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Abhinav Jangda
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2020 – today
- 2024
- [j5]Federico Cassano
, John Gouwar
Knowledge Transfer from High-Resource to Low-Resource Programming Languages for Code LLMs. Proc. ACM Program. Lang. 8(OOPSLA2): 677-708 (2024) - [c11]Abhinav Jangda, Saeed Maleki, Maryam Mehri Dehnavi, Madan Musuvathi, Olli Saarikivi:
A Framework for Fine-Grained Synchronization of Dependent GPU Kernels. CGO 2024: 93-105 - [c10]Abhinav Jangda
Fast Kronecker Matrix-Matrix Multiplication on GPUs. PPoPP 2024: 390-403 - [i11]Abhinav Jangda, Mohit Yadav:
Fast Kronecker Matrix-Matrix Multiplication on GPUs. CoRR abs/2401.10187 (2024) - 2023
- [j4]Federico Cassano
MultiPL-E: A Scalable and Polyglot Approach to Benchmarking Neural Code Generation. IEEE Trans. Software Eng. 49(7): 3675-3691 (2023) - [i10]Abhinav Jangda, Saeed Maleki, Maryam Mehri Dehnavi, Madan Musuvathi, Olli Saarikivi:
A Framework for Fine-Grained Synchronization of Dependent GPU Kernels. CoRR abs/2305.13450 (2023) - [i9]Federico Cassano, John Gouwar, Francesca Lucchetti, Claire Schlesinger, Carolyn Jane Anderson, Michael Greenberg, Abhinav Jangda, Arjun Guha:
Knowledge Transfer from High-Resource to Low-Resource Programming Languages for Code LLMs. CoRR abs/2308.09895 (2023) - 2022
- [c9]Abhinav Jangda, Jun Huang, Guodong Liu, Amir Hossein Nodehi Sabet, Saeed Maleki, Youshan Miao
Breaking the computation and communication abstraction barrier in distributed machine learning workloads. ASPLOS 2022: 402-416 - [i8]Federico Cassano, John Gouwar, Daniel Nguyen, Sydney Nguyen, Luna Phipps-Costin, Donald Pinckney, Ming-Ho Yee, Yangtian Zi, Carolyn Jane Anderson, Molly Q. Feldman, Arjun Guha, Michael Greenberg
A Scalable and Extensible Approach to Benchmarking NL2Code for 18 Programming Languages. CoRR abs/2208.08227 (2022) - 2021
- [c8]Abhinav Jangda, Sandeep Polisetty, Arjun Guha
Accelerating graph sampling for graph machine learning using GPUs. EuroSys 2021: 311-326 - [i7]Abhinav Jangda, Jun Huang, Guodong Liu, Amir Hossein Nodehi Sabet, Saeed Maleki, Youshan Miao, Madanlal Musuvathi, Todd Mytkowicz, Olli Saarikivi:
CoCoNet: Co-Optimizing Computation and Communication for Distributed Machine Learning. CoRR abs/2105.05720 (2021) - 2020
- [j3]Abhinav Jangda, Uday Bondhugula:
An Effective Fusion and Tile Size Model for PolyMage. ACM Trans. Program. Lang. Syst. 42(3): 12:1-12:27 (2020) - [c7]Abhinav Jangda, Arjun Guha:
Model-Based Warp Overlapped Tiling for Image Processing Programs on GPUs. PACT 2020: 317-328 - [i6]Abhinav Jangda, Sandeep Polisetty, Arjun Guha, Marco Serafini:
NextDoor: GPU-Based Graph Sampling for Graph Machine Learning. CoRR abs/2009.06693 (2020)
2010 – 2019
- 2019
- [j2]Abhinav Jangda, Donald Pinckney
Formal foundations of serverless computing. Proc. ACM Program. Lang. 3(OOPSLA): 149:1-149:26 (2019) - [j1]Abhinav Jangda, Bobby Powers, Emery D. Berger
Not So Fast: Analyzing the Performance of WebAssembly vs. Native Code. login Usenix Mag. 44(3) (2019) - [c6]Phitchaya Mangpo Phothilimthana, Archibald Samuel Elliott, An Wang, Abhinav Jangda, Bastian Hagedorn, Henrik Barthels, Samuel J. Kaufman, Vinod Grover, Emina Torlak, Rastislav Bodík:
Swizzle Inventor: Data Movement Synthesis for GPU Kernels. ASPLOS 2019: 65-78 - [c5]Abhinav Jangda, Bobby Powers, Emery D. Berger
Not So Fast: Analyzing the Performance of WebAssembly vs. Native Code. USENIX ATC 2019: 107-120 - [i5]Abhinav Jangda, Gaurav Anand:
Predicting Variable Types in Dynamically Typed Programming Languages. CoRR abs/1901.05138 (2019) - [i4]Abhinav Jangda, Bobby Powers, Arjun Guha, Emery D. Berger:
Mind the Gap: Analyzing the Performance of WebAssembly vs. Native Code. CoRR abs/1901.09056 (2019) - [i3]Abhinav Jangda, Donald Pinckney, Samuel Baxter, Breanna Devore-McDonald, Joseph Spitzer, Yuriy Brun, Arjun Guha:
Formal Foundations of Serverless Computing. CoRR abs/1902.05870 (2019) - [i2]Abhinav Jangda, Arjun Guha:
Model-Based Warp-Level Tiling for Image Processing Programs on GPUs. CoRR abs/1909.07190 (2019) - 2018
- [c4]Abhinav Jangda, Uday Bondhugula:
An effective fusion and tile size model for optimizing image processing pipelines. PPoPP 2018: 261-275 - 2017
- [c3]Abhinav Jangda, Greta Yorsh:
Unbounded superoptimization. Onward! 2017: 78-88 - [c2]Abhinav Jangda, Mohit Mishra:
RandHeap: Heap Randomization for Mitigating Heap Spray Attacks in Virtual Machines. PST 2017: 169-180 - 2015
- [c1]Abhinav Jangda, Mohit Mishra, Bjorn De Sutter:
Adaptive Just-In-Time Code Diversification. MTD@CCS 2015: 49-53 - [i1]Abhinav Jangda:
Block-Level Parallelism in Parsing Block Structured Languages. CoRR abs/1509.08068 (2015)
Coauthor Index
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