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2020 – today
- 2024
[c23]Mostafa Elhoushi, Akshat Shrivastava, Diana Liskovich, Basil Hosmer, Bram Wasti, Liangzhen Lai, Anas Mahmoud, Bilge Acun, Saurabh Agarwal, Ahmed Roman, Ahmed A Aly, Beidi Chen, Carole-Jean Wu:
LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding. ACL (1) 2024: 12622-12642- [c22]Maximilian Lam
, Jeff Johnson, Wenjie Xiong, Kiwan Maeng, Udit Gupta, Yang Li, Liangzhen Lai, Ilias Leontiadis, Minsoo Rhu, Hsien-Hsin S. Lee, Vijay Janapa Reddi, Gu-Yeon Wei, David Brooks, G. Edward Suh:
GPU-based Private Information Retrieval for On-Device Machine Learning Inference. ASPLOS (1) 2024: 197-214 - [c21]Yang Li, Liangzhen Lai, Yuan Shangguan, Forrest N. Iandola, Zhaoheng Ni, Ernie Chang, Yangyang Shi, Vikas Chandra:
Folding Attention: Memory and Power Optimization for On-Device Transformer-Based Streaming Speech Recognition. ICASSP 2024: 11901-11905 - [c20]Zechun Liu, Changsheng Zhao, Forrest N. Iandola, Chen Lai, Yuandong Tian, Igor Fedorov, Yunyang Xiong, Ernie Chang, Yangyang Shi, Raghuraman Krishnamoorthi, Liangzhen Lai, Vikas Chandra:
MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases. ICML 2024 - [i21]Yang Li, Yuan Shangguan, Yuhao Wang, Liangzhen Lai, Ernie Chang, Changsheng Zhao, Yangyang Shi, Vikas Chandra:
Not All Weights Are Created Equal: Enhancing Energy Efficiency in On-Device Streaming Speech Recognition. CoRR abs/2402.13076 (2024) - [i20]Zechun Liu, Changsheng Zhao, Forrest N. Iandola, Chen Lai, Yuandong Tian, Igor Fedorov, Yunyang Xiong, Ernie Chang, Yangyang Shi, Raghuraman Krishnamoorthi, Liangzhen Lai, Vikas Chandra:
MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases. CoRR abs/2402.14905 (2024) - [i19]Mostafa Elhoushi, Akshat Shrivastava, Diana Liskovich, Basil Hosmer, Bram Wasti, Liangzhen Lai, Anas Mahmoud, Bilge Acun, Saurabh Agarwal, Ahmed Roman, Ahmed A Aly, Beidi Chen, Carole-Jean Wu:
LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding. CoRR abs/2404.16710 (2024) - [i18]Raveesh Garg, Hyoukjun Kwon, Eric Qin, Yu-Hsin Chen, Tushar Krishna, Liangzhen Lai:
PipeOrgan: Efficient Inter-operation Pipelining with Flexible Spatial Organization and Interconnects. CoRR abs/2405.01736 (2024) - 2023
- [c19]Seah Kim, Hyoukjun Kwon, Jinook Song, Jihyuck Jo, Yu-Hsin Chen, Liangzhen Lai, Vikas Chandra:
DREAM: A Dynamic Scheduler for Dynamic Real-time Multi-model ML Workloads. ASPLOS (4) 2023: 73-86 - [c18]Yixuan Hu, Tengyu Zhang, Meng Li, Renjie Wei, Liangzhen Lai, Yuan Wang, Runsheng Wang, Ru Huang:
Efficient Non-Linear Adder for Stochastic Computing with Approximate Spatial-Temporal Sorting Network. DAC 2023: 1-6 - [c17]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 - [i17]Maximilian Lam, Jeff Johnson, Wenjie Xiong, Kiwan Maeng, Udit Gupta, Yang Li, Liangzhen Lai, Ilias Leontiadis, Minsoo Rhu, Hsien-Hsin S. Lee, Vijay Janapa Reddi, Gu-Yeon Wei, David Brooks, G. Edward Suh:
GPU-based Private Information Retrieval for On-Device Machine Learning Inference. CoRR abs/2301.10904 (2023) - [i16]Yang Li, Liangzhen Lai, Yuan Shangguan, Forrest N. Iandola, Ernie Chang, Yangyang Shi, Vikas Chandra:
Folding Attention: Memory and Power Optimization for On-Device Transformer-based Streaming Speech Recognition. CoRR abs/2309.07988 (2023) - 2022
- [c16]Jiaqi Gu, Hyoukjun Kwon, Dilin Wang, Wei Ye, Meng Li, Yu-Hsin Chen, Liangzhen Lai, Vikas Chandra, David Z. Pan:
Multi-Scale High-Resolution Vision Transformer for Semantic Segmentation. CVPR 2022: 12084-12093 - [i15]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) - [i14]Seah Kim, Hyoukjun Kwon, Jinook Song, Jihyuck Jo, Yu-Hsin Chen, Liangzhen Lai, Vikas Chandra:
SDRM3: A Dynamic Scheduler for Dynamic Real-time Multi-model ML Workloads. CoRR abs/2212.03414 (2022) - 2021
- [c15]Hyoukjun Kwon, Liangzhen Lai, Michael Pellauer, Tushar Krishna, Yu-Hsin Chen, Vikas Chandra:
Heterogeneous Dataflow Accelerators for Multi-DNN Workloads. HPCA 2021: 71-83 - [i13]Jiaqi Gu, Hyoukjun Kwon, Dilin Wang, Wei Ye, Meng Li, Yu-Hsin Chen, Liangzhen Lai, Vikas Chandra, David Z. Pan:
Multi-Scale High-Resolution Vision Transformer for Semantic Segmentation. CoRR abs/2111.01236 (2021) - [i12]Cole Hawkins, Haichuan Yang, Meng Li, Liangzhen Lai, Vikas Chandra:
Low-Rank+Sparse Tensor Compression for Neural Networks. CoRR abs/2111.01697 (2021) - 2020
- [c14]Lei Yang, Zheyu Yan, Meng Li, Hyoukjun Kwon, Liangzhen Lai, Tushar Krishna, Vikas Chandra, Weiwen Jiang, Yiyu Shi:
Co-Exploration of Neural Architectures and Heterogeneous ASIC Accelerator Designs Targeting Multiple Tasks. DAC 2020: 1-6 - [i11]Lei Yang, Zheyu Yan, Meng Li, Hyoukjun Kwon, Liangzhen Lai, Tushar Krishna, Vikas Chandra, Weiwen Jiang, Yiyu Shi:
Co-Exploration of Neural Architectures and Heterogeneous ASIC Accelerator Designs Targeting Multiple Tasks. CoRR abs/2002.04116 (2020) - [i10]Meng Li, Yilei Li, Pierce Chuang, Liangzhen Lai, Vikas Chandra:
Improving Efficiency in Neural Network Accelerator Using Operands Hamming Distance optimization. CoRR abs/2002.05293 (2020)
2010 – 2019
- 2019
- [c13]Jeya Vikranth Jeyakumar, Liangzhen Lai, Naveen Suda, Mani B. Srivastava:
SenseHAR: a robust virtual activity sensor for smartphones and wearables. SenSys 2019: 15-28 - [i9]Hyoukjun Kwon, Liangzhen Lai, Tushar Krishna, Vikas Chandra:
HERALD: Optimizing Heterogeneous DNN Accelerators for Edge Devices. CoRR abs/1909.07437 (2019) - 2018
- [c12]Liangzhen Lai, Naveen Suda:
Enabling deep learning at the IoT edge. ICCAD 2018: 135 - [c11]Hardik Sharma, Jongse Park, Naveen Suda, Liangzhen Lai, Benson Chau, Vikas Chandra, Hadi Esmaeilzadeh:
Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Network. ISCA 2018: 764-775 - [i8]Liangzhen Lai, Naveen Suda, Vikas Chandra:
Not All Ops Are Created Equal! CoRR abs/1801.04326 (2018) - [i7]Liangzhen Lai, Naveen Suda, Vikas Chandra:
CMSIS-NN: Efficient Neural Network Kernels for Arm Cortex-M CPUs. CoRR abs/1801.06601 (2018) - [i6]Yue Zhao, Meng Li, Liangzhen Lai, Naveen Suda, Damon Civin, Vikas Chandra:
Federated Learning with Non-IID Data. CoRR abs/1806.00582 (2018) - [i5]Liangzhen Lai, Naveen Suda:
Rethinking Machine Learning Development and Deployment for Edge Devices. CoRR abs/1806.07846 (2018) - 2017
- [j5]Liangzhen Lai, Puneet Gupta:
System-Level Dynamic Variation Margining in Presence of Monitoring and Actuation. IEEE Embed. Syst. Lett. 9(3): 85-88 (2017) - [c10]Meng Li, Liangzhen Lai, Vikas Chandra, David Z. Pan:
Cross-level Monte Carlo Framework for System Vulnerability Evaluation against Fault Attack. DAC 2017: 17:1-17:6 - [c9]Vikas Chandra, Liangzhen Lai:
Exploiting data-dependence and Flip-Flop asymmetry for zero-overhead system soft error mitigation. DATE 2017: 1189-1194 - [i4]Liangzhen Lai, Naveen Suda, Vikas Chandra:
Deep Convolutional Neural Network Inference with Floating-point Weights and Fixed-point Activations. CoRR abs/1703.03073 (2017) - [i3]Meng Li, Liangzhen Lai, Naveen Suda, Vikas Chandra, David Z. Pan:
PrivyNet: A Flexible Framework for Privacy-Preserving Deep Neural Network Training with A Fine-Grained Privacy Control. CoRR abs/1709.06161 (2017) - [i2]Yundong Zhang, Naveen Suda, Liangzhen Lai, Vikas Chandra:
Hello Edge: Keyword Spotting on Microcontrollers. CoRR abs/1711.07128 (2017) - [i1]Hardik Sharma, Jongse Park, Naveen Suda, Liangzhen Lai, Benson Chau, Joon Kyung Kim, Vikas Chandra, Hadi Esmaeilzadeh:
Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Networks. CoRR abs/1712.01507 (2017) - 2016
- [c8]Liangzhen Lai, Puneet Gupta:
Hardware Reliability margining for the dark silicon era. ASP-DAC 2016: 637-642 - [c7]Qixiang Zhang, Liangzhen Lai, Mark Gottscho, Puneet Gupta:
Multi-story power distribution networks for GPUs. DATE 2016: 451-456 - [c6]Liangzhen Lai, Vikas Chandra, Rob Aitken:
Resiliency in dynamically power managed designs. ICCAD 2016: 69 - 2015
- [j4]Lucas Francisco Wanner, Liangzhen Lai, Abbas Rahimi, Mark Gottscho, Pietro Mercati, Chu-Hsiang Huang, Frederic Sala, Yuvraj Agarwal, Lara Dolecek, Nikil D. Dutt, Puneet Gupta, Rajesh K. Gupta, Ranjit Jhala, Rakesh Kumar, Sorin Lerner, Subhasish Mitra, Alexandru Nicolau, Tajana Simunic Rosing, Mani B. Srivastava, Steven Swanson, Dennis Sylvester, Yuanyuan Zhou:
NSF expedition on variability-aware software: Recent results and contributions. it Inf. Technol. 57(3): 181-198 (2015) - [c5]Liangzhen Lai, Vikas Chandra, Puneet Gupta:
Evaluating and exploiting impacts of dynamic power management schemes on system reliability. CASES 2015: 39-48 - 2014
- [j3]Liangzhen Lai, Vikas Chandra, Robert C. Aitken, Puneet Gupta:
BTI-Gater: An Aging-Resilient Clock Gating Methodology. IEEE J. Emerg. Sel. Topics Circuits Syst. 4(2): 180-189 (2014) - [j2]Liangzhen Lai, Vikas Chandra, Robert C. Aitken, Puneet Gupta:
SlackProbe: A Flexible and Efficient In Situ Timing Slack Monitoring Methodology. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 33(8): 1168-1179 (2014) - [j1]Tuck-Boon Chan, Puneet Gupta, Andrew B. Kahng, Liangzhen Lai:
Synthesis and Analysis of Design-Dependent Ring Oscillator (DDRO) Performance Monitors. IEEE Trans. Very Large Scale Integr. Syst. 22(10): 2117-2130 (2014) - [c4]Liangzhen Lai, Puneet Gupta:
Accurate and inexpensive performance monitoring for variability-aware systems. ASP-DAC 2014: 467-473 - 2013
- [c3]Lucas Francisco Wanner, Salma Elmalaki, Liangzhen Lai, Puneet Gupta, Mani B. Srivastava:
VarEMU: An emulation testbed for variability-aware software. CODES+ISSS 2013: 27:1-27:10 - [c2]Liangzhen Lai, Vikas Chandra, Robert C. Aitken, Puneet Gupta:
SlackProbe: a low overhead in situ on-line timing slack monitoring methodology. DATE 2013: 282-287 - 2012
- [c1]Tuck-Boon Chan, Puneet Gupta, Andrew B. Kahng, Liangzhen Lai:
DDRO: A novel performance monitoring methodology based on design-dependent ring oscillators. ISQED 2012: 633-640
Coauthor Index
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last updated on 2024-09-26 00:59 CEST by the dblp team
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