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Peng Jiang
Peng Jiang
Verified email at uiowa.edu - Homepage
Title
Cited by
Cited by
Year
A linear speedup analysis of distributed deep learning with sparse and quantized communication
P Jiang, G Agrawal
Advances in Neural Information Processing Systems 31, 2018
2122018
A novel data transformation and execution strategy for accelerating sparse matrix multiplication on GPUs
P Jiang, C Hong, G Agrawal
Proceedings of the 25th ACM SIGPLAN symposium on principles and practice of …, 2020
492020
Exploiting recent simd architectural advances for irregular applications
L Chen, P Jiang, G Agrawal
Proceedings of the 2016 International Symposium on Code Generation and …, 2016
492016
Accelerating sparse cnn inference on gpus with performance-aware weight pruning
MA Rumi, X Ma, Y Wang, P Jiang
Proceedings of the ACM International Conference on Parallel Architectures …, 2020
292020
Combining SIMD and Many/Multi-core parallelism for finite state machines with enumerative speculation
P Jiang, G Agrawal
Proceedings of the 22nd ACM SIGPLAN Symposium on Principles and Practice of …, 2017
282017
Reusing data reorganization for efficient simd parallelization of adaptive irregular applications
P Jiang, L Chen, G Agrawal
Proceedings of the 2016 International Conference on Supercomputing, 1-10, 2016
252016
Efficient SIMD and MIMD parallelization of hash-based aggregation by conflict mitigation
P Jiang, G Agrawal
Proceedings of the International Conference on Supercomputing, 1-11, 2017
242017
Conflict-free vectorization of associative irregular applications with recent SIMD architectural advances
P Jiang, G Agrawal
Proceedings of the 2018 International Symposium on Code Generation and …, 2018
152018
Exposing and exploiting fine-grained block structures for fast and accurate sparse training
P Jiang, L Hu, S Song
Advances in Neural Information Processing Systems 35, 38345-38357, 2022
132022
Revealing parallel scans and reductions in recurrences through function reconstruction
P Jiang, L Chen, G Agrawal
Proceedings of the 27th International Conference on Parallel Architectures …, 2018
122018
Rethinking graph data placement for graph neural network training on multiple GPUs
S Song, P Jiang
Proceedings of the 36th ACM International Conference on Supercomputing, 1-10, 2022
102022
A methodology for characterizing sparse datasets and its application to simd performance prediction
G Zhu, P Jiang, G Agrawal
2019 28th International Conference on Parallel Architectures and Compilation …, 2019
82019
Accelerating distributed stochastic gradient descent with adaptive periodic parameter averaging: Poster
P Jiang, G Agrawal
Proceedings of the 24th Symposium on Principles and Practice of Parallel …, 2019
82019
Communication-efficient sampling for distributed training of graph convolutional networks
P Jiang, MA Rumi
arXiv preprint arXiv:2101.07706, 2021
62021
Scaling out speculative execution of finite-state machines with parallel merge
Y Xia, P Jiang, G Agrawal
Proceedings of the 25th ACM SIGPLAN Symposium on principles and practice of …, 2020
62020
Enabling prefix sum parallelism pattern for recurrences with principled function reconstruction
Y Xia, P Jiang, G Agrawal
Proceedings of the 28th International Conference on Compiler Construction, 17-28, 2019
62019
Scaling and selecting gpu methods for all pairs shortest paths (apsp) computations
Y Xia, P Jiang, G Agrawal, R Ramnath
2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2022
42022
Exploring pim architecture for high-performance graph pattern mining
J Su, L He, P Jiang, R Wang
IEEE computer architecture letters 20 (2), 114-117, 2021
42021
Scaling sparse matrix multiplication on cpu-gpu nodes
Y Xia, P Jiang, G Agrawal, R Ramnath
2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2021
42021
End-to-End LU Factorization of Large Matrices on GPUs
Y Xia, P Jiang, G Agrawal, R Ramnath
Proceedings of the 28th ACM SIGPLAN Annual Symposium on Principles and …, 2023
32023
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