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2020 – today
- 2022
[i10]Paulius Micikevicius, Dusan Stosic, Neil Burgess, Marius Cornea, Pradeep Dubey, Richard Grisenthwaite, Sangwon Ha, Alexander Heinecke, Patrick Judd, John Kamalu, Naveen Mellempudi, Stuart F. Oberman, Mohammad Shoeybi, Michael Y. Siu, Hao Wu:
FP8 Formats for Deep Learning. CoRR abs/2209.05433 (2022)- 2020
- [i9]Hao Wu, Patrick Judd, Xiaojie Zhang, Mikhail Isaev, Paulius Micikevicius:
Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation. CoRR abs/2004.09602 (2020)
2010 – 2019
- 2019
- [j5]Mostafa Mahmoud, Dylan Malone Stuart, Zissis Poulos, Alberto Delmas Lascorz, Patrick Judd, Sayeh Sharify, Milos Nikolic, Kevin Siu, Isak Edo Vivancos, Jorge Albericio, Andreas Moshovos:
Accelerating Image-Sensor-Based Deep Learning Applications. IEEE Micro 39(5): 26-35 (2019) - [c10]Alberto Delmas Lascorz, Patrick Judd, Dylan Malone Stuart, Zissis Poulos, Mostafa Mahmoud, Sayeh Sharify, Milos Nikolic, Kevin Siu, Andreas Moshovos:
Bit-Tactical: A Software/Hardware Approach to Exploiting Value and Bit Sparsity in Neural Networks. ASPLOS 2019: 749-763 - [c9]Alberto Delmas Lascorz, Sayeh Sharify, Isak Edo Vivancos, Dylan Malone Stuart, Omar Mohamed Awad, Patrick Judd, Mostafa Mahmoud, Milos Nikolic, Kevin Siu, Zissis Poulos, Andreas Moshovos:
ShapeShifter: Enabling Fine-Grain Data Width Adaptation in Deep Learning. MICRO 2019: 28-41 - 2018
- [j4]Andreas Moshovos, Jorge Albericio, Patrick Judd, Alberto Delmas Lascorz, Sayeh Sharify, Zissis Poulos, Tayler H. Hetherington, Tor M. Aamodt, Natalie D. Enright Jerger
:
Exploiting Typical Values to Accelerate Deep Learning. Computer 51(5): 18-30 (2018) - [j3]Andreas Moshovos, Jorge Albericio, Patrick Judd, Alberto Delmas Lascorz, Sayeh Sharify, Tayler H. Hetherington, Tor M. Aamodt, Natalie D. Enright Jerger:
Value-Based Deep-Learning Acceleration. IEEE Micro 38(1): 41-55 (2018) - [j2]Patrick Judd, Jorge Albericio, Tayler H. Hetherington, Tor M. Aamodt, Natalie D. Enright Jerger, Raquel Urtasun, Andreas Moshovos:
Proteus: Exploiting precision variability in deep neural networks. Parallel Comput. 73: 40-51 (2018) - [c8]Sayeh Sharify, Alberto Delmas Lascorz, Kevin Siu, Patrick Judd, Andreas Moshovos:
Loom: exploiting weight and activation precisions to accelerate convolutional neural networks. DAC 2018: 20:1-20:6 - [c7]Andreas Moshovos, Jorge Albericio, Patrick Judd, Alberto Delmas, Sayeh Sharify, Mostafa Mahmoud, Tayler H. Hetherington, Milos Nikolic, Dylan Malone Stuart, Kevin Siu, Zissis Poulos, Tor M. Aamodt, Natalie D. Enright Jerger:
Identifying and Exploiting Ineffectual Computations to Enable Hardware Acceleration of Deep Learning. NEWCAS 2018: 356-360 - [i8]Alberto Delmas, Patrick Judd, Dylan Malone Stuart, Zissis Poulos, Mostafa Mahmoud, Sayeh Sharify, Milos Nikolic, Andreas Moshovos:
Bit-Tactical: Exploiting Ineffectual Computations in Convolutional Neural Networks: Which, Why, and How. CoRR abs/1803.03688 (2018) - [i7]Alberto Delmas, Sayeh Sharify, Patrick Judd, Milos Nikolic, Andreas Moshovos:
DPRed: Making Typical Activation Values Matter In Deep Learning Computing. CoRR abs/1804.06732 (2018) - 2017
- [j1]Patrick Judd, Jorge Albericio, Andreas Moshovos:
Stripes: Bit-Serial Deep Neural Network Computing. IEEE Comput. Archit. Lett. 16(1): 80-83 (2017) - [c6]Jorge Albericio, Patrick Judd, Alberto Delmas, Sayeh Sharify, Andreas Moshovos:
Bit-Pragmatic Deep Neural Network Computing. ICLR (Workshop) 2017 - [c5]Jorge Albericio, Alberto Delmas, Patrick Judd, Sayeh Sharify, Gerard O'Leary, Roman Genov, Andreas Moshovos:
Bit-pragmatic deep neural network computing. MICRO 2017: 382-394 - [i6]Patrick Judd, Alberto Delmas Lascorz, Sayeh Sharify, Andreas Moshovos:
Cnvlutin2: Ineffectual-Activation-and-Weight-Free Deep Neural Network Computing. CoRR abs/1705.00125 (2017) - [i5]Alberto Delmas, Patrick Judd, Sayeh Sharify, Andreas Moshovos:
Dynamic Stripes: Exploiting the Dynamic Precision Requirements of Activation Values in Neural Networks. CoRR abs/1706.00504 (2017) - [i4]Sayeh Sharify, Alberto Delmas Lascorz, Patrick Judd, Andreas Moshovos:
Loom: Exploiting Weight and Activation Precisions to Accelerate Convolutional Neural Networks. CoRR abs/1706.07853 (2017) - [i3]Alberto Delmas, Sayeh Sharify, Patrick Judd, Andreas Moshovos:
Tartan: Accelerating Fully-Connected and Convolutional Layers in Deep Learning Networks by Exploiting Numerical Precision Variability. CoRR abs/1707.09068 (2017) - 2016
- [c4]Patrick Judd, Jorge Albericio, Tayler H. Hetherington, Tor M. Aamodt, Natalie D. Enright Jerger, Andreas Moshovos:
Proteus: Exploiting Numerical Precision Variability in Deep Neural Networks. ICS 2016: 23:1-23:12 - [c3]Jorge Albericio, Patrick Judd, Tayler H. Hetherington, Tor M. Aamodt, Natalie D. Enright Jerger, Andreas Moshovos:
Cnvlutin: Ineffectual-Neuron-Free Deep Neural Network Computing. ISCA 2016: 1-13 - [c2]Patrick Judd, Jorge Albericio, Tayler H. Hetherington, Tor M. Aamodt, Andreas Moshovos:
Stripes: Bit-serial deep neural network computing. MICRO 2016: 19:1-19:12 - [i2]Jorge Albericio, Patrick Judd, Alberto Delmas Lascorz, Sayeh Sharify, Andreas Moshovos:
Bit-pragmatic Deep Neural Network Computing. CoRR abs/1610.06920 (2016) - 2015
- [i1]Patrick Judd, Jorge Albericio, Tayler H. Hetherington, Tor M. Aamodt, Natalie D. Enright Jerger, Raquel Urtasun, Andreas Moshovos:
Reduced-Precision Strategies for Bounded Memory in Deep Neural Nets. CoRR abs/1511.05236 (2015) - 2014
- [c1]Goran Narancic, Patrick Judd, Di Wu, Islam Atta, Michel Elnacouzi, Jason Zebchuk, Jorge Albericio, Natalie D. Enright Jerger, Andreas Moshovos, Kyros Kutulakos, Serag Gadelrab:
Evaluating the memory system behavior of smartphone workloads. ICSAMOS 2014: 83-92
Coauthor Index
aka: Alberto Delmas
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