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Journal Articles
- 2022
[j1]Paolo D'Alberto
, Victor Wu, Aaron Ng, Rahul Nimaiyar, Elliott Delaye, Ashish Sirasao:
xDNN: Inference for Deep Convolutional Neural Networks. ACM Trans. Reconfigurable Technol. Syst. 15(2): 18:1-18:29 (2022)
Conference and Workshop Papers
- 2024
- [c12]Ji Liu, Dehua Tang, Yuanxian Huang, Li Zhang, Xiaocheng Zeng, Dong Li, Mingjie Lu, Jinzhang Peng, Yu Wang, Fan Jiang, Lu Tian, Ashish Sirasao:
UPDP: A Unified Progressive Depth Pruner for CNN and Vision Transformer. AAAI 2024: 13891-13899 - [c11]Yixing Xu, Chao Li, Dong Li, Xiao Sheng, Fan Jiang, Lu Tian, Ashish Sirasao, Emad Barsoum:
Enhancing Vision Transformer: Amplifying Non-Linearity in Feedforward Network Module. ICML 2024 - [c10]Mengmeng Ge, Xu Jia, Takashi Isobe, Xiaomin Li, Qinghe Wang, Jing Mu, Dong Zhou, Li Wang, Huchuan Lu, Lu Tian, Ashish Sirasao, Emad Barsoum:
Customizing Text-to-Image Generation with Inverted Interaction. ACM Multimedia 2024: 10901-10909 - 2023
- [c9]Yixing Xu, Chao Li, Dong Li, Xiao Sheng, Fan Jiang, Lu Tian, Ashish Sirasao:
FDViT: Improve the Hierarchical Architecture of Vision Transformer. ICCV 2023: 5927-5937 - [c8]Hyoukjun Kwon, Krishnakumar Nair, Jamin Seo, Jason Yik, Debabrata Mohapatra, Dongyuan Zhan, Jinook Song, Peter Capak, Peizhao Zhang, Peter Vajda, Colby R. Banbury, Mark Mazumder, Liangzhen Lai, Ashish Sirasao, Tushar Krishna, Harshit Khaitan, Vikas Chandra, Vijay Janapa Reddi:
XRBench: An Extended Reality (XR) Machine Learning Benchmark Suite for the Metaverse. MLSys 2023 - 2021
- [c7]Taehee Jeong, Manasa Bollavaram, Elliott Delaye, Ashish Sirasao:
Neural network pruning for biomedical image segmentation. Image-Guided Procedures 2021 - 2020
- [c6]Vijay Janapa Reddi, Christine Cheng, David Kanter, Peter Mattson, Guenther Schmuelling, Carole-Jean Wu, Brian Anderson, Maximilien Breughe, Mark Charlebois, William Chou, Ramesh Chukka, Cody Coleman, Sam Davis, Pan Deng, Greg Diamos, Jared Duke, Dave Fick, J. Scott Gardner, Itay Hubara, Sachin Idgunji, Thomas B. Jablin, Jeff Jiao, Tom St. John, Pankaj Kanwar, David Lee, Jeffery Liao, Anton Lokhmotov, Francisco Massa, Peng Meng, Paulius Micikevicius, Colin Osborne, Gennady Pekhimenko, Arun Tejusve Raghunath Rajan, Dilip Sequeira, Ashish Sirasao, Fei Sun, Hanlin Tang, Michael Thomson, Frank Wei, Ephrem Wu, Lingjie Xu, Koichi Yamada, Bing Yu, George Yuan, Aaron Zhong, Peizhao Zhang, Yuchen Zhou:
MLPerf Inference Benchmark. ISCA 2020: 446-459 - [c5]Taehee Jeong, Ehsam Ghasemi, Jorn Tuyls, Elliott Delaye, Ashish Sirasao:
Neural network pruning and hardware acceleration. UCC 2020: 440-445 - 2018
- [c4]Elliott Delaye, Ashish Sirasao, Ehsan Ghasemi:
Exploration and Tradeoffs of different Kernels in FPGA Deep Learning Applications. ISPD 2018: 42-47 - 2017
- [c3]Elliott Delaye, Ashish Sirasao, Chaithanya Dudha, Sabya Das:
Deep learning challenges and solutions with Xilinx FPGAs. ICCAD 2017: 908-913 - [c2]Brian Hill, Jaclyn Smith, Gans Srinivasa, Kemal Sönmez, Ashish Sirasao, Amit Gupta, Madhubanti Mukherjee:
Precision medicine and FPGA technology: Challenges and opportunities. MWSCAS 2017: 655-658 - 1997
- [c1]Madhav Y. Chikodikar, Shridhar Laddha, Ashish Sirasao:
A Technology Mapper for Xilinx FPGAs. VLSI Design 1997: 57-61
Informal and Other Publications
- 2024
- [i9]Ji Liu, Dehua Tang, Yuanxian Huang, Li Zhang, Xiaocheng Zeng, Dong Li, Mingjie Lu, Jinzhang Peng, Yu Wang, Fan Jiang, Lu Tian, Ashish Sirasao:
UPDP: A Unified Progressive Depth Pruner for CNN and Vision Transformer. CoRR abs/2401.06426 (2024) - [i8]Ji Liu, Zifeng Zhang, Mingjie Lu, Hongyang Wei, Dong Li, Yile Xie, Jinzhang Peng, Lu Tian, Ashish Sirasao, Emad Barsoum:
Sparse Laneformer. CoRR abs/2404.07821 (2024) - [i7]Yuchen Yang, Xinyi Wang, Dong Li, Lu Tian, Ashish Sirasao, Xun Yang:
Towards Scale-Aware Full Surround Monodepth with Transformers. CoRR abs/2407.10406 (2024) - [i6]Guanchen Li, Xiandong Zhao, Lian Liu, Zeping Li, Dong Li, Lu Tian, Jie He, Ashish Sirasao, Emad Barsoum:
Enhancing One-shot Pruned Pre-trained Language Models through Sparse-Dense-Sparse Mechanism. CoRR abs/2408.10473 (2024) - [i5]Haowei Zhu, Dehua Tang, Ji Liu, Mingjie Lu, Jintu Zheng, Jinzhang Peng, Dong Li, Yu Wang, Fan Jiang, Lu Tian, Spandan Tiwari, Ashish Sirasao, Jun-Hai Yong, Bin Wang, Emad Barsoum:
DiP-GO: A Diffusion Pruner via Few-step Gradient Optimization. CoRR abs/2410.16942 (2024) - 2023
- [i4]Mingjie Lu, Yuanxian Huang, Ji Liu, Jinzhang Peng, Lu Tian, Ashish Sirasao:
Separated RoadTopoFormer. CoRR abs/2307.01557 (2023) - 2022
- [i3]Hyoukjun Kwon, Krishnakumar Nair, Jamin Seo, Jason Yik, Debabrata Mohapatra, Dongyuan Zhan, Jinook Song, Peter Capak, Peizhao Zhang, Peter Vajda, Colby R. Banbury, Mark Mazumder, Liangzhen Lai, Ashish Sirasao, Tushar Krishna, Harshit Khaitan, Vikas Chandra, Vijay Janapa Reddi:
XRBench: An Extended Reality (XR) Machine Learning Benchmark Suite for the Metaverse. CoRR abs/2211.08675 (2022) - 2019
- [i2]Vijay Janapa Reddi, Christine Cheng, David Kanter, Peter Mattson, Guenther Schmuelling, Carole-Jean Wu, Brian Anderson, Maximilien Breughe, Mark Charlebois, William Chou, Ramesh Chukka, Cody Coleman, Sam Davis, Pan Deng, Greg Diamos, Jared Duke, Dave Fick, J. Scott Gardner, Itay Hubara, Sachin Idgunji, Thomas B. Jablin, Jeff Jiao, Tom St. John, Pankaj Kanwar, David Lee, Jeffery Liao, Anton Lokhmotov, Francisco Massa, Peng Meng, Paulius Micikevicius, Colin Osborne, Gennady Pekhimenko, Arun Tejusve Raghunath Rajan, Dilip Sequeira, Ashish Sirasao, Fei Sun, Hanlin Tang, Michael Thomson, Frank Wei, Ephrem Wu, Lingjie Xu, Koichi Yamada, Bing Yu, George Yuan, Aaron Zhong, Peizhao Zhang, Yuchen Zhou:
MLPerf Inference Benchmark. CoRR abs/1911.02549 (2019) - 2018
- [i1]Sean O. Settle, Manasa Bollavaram, Paolo D'Alberto, Elliott Delaye, Oscar Fernandez, Nicholas Fraser, Aaron Ng, Ashish Sirasao, Michael Wu:
Quantizing Convolutional Neural Networks for Low-Power High-Throughput Inference Engines. CoRR abs/1805.07941 (2018)
Coauthor Index
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