I am a Senior Researcher in the Research in Software Engineering (RiSE) group at Microsoft Research. I obtained my PhD in Computer Science from College of Information and Computer Sciences, University of Massachusetts Amherst. I was advised by Prof. Arjun Guha and collaborated with Prof. Emery Berger and Prof. Marco Serafini from UMass Amherst, and the Parasail Team at Microsoft Research. I work at the intersection of Programming Languages, Systems, and High Performance Computing.
Email: ajangda <at> microsoft <dot> com
Public Profiles:
DBLP: http://dblp.uni-trier.de/pers/hc/j/Jangda:Abhinav
Google Scholar: https://scholar.google.com/citations?user=T1bu2_IAAAAJ&hl=en
LinkedIn: https://www.linkedin.com/in/abhijangda
Publications
Abhinav Jangda, Jun Huang, Guodong Liu, Amir Hossein Nodehi Sabet, Saeed Maleki, Youshan Miao, Madanlal Musuvathi, Todd Mytkowicz, Olli Sarikivi. Breaking the Computation and Communication Abstraction Barrier in Distributed Machine Learning Workloads. 27th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS 2022)
Abhinav Jangda, Sandeep Polisetty, Arjun Guha, and Marco Serafini. Accelerating Graph Sampling for Graph Machine Learning using GPUs. 16th European Conference on Systems (EuroSys 2021). Artifact Functional and Results Reproduced. [code][12min talk][20min talk]
Abhinav Jangda and Arjun Guha. Model based Warp Overlapped Tiling for Image Processing Programs on GPUs. International Conference on Parallel Architecture and Compilation Techniques 2020 (PACT 2020). Best Paper Award [code]
Abhinav Jangda and Uday Bondhugula. An Effective Fusion and Tile Size Model for PolyMage. ACM Transactions on Programming Languages and Systems (TOPLAS), Vol 43, Issue 3, November 2020. (Extended version of PPoPP 2018 paper) [code]
Abhinav Jangda, Donald Pinckney, Yuriy Brun, and Arjun Guha. Formal Foundations of Serverless Computing. ACM SIGPLAN Conference on Object Oriented Programming, Systems, Languages and Applications (OOPSLA), 2019 ACM SIGPLAN Distinguished Paper Award [code][talk video]
Abhinav Jangda, Bobby Powers, Emery D. Berger, and Arjun Guha. Not so fast: Analyzing the Performance of WebAssembly vs. Native Code. 2019 USENIX Annual Technical Conference (USENIX ATC' 2019) Invited for USENIX ;login: article [code][lightning talk video][talk video]
Phitchaya Mangpo Phothilimthana, Archibald Samuel Elliott, An Wang, Abhinav Jangda, Bastian Hagedorn, Henrik Barthels, Samuel J. Kaufman, Vinod Grover, Emina Torlak, and Rastislav Bodik. Swizzle Inventor: Data Movement Synthesis for GPU Kernels. 24th International Conference on Architectural Support for Programming Languages and Operating Systems [code][lightning talk video]
Abhinav Jangda and Uday Bondhugula. An Effective Fusion and Tile Size Model for Optimizing Image Processing Pipelines. ACM SIGPLAN symposium on Principles and Practice of Parallel Programming (PPoPP), Feb 2018 Artifact Functional and Results Reproduced [code]
Abhinav Jangda and Greta Yorsh. Unbounded Superoptimization. ACM Symposium on New Ideas in Programming and Reflections on Software 2017 (Onward 2017)
Abhinav Jangda and Rupesh Nasre. FastCollect: Offloading Generational Garbage Collection on Integrated GPUs. International Conference on Compilers, Architectures and Synthesis For Embedded Systems (CASES), ESWeek 2016
Abhinav Jangda, Mohit Mishra, and Bjorn De Sutter. Adaptive Just-In-Time Code Diversification. Proceedings of the Second ACM Workshop on Moving Target Defense, pages 49-53, Oct 2015
Technical Articles
Abhinav Jangda, Bobby Powers, Emery D. Berger, and Arjun Guha. Not so fast: Analyzing the Performance of WebAssembly vs. Native Code. USENIX; login: Fall 2019 Issue
Work Experience
University of Massachusetts, Amherst
Research Assistant (Sept 2017 - Present)
Advisor: Prof. Arjun Guha
Parasail Team, RiSE Group, Microsoft Research, Redmond, WA
Research Intern (June 2021 - August 2021)
Manager: Dr. Saeed Maleki
Parasail Team, RiSE Group, Microsoft Research, Redmond, WA
Research Intern (June 2020 - August 2020)
Manager: Dr. Saeed Maleki
Deep Learning Compiler Team, NVIDIA
Software Engineering Intern (March 2020 - April 2020)
Manager: Vinod Grover
Deep Learning Compiler Team, NVIDIA
Software Engineering Intern (June 2018 - August 2018)
Manager: Vinod Grover
Multi-Core Computing Lab, Indian Institute of Science, Bangalore
Research Associate (Jun 2016 - Aug 2017)
Supervisor: Prof. Uday Kumar Reddy B
School of Computing Sciences, University of Glasgow
Visiting Student Researcher (Feb 2016 - Mar 2016)
Mentor: Dr. Jeremy Singer
Institute for Software Research, Carnegie Mellon University
Visiting Student Research (May 2015 - July 2015)
Mentor: Prof. Jonathan Aldrich
GNOME Foundation, Google Summer of Code
Internship (May 2014 - Aug 2014)
Qualcomm India Pvt Ltd, Bangalore
Internship (May 2014 - Aug 2014)
Python Software Foundation, Google Summer of Code
Internship (May 2013 - Aug 2013)
Service
Program Committee of HPDC 2023 and EuroPar 2023
Invited to Review for IMC 2021, IEEE TPDS 2022
Extended Review Committee of ASPLOS 2021 and OOPSLA 2023.
Shadow Program Committee of EuroSys 2020
Artifact Evaluation Committee of OOPSLA 2020, PLDI 2020, and SOSP 2019
Awards and Grants
Best Paper Award at PACT 2020
Facebook Systems for Machine Learning Grant for NextDoor 2020
ACM SIGPLAN Distinguished Paper Award at OOPSLA 2019
Invited Article for USENIX ;login: Fall 2019
Student Travel Grant for attending USENIX ATC, SPLASH, and PPoPP