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ORCIDGanesh Venkatesh
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2020 – today
- 2023
[c21]Zhaoshuo Li, Wei Ye, Dilin Wang, Francis X. Creighton, Russell H. Taylor, Ganesh Venkatesh, Mathias Unberath:
Temporally Consistent Online Depth Estimation in Dynamic Scenes. WACV 2023: 3017-3026- 2022
- [c20]Haichuan Yang, Yuan Shangguan, Dilin Wang, Meng Li, Pierce Chuang, Xiaohui Zhang, Ganesh Venkatesh, Ozlem Kalinli, Vikas Chandra:
Omni-Sparsity DNN: Fast Sparsity Optimization for On-Device Streaming E2E ASR Via Supernet. ICASSP 2022: 8197-8201 - 2021
- [j2]Hyojin Park
, Jayeon Yoo, Ganesh Venkatesh, Nojun Kwak:
Adaptive Template and Transition Map for Real-Time Video Object Segmentation. IEEE Access 9: 116914-116926 (2021) - [c19]Hyojin Park, Jayeon Yoo, Seohyeong Jeong, Ganesh Venkatesh, Nojun Kwak:
Learning Dynamic Network Using a Reuse Gate Function in Semi-Supervised Video Object Segmentation. CVPR 2021: 8405-8414 - [c18]Ganesh Venkatesh, Alagappan Valliappan, Jay Mahadeokar, Yuan Shangguan, Christian Fuegen, Michael L. Seltzer, Vikas Chandra:
Memory-Efficient Speech Recognition on Smart Devices. ICASSP 2021: 8368-8372 - [c17]Varun Nagaraja, Yangyang Shi, Ganesh Venkatesh, Ozlem Kalinli, Michael L. Seltzer, Vikas Chandra:
Collaborative Training of Acoustic Encoders for Speech Recognition. Interspeech 2021: 4573-4577 - [i12]Ganesh Venkatesh, Alagappan Valliappan, Jay Mahadeokar, Yuan Shangguan, Christian Fuegen, Michael L. Seltzer, Vikas Chandra:
Memory-efficient Speech Recognition on Smart Devices. CoRR abs/2102.11531 (2021) - [i11]Asit K. Mishra, Jorge Albericio Latorre, Jeff Pool, Darko Stosic, Dusan Stosic, Ganesh Venkatesh, Chong Yu, Paulius Micikevicius:
Accelerating Sparse Deep Neural Networks. CoRR abs/2104.08378 (2021) - [i10]Varun Nagaraja, Yangyang Shi, Ganesh Venkatesh, Ozlem Kalinli, Michael L. Seltzer, Vikas Chandra:
Collaborative Training of Acoustic Encoders for Speech Recognition. CoRR abs/2106.08960 (2021) - [i9]David Eriksson, Pierce I-Jen Chuang, Samuel Daulton, Peng Xia, Akshat Shrivastava, Arun Babu, Shicong Zhao, Ahmed Aly, Ganesh Venkatesh, Maximilian Balandat:
Latency-Aware Neural Architecture Search with Multi-Objective Bayesian Optimization. CoRR abs/2106.11890 (2021) - [i8]Dilin Wang, Yuan Shangguan, Haichuan Yang, Pierce Chuang, Jiatong Zhou, Meng Li, Ganesh Venkatesh, Ozlem Kalinli, Vikas Chandra:
Noisy Training Improves E2E ASR for the Edge. CoRR abs/2107.04677 (2021) - [i7]Haichuan Yang, Yuan Shangguan, Dilin Wang, Meng Li, Pierce Chuang, Xiaohui Zhang, Ganesh Venkatesh, Ozlem Kalinli, Vikas Chandra:
Omni-sparsity DNN: Fast Sparsity Optimization for On-Device Streaming E2E ASR via Supernet. CoRR abs/2110.08352 (2021) - [i6]Zhaoshuo Li, Wei Ye, Dilin Wang, Francis X. Creighton, Russell H. Taylor, Ganesh Venkatesh, Mathias Unberath:
Temporally Consistent Online Depth Estimation in Dynamic Scenes. CoRR abs/2111.09337 (2021) - 2020
- [i5]Hyojin Park, Ganesh Venkatesh, Nojun Kwak:
TTVOS: Lightweight Video Object Segmentation with Adaptive Template Attention Module and Temporal Consistency Loss. CoRR abs/2011.04445 (2020) - [i4]Yutong Bai, Haoqi Fan, Ishan Misra, Ganesh Venkatesh, Yongyi Lu, Yuyin Zhou, Qihang Yu, Vikas Chandra, Alan L. Yuille:
Can Temporal Information Help with Contrastive Self-Supervised Learning? CoRR abs/2011.13046 (2020) - [i3]Hyojin Park, Jayeon Yoo, Seohyeong Jeong, Ganesh Venkatesh, Nojun Kwak:
Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Video Object Segmentation. CoRR abs/2012.11655 (2020)
2010 – 2019
- 2018
- [c16]Paulius Micikevicius, Sharan Narang, Jonah Alben, Gregory F. Diamos, Erich Elsen, David García, Boris Ginsburg, Michael Houston, Oleksii Kuchaiev, Ganesh Venkatesh, Hao Wu:
Mixed Precision Training. ICLR (Poster) 2018 - 2017
- [c15]Asit K. Mishra, Eriko Nurvitadhi, Ganesh Venkatesh, Jonathan Pearce, Debbie Marr:
Fine-grained accelerators for sparse machine learning workloads. ASP-DAC 2017: 635-640 - [c14]Eriko Nurvitadhi, Ganesh Venkatesh, Jaewoong Sim, Debbie Marr, Randy Huang, Jason Ong Gee Hock, Yeong Tat Liew, Krishnan Srivatsan, Duncan J. M. Moss, Suchit Subhaschandra, Guy Boudoukh:
Can FPGAs Beat GPUs in Accelerating Next-Generation Deep Neural Networks? FPGA 2017: 5-14 - [c13]Ganesh Venkatesh, Eriko Nurvitadhi, Debbie Marr:
Accelerating Deep Convolutional Networks using low-precision and sparsity. ICASSP 2017: 2861-2865 - [i2]Paulius Micikevicius, Sharan Narang, Jonah Alben, Gregory F. Diamos, Erich Elsen, David García, Boris Ginsburg, Michael Houston, Oleksii Kuchaiev, Ganesh Venkatesh, Hao Wu:
Mixed Precision Training. CoRR abs/1710.03740 (2017) - 2016
- [c12]Eriko Nurvitadhi, Asit K. Mishra, Yu Wang, Ganesh Venkatesh, Debbie Marr:
Hardware accelerator for analytics of sparse data. DATE 2016: 1616-1621 - [c11]Eriko Nurvitadhi, David Sheffield, Jaewoong Sim, Asit K. Mishra, Ganesh Venkatesh, Debbie Marr:
Accelerating Binarized Neural Networks: Comparison of FPGA, CPU, GPU, and ASIC. FPT 2016: 77-84 - [i1]Ganesh Venkatesh, Eriko Nurvitadhi, Debbie Marr:
Accelerating Deep Convolutional Networks using low-precision and sparsity. CoRR abs/1610.00324 (2016) - 2013
- [c10]Nicholas P. Carter, Aditya Agrawal, Shekhar Borkar, Romain Cledat, Howard David, Dave Dunning, Joshua B. Fryman, Ivan Ganev, Roger A. Golliver, Rob C. Knauerhase, Richard Lethin, Benoît Meister, Asit K. Mishra, Wilfred R. Pinfold, Justin Teller, Josep Torrellas, Nicolas Vasilache, Ganesh Venkatesh, Jianping Xu:
Runnemede: An architecture for Ubiquitous High-Performance Computing. HPCA 2013: 198-209 - [c9]Ganesh Venkatesh:
APE: accelerator processor extensions to optimize data-compute co-location. MSPC@PLDI 2013: 1:1-1:10 - 2011
- [b1]Ganesh Venkatesh:
Configurable energy-efficient co-processors to scale the utilization wall. University of California, San Diego, USA, 2011 - [j1]Nathan Goulding-Hotta, Jack Sampson, Ganesh Venkatesh, Saturnino Garcia, Joe Auricchio, Po-Chao Huang, Manish Arora, Siddhartha Nath, Vikram Bhatt, Jonathan Babb, Steven Swanson, Michael B. Taylor:
The GreenDroid Mobile Application Processor: An Architecture for Silicon's Dark Future. IEEE Micro 31(2): 86-95 (2011) - [c8]Manish Arora, Jack Sampson, Nathan Goulding-Hotta, Jonathan Babb, Ganesh Venkatesh, Michael Bedford Taylor, Steven Swanson:
Reducing the Energy Cost of Irregular Code Bases in Soft Processor Systems. FCCM 2011: 210-213 - [c7]Jack Sampson, Manish Arora, Nathan Goulding-Hotta, Ganesh Venkatesh, Jonathan Babb, Vikram Bhatt, Steven Swanson, Michael Bedford Taylor:
An Evaluation of Selective Depipelining for FPGA-Based Energy-Reducing Irregular Code Coprocessors. FPL 2011: 24-29 - [c6]Jack Sampson, Ganesh Venkatesh, Nathan Goulding-Hotta, Saturnino Garcia, Steven Swanson, Michael Bedford Taylor:
Efficient complex operators for irregular codes. HPCA 2011: 491-502 - [c5]Ganesh Venkatesh, Jack Sampson, Nathan Goulding-Hotta, Sravanthi Kota Venkata, Michael Bedford Taylor, Steven Swanson:
QsCores: trading dark silicon for scalable energy efficiency with quasi-specific cores. MICRO 2011: 163-174 - 2010
- [c4]Ganesh Venkatesh, Jack Sampson, Nathan Goulding, Saturnino Garcia, Vladyslav Bryksin, Jose Lugo-Martinez, Steven Swanson, Michael Bedford Taylor:
Conservation cores: reducing the energy of mature computations. ASPLOS 2010: 205-218 - [c3]Nathan Goulding, Jack Sampson, Ganesh Venkatesh, Saturnino Garcia, Joe Auricchio, Jonathan Babb, Michael B. Taylor, Steven Swanson:
GreenDroid: A mobile application processor for a future of dark silicon. Hot Chips Symposium 2010: 1-39
2000 – 2009
- 2006
- [c2]Weihaw Chuang, Satish Narayanasamy, Ganesh Venkatesh, Jack Sampson, Michael Van Biesbrouck, Gilles Pokam, Brad Calder, Osvaldo Colavin:
Unbounded page-based transactional memory. ASPLOS 2006: 347-358 - 2005
- [c1]Bengu Li, Ganesh Venkatesh, Brad Calder, Rajiv Gupta:
Exploiting a Computation Reuse Cache to Reduce Energy in Network Processors. HiPEAC 2005: 251-265
Coauthor Index
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