2019: CMPT 431: Distributed Systems
    • Previous Courses
      • Spring 2019: CMPT 886/479: Large-Scale Graph Processing
      • Fall 2018: CMPT 300: Operating Systems (D1),   CMPT 300: Operating Systems (D2)
      • Spring 2018: CMPT 300: Operating Systems,   CMPT 886/479: Large-Scale Graph Processing