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ORCIDChangwan Hong
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2020 – today
- 2024
[i5]Willow Ahrens, Teodoro Fields Collin, Radha Patel, Kyle Deeds, Changwan Hong, Saman P. Amarasinghe:
Finch: Sparse and Structured Array Programming with Control Flow. CoRR abs/2404.16730 (2024)- 2023
- [c17]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 - 2021
- [c16]Ajay Brahmakshatriya, Yunming Zhang, Changwan Hong, Shoaib Kamil, Julian Shun
, Saman P. Amarasinghe:
Compiling Graph Applications for GPU s with GraphIt. CGO 2021: 248-261 - [c15]Ajay Brahmakshatriya, Emily Furst, Victor A. Ying, Claire Hsu, Changwan Hong, Max Ruttenberg, Yunming Zhang, Dai Cheol Jung, Dustin Richmond, Michael B. Taylor, Julian Shun, Mark Oskin, Daniel Sánchez, Saman P. Amarasinghe:
Taming the Zoo: The Unified GraphIt Compiler Framework for Novel Architectures. ISCA 2021: 429-442 - 2020
- [j3]Ryan Senanayake, Changwan Hong, Ziheng Wang, Amalee Wilson, Stephen Chou, Shoaib Kamil, Saman P. Amarasinghe, Fredrik Kjolstad:
A sparse iteration space transformation framework for sparse tensor algebra. Proc. ACM Program. Lang. 4(OOPSLA): 158:1-158:30 (2020) - [j2]Laxman Dhulipala, Changwan Hong, Julian Shun:
ConnectIt: A Framework for Static and Incremental Parallel Graph Connectivity Algorithms. Proc. VLDB Endow. 14(4): 653-667 (2020) - [c14]Changwan Hong, Laxman Dhulipala, Julian Shun:
Exploring the Design Space of Static and Incremental Graph Connectivity Algorithms on GPUs. PACT 2020: 55-69 - [c13]Peng Jiang, Changwan Hong, Gagan Agrawal:
A novel data transformation and execution strategy for accelerating sparse matrix multiplication on GPUs. PPoPP 2020: 376-388 - [i4]Ryan Senanayake, Fredrik Kjolstad, Changwan Hong, Shoaib Kamil, Saman P. Amarasinghe:
A Unified Iteration Space Transformation Framework for Sparse and Dense Tensor Algebra. CoRR abs/2001.00532 (2020) - [i3]Laxman Dhulipala, Changwan Hong, Julian Shun:
ConnectIt: A Framework for Static and Incremental Parallel Graph Connectivity Algorithms. CoRR abs/2008.03909 (2020) - [i2]Changwan Hong, Laxman Dhulipala, Julian Shun:
Exploring the Design Space of Static and Incremental Graph Connectivity Algorithms on GPUs. CoRR abs/2008.11839 (2020) - [i1]Ajay Brahmakshatriya, Yunming Zhang, Changwan Hong, Shoaib Kamil, Julian Shun, Saman P. Amarasinghe:
Compliation Techniques for Graphs Algorithms on GPUs. CoRR abs/2012.07990 (2020)
2010 – 2019
- 2019
- [c12]Changwan Hong, Aravind Sukumaran-Rajam, Israt Nisa, Kunal Singh, P. Sadayappan:
Adaptive sparse tiling for sparse matrix multiplication. PPoPP 2019: 300-314 - 2018
- [c11]Israt Nisa, Aravind Sukumaran-Rajam, Süreyya Emre Kurt, Changwan Hong, P. Sadayappan:
Sampled Dense Matrix Multiplication for High-Performance Machine Learning. HiPC 2018: 32-41 - [c10]Changwan Hong, Aravind Sukumaran-Rajam, Bortik Bandyopadhyay, Jinsung Kim, Süreyya Emre Kurt, Israt Nisa, Shivani Sabhlok, Ümit V. Çatalyürek, Srinivasan Parthasarathy, P. Sadayappan:
Efficient sparse-matrix multi-vector product on GPUs. HPDC 2018: 66-79 - [c9]Jinsung Kim, Aravind Sukumaran-Rajam, Changwan Hong, Ajay Panyala, Rohit Kumar Srivastava, Sriram Krishnamoorthy, P. Sadayappan:
Optimizing Tensor Contractions in CCSD(T) for Efficient Execution on GPUs. ICS 2018: 96-106 - [c8]Jyothi Vedurada, Arjun Suresh, Aravind Sukumaran-Rajam, Jinsung Kim, Changwan Hong, Ajay Panyala, Sriram Krishnamoorthy, V. Krishna Nandivada, Rohit Kumar Srivastava, P. Sadayappan:
TTLG - An Efficient Tensor Transposition Library for GPUs. IPDPS 2018: 578-588 - [c7]Changwan Hong, Aravind Sukumaran-Rajam, Jinsung Kim, Prashant Singh Rawat, Sriram Krishnamoorthy, Louis-Noël Pouchet, Fabrice Rastello, P. Sadayappan:
GPU code optimization using abstract kernel emulation and sensitivity analysis. PLDI 2018: 736-751 - [c6]Changwan Hong, Aravind Sukumaran-Rajam, Jinsung Kim, Prashant Singh Rawat, Sriram Krishnamoorthy, Louis-Noël Pouchet, Fabrice Rastello, P. Sadayappan:
Performance modeling for GPUs using abstract kernel emulation. PPoPP 2018: 397-398 - 2017
- [c5]Changwan Hong, Aravind Sukumaran-Rajam, Jinsung Kim, P. Sadayappan:
MultiGraph: Efficient Graph Processing on GPUs. PACT 2017: 27-40 - [c4]Süreyya Emre Kurt, Vineeth Thumma, Changwan Hong, Aravind Sukumaran-Rajam, P. Sadayappan:
Characterization of Data Movement Requirements for Sparse Matrix Computations on GPUs. HiPC 2017: 283-293 - 2016
- [j1]Wenlei Bao, Changwan Hong, Sudheer Chunduri, Sriram Krishnamoorthy, Louis-Noël Pouchet, Fabrice Rastello, P. Sadayappan:
Static and Dynamic Frequency Scaling on Multicore CPUs. ACM Trans. Archit. Code Optim. 13(4): 51:1-51:26 (2016) - [c3]Prashant Singh Rawat, Changwan Hong, Mahesh Ravishankar, Vinod Grover, Louis-Noël Pouchet, Atanas Rountev, P. Sadayappan:
Resource Conscious Reuse-Driven Tiling for GPUs. PACT 2016: 99-111 - [c2]Changwan Hong, Wenlei Bao, Albert Cohen, Sriram Krishnamoorthy, Louis-Noël Pouchet, Fabrice Rastello, J. Ramanujam, P. Sadayappan:
Effective padding of multidimensional arrays to avoid cache conflict misses. PLDI 2016: 129-144 - [c1]Prashant Singh Rawat, Changwan Hong, Mahesh Ravishankar, Vinod Grover, Louis-Noël Pouchet, P. Sadayappan:
Effective resource management for enhancing performance of 2D and 3D stencils on GPUs. GPGPU@PPoPP 2016: 92-102
Coauthor Index
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