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Charith Mendis
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- affiliation: University of Illinois at Urbana-Champaign, IL, USA
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2020 – today
- 2024
- [j2]Stefanos Baziotis
, Daniel D. Kang
Dias: Dynamic Rewriting of Pandas Code. Proc. ACM Manag. Data 2(1): 58:1-58:27 (2024) - [c25]Akash Kothari
Hydride: A Retargetable and Extensible Synthesis-based Compiler for Modern Hardware Architectures. ASPLOS (2) 2024: 514-529 - [c24]Yufeng Wang
TGLite: A Lightweight Programming Framework for Continuous-Time Temporal Graph Neural Networks. ASPLOS (2) 2024: 1183-1199 - [c23]Charles Block
Two-Face: Combining Collective and One-Sided Communication for Efficient Distributed SpMM. ASPLOS (2) 2024: 1200-1217 - [c22]Ruijie Wang, Wanyu Zhao, Dachun Sun, Charith Mendis, Tarek F. Abdelzaher:
Towards Efficient Temporal Graph Learning: Algorithms, Frameworks, and Tools. CIKM 2024: 5530-5533 - [c21]Isha Chaudhary, Alex Renda, Charith Mendis, Gagandeep Singh:
COMET: Neural Cost Model Explanation Framework. MLSys 2024 - [c20]Ruijie Wang
TGOnline: Enhancing Temporal Graph Learning with Adaptive Online Meta-Learning. SIGIR 2024: 1659-1669 - [i14]Avaljot Singh, Yasmin Sarita, Charith Mendis, Gagandeep Singh:
ConstraintFlow: A DSL for Specification and Verification of Neural Network Analyses. CoRR abs/2403.18729 (2024) - [i13]Ahan Gupta, Yueming Yuan, Devansh Jain
SPLAT: A framework for optimised GPU code-generation for SParse reguLar ATtention. CoRR abs/2407.16847 (2024) - 2023
- [c19]Jaeyeon Won, Charith Mendis
WACO: Learning Workload-Aware Co-optimization of the Format and Schedule of a Sparse Tensor Program. ASPLOS (2) 2023: 920-934 - [c18]Gerasimos Gerogiannis
SPADE: A Flexible and Scalable Accelerator for SpMM and SDDMM. ISCA 2023: 19:1-19:15 - [c17]Tarek F. Abdelzaher, Matthew Caesar, Charith Mendis, Klara Nahrstedt, Mani Srivastava, Minlan Yu:
Challenges in Metaverse Research: An Internet of Things Perspective. MetaCom 2023: 161-170 - [c16]Jaeyeon Won, Changwan Hong, Charith Mendis, Joel S. Emer, Saman P. Amarasinghe:
Unified Convolution Framework: A compiler-based approach to support sparse convolutions. MLSys 2023 - [c15]Kaidi Cao, Phitchaya Mangpo Phothilimthana, Sami Abu-El-Haija, Dustin Zelle, Yanqi Zhou, Charith Mendis, Jure Leskovec, Bryan Perozzi:
Learning Large Graph Property Prediction via Graph Segment Training. NeurIPS 2023 - [c14]Phitchaya Mangpo Phothilimthana, Sami Abu-El-Haija, Kaidi Cao, Bahare Fatemi, Michael Burrows, Charith Mendis, Bryan Perozzi:
TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs. NeurIPS 2023 - [c13]Yufeng Wang, Charith Mendis
TGOpt: Redundancy-Aware Optimizations for Temporal Graph Attention Networks. PPoPP 2023: 354-368 - [e1]Charith Mendis, Lawrence Rauchwerger:
Languages and Compilers for Parallel Computing - 35th International Workshop, LCPC 2022, Chicago, IL, USA, October 12-14, 2022, Revised Selected Papers. Lecture Notes in Computer Science 13829, Springer 2023, ISBN 978-3-031-31444-5 [contents] - [i12]Isha Chaudhary, Alex Renda, Charith Mendis, Gagandeep Singh:
CoMEt: x86 Cost Model Explanation Framework. CoRR abs/2302.06836 (2023) - [i11]Stefanos Baziotis, Daniel Kang, Charith Mendis:
Dias: Dynamic Rewriting of Pandas Code. CoRR abs/2303.16146 (2023) - [i10]Kaidi Cao, Phitchaya Mangpo Phothilimthana, Sami Abu-El-Haija, Dustin Zelle, Yanqi Zhou, Charith Mendis, Jure Leskovec, Bryan Perozzi:
Learning Large Graph Property Prediction via Graph Segment Training. CoRR abs/2305.12322 (2023) - [i9]Damitha Lenadora, Vimarsh Sathia, Gerasimos Gerogiannis, Serif Yesil, Josep Torrellas, Charith Mendis:
Input-sensitive dense-sparse primitive compositions for GNN acceleration. CoRR abs/2306.15155 (2023) - [i8]Ahan Gupta, Yueming Yuan, Yanqi Zhou, Charith Mendis:
FLuRKA: Fast fused Low-Rank & Kernel Attention. CoRR abs/2306.15799 (2023) - [i7]Phitchaya Mangpo Phothilimthana, Sami Abu-El-Haija, Kaidi Cao, Bahare Fatemi, Charith Mendis, Bryan Perozzi:
TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs. CoRR abs/2308.13490 (2023) - 2022
- [c12]Ondrej Sýkora, Phitchaya Mangpo Phothilimthana, Charith Mendis
GRANITE: A Graph Neural Network Model for Basic Block Throughput Estimation. IISWC 2022: 14-26 - [c11]Yishen Chen, Charith Mendis
All you need is superword-level parallelism: systematic control-flow vectorization with SLP. PLDI 2022: 301-315 - [i6]Ondrej Sýkora, Phitchaya Mangpo Phothilimthana, Charith Mendis, Amir Yazdanbakhsh:
GRANITE: A Graph Neural Network Model for Basic Block Throughput Estimation. CoRR abs/2210.03894 (2022) - 2021
- [c10]Yishen Chen, Charith Mendis, Michael Carbin, Saman P. Amarasinghe
VeGen: a vectorizer generator for SIMD and beyond. ASPLOS 2021: 902-914 - [c9]Samuel J. Kaufman, Phitchaya Mangpo Phothilimthana, Yanqi Zhou, Charith Mendis, Sudip Roy, Amit Sabne, Mike Burrows:
A Learned Performance Model for Tensor Processing Units. MLSys 2021 - 2020
- [c8]Alex Renda, Yishen Chen, Charith Mendis, Michael Carbin:
DiffTune: Optimizing CPU Simulator Parameters with Learned Differentiable Surrogates. MICRO 2020: 442-455 - [i5]Alex Renda, Yishen Chen, Charith Mendis, Michael Carbin:
DiffTune: Optimizing CPU Simulator Parameters with Learned Differentiable Surrogates. CoRR abs/2010.04017 (2020)
2010 – 2019
- 2019
- [c7]Charith Mendis, Ajay Jain, Paras Jain, Saman P. Amarasinghe
Revec: program rejuvenation through revectorization. CC 2019: 29-41 - [c6]Charith Mendis, Alex Renda, Saman P. Amarasinghe, Michael Carbin:
Ithemal: Accurate, Portable and Fast Basic Block Throughput Estimation using Deep Neural Networks. ICML 2019: 4505-4515 - [c5]Yishen Chen, Ajay Brahmakshatriya, Charith Mendis, Alex Renda, Eric Atkinson, Ondrej Sýkora, Saman P. Amarasinghe, Michael Carbin:
BHive: A Benchmark Suite and Measurement Framework for Validating x86-64 Basic Block Performance Models. IISWC 2019: 167-177 - [c4]Charith Mendis, Cambridge Yang, Yewen Pu, Saman P. Amarasinghe, Michael Carbin:
Compiler Auto-Vectorization with Imitation Learning. NeurIPS 2019: 14598-14609 - [i4]Charith Mendis, Ajay Jain, Paras Jain, Saman P. Amarasinghe:
Revec: Program Rejuvenation through Revectorization. CoRR abs/1902.02816 (2019) - 2018
- [j1]Charith Mendis, Saman P. Amarasinghe
goSLP: globally optimized superword level parallelism framework. Proc. ACM Program. Lang. 2(OOPSLA): 110:1-110:28 (2018) - [i3]Charith Mendis, Saman P. Amarasinghe:
goSLP: Globally Optimized Superword Level Parallelism Framework. CoRR abs/1804.08733 (2018) - [i2]Charith Mendis, Saman P. Amarasinghe, Michael Carbin:
Ithemal: Accurate, Portable and Fast Basic Block Throughput Estimation using Deep Neural Networks. CoRR abs/1808.07412 (2018) - 2017
- [c3]Yunming Zhang, Vladimir Kiriansky, Charith Mendis, Saman P. Amarasinghe, Matei Zaharia
Making caches work for graph analytics. IEEE BigData 2017: 293-302 - 2016
- [c2]Charith Mendis, Jasha Droppo
Parallelizing WFST speech decoders. ICASSP 2016: 5325-5329 - [i1]Yunming Zhang, Vladimir Kiriansky, Charith Mendis, Matei Zaharia, Saman P. Amarasinghe:
Optimizing Cache Performance for Graph Analytics. CoRR abs/1608.01362 (2016) - 2015
- [c1]Charith Mendis, Jeffrey Bosboom
Helium: lifting high-performance stencil kernels from stripped x86 binaries to halide DSL code. PLDI 2015: 391-402
Coauthor Index
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last updated on 2024-11-15 19:35 CET by the dblp team
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