Changwan Hong

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 25

Top Topics

Data Transformation

Matrix Multiplication

Top Venues

Publications

Willow Ahrens, Teodoro Fields Collin, Radha Patel, Kyle Deeds, Changwan Hong, Saman P. Amarasinghe
Finch: Sparse and Structured Array Programming with Control Flow. CoRR (2024)
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)
Ajay Brahmakshatriya, Yunming Zhang, Changwan Hong, Shoaib Kamil, Julian Shun, Saman P. Amarasinghe
Compiling Graph Applications for GPU s with GraphIt. CGO (2021)
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)
Changwan Hong, Laxman Dhulipala, Julian Shun
Exploring the Design Space of Static and Incremental Graph Connectivity Algorithms on GPUs. PACT (2020)
Ajay Brahmakshatriya, Yunming Zhang, Changwan Hong, Shoaib Kamil, Julian Shun, Saman P. Amarasinghe
Compliation Techniques for Graphs Algorithms on GPUs. CoRR (2020)
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) (2020)
Peng Jiang, Changwan Hong, Gagan Agrawal
A novel data transformation and execution strategy for accelerating sparse matrix multiplication on GPUs. PPoPP (2020)
Laxman Dhulipala, Changwan Hong, Julian Shun
ConnectIt: A Framework for Static and Incremental Parallel Graph Connectivity Algorithms. CoRR (2020)
Changwan Hong, Laxman Dhulipala, Julian Shun
Exploring the Design Space of Static and Incremental Graph Connectivity Algorithms on GPUs. CoRR (2020)
Ryan Senanayake, Fredrik Kjolstad, Changwan Hong, Shoaib Kamil, Saman P. Amarasinghe
A Unified Iteration Space Transformation Framework for Sparse and Dense Tensor Algebra. CoRR (2020)
Laxman Dhulipala, Changwan Hong, Julian Shun
ConnectIt: A Framework for Static and Incremental Parallel Graph Connectivity Algorithms. Proc. VLDB Endow. 14 (4) (2020)
Changwan Hong, Aravind Sukumaran-Rajam, Israt Nisa, Kunal Singh, P. Sadayappan
Adaptive sparse tiling for sparse matrix multiplication. PPoPP (2019)
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)
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)
Israt Nisa, Aravind Sukumaran-Rajam, Süreyya Emre Kurt, Changwan Hong, P. Sadayappan
Sampled Dense Matrix Multiplication for High-Performance Machine Learning. HiPC (2018)
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)
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)
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)
Changwan Hong, Aravind Sukumaran-Rajam, Jinsung Kim, P. Sadayappan
MultiGraph: Efficient Graph Processing on GPUs. PACT (2017)
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)
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)
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)
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) (2016)
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)