I am a 3rd-year PhD student working with Dr. Keshav Pingali at The University of Texas at Austin. I mainly work in distributed graph analytics and associated algorithms. My research interest is basically looking into ways to make algorithms run faster, whether it be through algorithmic improvements or through leveraging existing hardware in new ways.
I received both my Bachelor's of Science and my Master's of Science in Computer Science in Spring 2017 at The University of Texas at Austin under the Integrated BS/MS program in the Department of Computer Science. My ultimate goal is to go into academia, but we'll see what the future has in store for me.
I have worked as an intern at Intel Corporation where I developed graph applications using CUDA and Intel's DPC++ and analyzed their performance. I have also interned at KatanaGraph, a startup that uses some of the research that I have been involved in over the years: there I co-designed and developed parts of the initial KatanaGraph graph querying engine.
Links from the title of a paper go to the "official" conference/proceedings PDF provider (if it exists), while the PDF link goes to a local copy of the paper. If the official provider doesn't give public access, the paper will have a local copy you can download for non-commercial purposes (...eventually, if one doesn't already exist).
Paper errata can be found here. There will also be an "Errata" link on applicable papers below.
A Study of APIs for Graph Analytics Workloads
Hochan Lee, David Wong, Loc Hoang, Roshan Dathathri, Gurbinder Gill, Vishwesh Jatala, David Kuck, Keshav Pingali
To appear in IISWC 2020 IEEE International Symposium on Workload Characterization, October 2020
Single Machine Graph Analytics on Massive Datasets Using Intel Optane DC Persistent Memory
Gurbinder Gill, Roshan Dathathri, Loc Hoang, Ramesh Peri, Keshav Pingali
VLDB 2020 46th International Conference on Very Large Data Bases, August 2020
A Study of Graph Analytics for Massive Datasets on Large-Scale Distributed GPUs
Vishwesh Jatala, Roshan Dathathri, Gurbinder Gill, Loc Hoang, V. Krishna Nandivada, Keshav Pingali
IPDPS 2020 34th International Parallel and Distributed Processing Symposium, May 2020
Gluon-Async: A Bulk-Asynchronous System for Distributed and Heterogeneous Graph Analytics
Roshan Dathathri, Gurbinder Gill, Loc Hoang, Hoang-Vu Dang, Vishwesh Jatala, V. Krishna Nandivada, Marc Snir, Keshav Pingali
PACT 2019 28th International Conference on Parallel Architectures and Compilation Techniques, September 2019
Best Paper Nominee
DistTC: High Performance Distributed Triangle Counting
Loc Hoang*, Vishwesh Jatala*, Xuhao Chen, Udit Agarwal, Roshan Dathathri, Gurbinder Gill, Keshav Pingali
*Authors contributed equally
HPEC 2019 23rd IEEE High Performance Extreme Computing, Graph Challenge, September 2019
Student Innovation Award
A Study of Partitioning Policies for Graph Analytics on Large-scale Distributed Platforms
Gurbinder Gill, Roshan Dathathri, Loc Hoang, Keshav Pingali
VLDB 2019 45th International Conference on Very Large Data Bases, August 2019
CuSP: A Customizable Streaming Edge Partitioner for Distributed Graph Analytics
Loc Hoang, Roshan Dathathri, Gurbinder Gill, Keshav Pingali
IPDPS 2019 33rd IEEE International Parallel and Distributed Processing Symposium, May 2019
Email: shorter of first and last name at cs.utexas.edu
I don't have a public presence on social media (this includes LinkedIn).
Hobbies are mostly video games and reading. I used to watch a lot of anime, but these days I really don't watch anything.
Last update: September 16, 2020