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Dibakar Gope
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2020 – today
- 2023
- [c17]Natalia Frumkin, Dibakar Gope, Diana Marculescu
:
Jumping through Local Minima: Quantization in the Loss Landscape of Vision Transformers. ICCV 2023: 16932-16942 - [i15]Yuji Chai, Devashree Tripathy, Chuteng Zhou, Dibakar Gope, Igor Fedorov, Ramon Matas Navarro, David Brooks, Gu-Yeon Wei, Paul N. Whatmough:
PerfSAGE: Generalized Inference Performance Predictor for Arbitrary Deep Learning Models on Edge Devices. CoRR abs/2301.10999 (2023) - [i14]Natalia Frumkin, Dibakar Gope, Diana Marculescu:
Jumping through Local Minima: Quantization in the Loss Landscape of Vision Transformers. CoRR abs/2308.10814 (2023) - 2022
- [c16]Kartikeya Bhardwaj, Dibakar Gope, James Ward, Paul N. Whatmough, Danny Loh:
Super-Efficient Super Resolution for Fast Adversarial Defense at the Edge. DATE 2022: 418-423 - [c15]Kartikeya Bhardwaj, Milos Milosavljevic, Liam O'Neil, Dibakar Gope, Ramon Matas Navarro, Alex Chalfin, Naveen Suda, Lingchuan Meng, Danny Loh:
Collapsible Linear Blocks for Super-Efficient Super Resolution. MLSys 2022 - [i13]Kartikeya Bhardwaj, James Ward, Caleb Tung, Dibakar Gope, Lingchuan Meng, Igor Fedorov, Alex Chalfin, Paul N. Whatmough, Danny Loh:
Restructurable Activation Networks. CoRR abs/2208.08562 (2022) - [i12]Natalia Frumkin, Dibakar Gope, Diana Marculescu:
CPT-V: A Contrastive Approach to Post-Training Quantization of Vision Transformers. CoRR abs/2211.09643 (2022) - 2021
- [j2]Urmish Thakker, Igor Fedorov, Chu Zhou, Dibakar Gope, Matthew Mattina, Ganesh Dasika, Jesse G. Beu:
Compressing RNNs to Kilobyte Budget for IoT Devices Using Kronecker Products. ACM J. Emerg. Technol. Comput. Syst. 17(4): 46:1-46:18 (2021) - [c14]Colby R. Banbury, Chuteng Zhou, Igor Fedorov, Ramon Matas Navarro, Urmish Thakker, Dibakar Gope, Vijay Janapa Reddi, Matthew Mattina, Paul N. Whatmough:
MicroNets: Neural Network Architectures for Deploying TinyML Applications on Commodity Microcontrollers. MLSys 2021 - [i11]Kartikeya Bhardwaj, Milos Milosavljevic, Alex Chalfin, Naveen Suda, Liam O'Neil, Dibakar Gope, Lingchuan Meng, Ramon Matas Navarro, Danny Loh:
Collapsible Linear Blocks for Super-Efficient Super Resolution. CoRR abs/2103.09404 (2021) - [i10]Kartikeya Bhardwaj, Dibakar Gope, James Ward, Paul N. Whatmough, Danny Loh:
Super-Efficient Super Resolution for Fast Adversarial Defense at the Edge. CoRR abs/2112.14340 (2021) - 2020
- [c13]Dibakar Gope, Jesse G. Beu, Urmish Thakker, Matthew Mattina:
Ternary MobileNets via Per-Layer Hybrid Filter Banks. CVPR Workshops 2020: 3036-3046 - [c12]Urmish Thakker, Jesse G. Beu, Dibakar Gope, Ganesh Dasika, Matthew Mattina:
Rank and run-time aware compression of NLP Applications. SustaiNLP@EMNLP 2020: 8-18 - [c11]Xueqin Huang, Urmish Thakker, Dibakar Gope, Jesse G. Beu:
Pushing the Envelope of Dynamic Spatial Gating technologies. AIChallengeIoT@SenSys 2020: 21-26 - [c10]Ravi Raju, Dibakar Gope, Urmish Thakker, Jesse G. Beu:
Understanding the Impact of Dynamic Channel Pruning on Conditionally Parameterized Convolutions. AIChallengeIoT@SenSys 2020: 27-33 - [i9]Jason Lowe-Power, Abdul Mutaal Ahmad, Ayaz Akram, Mohammad Alian
The gem5 Simulator: Version 20.0+. CoRR abs/2007.03152 (2020) - [i8]Dibakar Gope, Jesse G. Beu, Matthew Mattina:
High Throughput Matrix-Matrix Multiplication between Asymmetric Bit-Width Operands. CoRR abs/2008.00638 (2020) - [i7]Urmish Thakker, Jesse G. Beu, Dibakar Gope, Ganesh Dasika, Matthew Mattina:
Rank and run-time aware compression of NLP Applications. CoRR abs/2010.03193 (2020) - [i6]Colby R. Banbury, Chuteng Zhou, Igor Fedorov, Ramon Matas Navarro, Urmish Thakker, Dibakar Gope, Vijay Janapa Reddi, Matthew Mattina, Paul N. Whatmough:
MicroNets: Neural Network Architectures for Deploying TinyML Applications on Commodity Microcontrollers. CoRR abs/2010.11267 (2020)
2010 – 2019
- 2019
- [c9]Urmish Thakker, Jesse G. Beu, Dibakar Gope, Ganesh Dasika, Matthew Mattina:
Run-Time Efficient RNN Compression for Inference on Edge Devices. EMC2@HPCA/CVPR/ISCA 2019: 26-30 - [c8]Dibakar Gope, Ganesh Dasika, Matthew Mattina:
Ternary Hybrid Neural-Tree Networks for Highly Constrained IoT Applications. SysML 2019 - [c7]Urmish Thakker, Igor Fedorov, Jesse G. Beu, Dibakar Gope, Chu Zhou, Ganesh Dasika, Matthew Mattina:
Pushing the limits of RNN Compression. EMC2@NeurIPS 2019: 18-21 - [i5]Dibakar Gope, Ganesh Dasika, Matthew Mattina:
Ternary Hybrid Neural-Tree Networks for Highly Constrained IoT Applications. CoRR abs/1903.01531 (2019) - [i4]Urmish Thakker
Compressing RNNs for IoT devices by 15-38x using Kronecker Products. CoRR abs/1906.02876 (2019) - [i3]Urmish Thakker
Run-Time Efficient RNN Compression for Inference on Edge Devices. CoRR abs/1906.04886 (2019) - [i2]Urmish Thakker
Pushing the limits of RNN Compression. CoRR abs/1910.02558 (2019) - [i1]Dibakar Gope, Jesse G. Beu, Urmish Thakker
Ternary MobileNets via Per-Layer Hybrid Filter Banks. CoRR abs/1911.01028 (2019) - 2018
- [c6]Dibakar Gope, Arkaprava Basu, Sooraj Puthoor, Mitesh Meswani:
A Case for Scoped Persist Barriers in GPUs. GPGPU@PPoPP 2018: 2-12 - 2017
- [j1]Vignyan Reddy Kothinti Naresh, Dibakar Gope, Mikko H. Lipasti:
The CURE: Cluster Communication Using Registers. ACM Trans. Embed. Comput. Syst. 16(5s): 124:1-124:19 (2017) - [c5]Dibakar Gope, David J. Schlais, Mikko H. Lipasti:
Architectural Support for Server-Side PHP Processing. ISCA 2017: 507-520 - 2016
- [c4]Dibakar Gope, Mikko H. Lipasti:
Hash Map Inlining. PACT 2016: 235-246 - 2014
- [c3]Dibakar Gope, Mikko H. Lipasti:
Atomic SC for simple in-order processors. HPCA 2014: 404-415 - [c2]Dibakar Gope, Mikko H. Lipasti:
Bias-Free Branch Predictor. MICRO 2014: 521-532 - 2012
- [c1]Dibakar Gope, D. M. H. Walker:
Maximizing crosstalk-induced slowdown during path delay test. ICCD 2012: 159-166
Coauthor Index
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