Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
2109.08957
Cited By
AI Accelerator Survey and Trends
18 September 2021
Albert Reuther
Peter Michaleas
Michael Jones
V. Gadepally
S. Samsi
J. Kepner
Re-assign community
ArXiv
PDF
HTML
Papers citing
"AI Accelerator Survey and Trends"
16 / 16 papers shown
Title
Optimizing DNN Inference on Multi-Accelerator SoCs at Training-time
Matteo Risso
Alessio Burrello
Daniele Jahier Pagliari
46
0
0
24 Feb 2025
Modeling Performance of Data Collection Systems for High-Energy Physics
W. Olin-Ammentorp
Xingfu Wu
Andrew A. Chien
21
0
0
27 Jun 2024
GreenLightningAI: An Efficient AI System with Decoupled Structural and Quantitative Knowledge
Jose Duato
Jose I. Mestre
Manuel F. Dolz
Enrique S. Quintana-Ortí
11
1
0
15 Dec 2023
Lincoln AI Computing Survey (LAICS) Update
Albert Reuther
Peter Michaleas
Michael Jones
V. Gadepally
S. Samsi
J. Kepner
ELM
26
4
0
13 Oct 2023
Energy Estimates Across Layers of Computing: From Devices to Large-Scale Applications in Machine Learning for Natural Language Processing, Scientific Computing, and Cryptocurrency Mining
Sadasivan Shankar
27
3
0
11 Oct 2023
Precision-aware Latency and Energy Balancing on Multi-Accelerator Platforms for DNN Inference
Matteo Risso
Alessio Burrello
G. M. Sarda
Luca Benini
Enrico Macii
M. Poncino
Marian Verhelst
Daniele Jahier Pagliari
28
4
0
08 Jun 2023
One-Shot Online Testing of Deep Neural Networks Based on Distribution Shift Detection
Soyed Tuhin Ahmed
M. Tahoori
34
3
0
16 May 2023
AI-assisted Automated Workflow for Real-time X-ray Ptychography Data Analysis via Federated Resources
A. Babu
Tekin Bicer
S. Kandel
Tao Zhou
Daniel J. Ching
S. Henke
Sinivsa Veseli
Ryan Chard
Antonino Miceli
Mathew J. Cherukara
24
6
0
09 Apr 2023
Perspectives on AI Architectures and Co-design for Earth System Predictability
M. Mudunuru
James A. Ang
M. Halappanavar
Simon D. Hammond
Maya Gokhale
...
Tushar Krishna
S. Sreepathi
Matthew R. Norman
Ivy Bo Peng
Philip W. Jones
15
0
0
07 Apr 2023
Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators
Malte J. Rasch
C. Mackin
Manuel Le Gallo
An Chen
A. Fasoli
...
P. Narayanan
H. Tsai
G. Burr
Abu Sebastian
Vijay Narayanan
13
83
0
16 Feb 2023
Intelligent Computing: The Latest Advances, Challenges and Future
Shiqiang Zhu
Ting Yu
Tao Xu
Hongyang Chen
Schahram Dustdar
...
Tariq S. Durrani
Huaimin Wang
Jiangxing Wu
Tongyi Zhang
Yunhe Pan
AI4CE
27
117
0
21 Nov 2022
Statistical Modeling of Soft Error Influence on Neural Networks
Haitong Huang
Xing-xiong Xue
Cheng Liu
Ying Wang
Tao Luo
Long Cheng
Huawei Li
Xiaowei Li
29
7
0
12 Oct 2022
PINCH: An Adversarial Extraction Attack Framework for Deep Learning Models
William Hackett
Stefan Trawicki
Zhengxin Yu
N. Suri
Peter Garraghan
MIACV
AAML
13
3
0
13 Sep 2022
The MIT Supercloud Workload Classification Challenge
Benny J. Tang
Qiqi Chen
Matthew L. Weiss
Nathan C. Frey
Joseph McDonald
...
Lindsey McEvoy
Baolin Li
Devesh Tiwari
V. Gadepally
S. Samsi
13
2
0
12 Apr 2022
Machines & Influence: An Information Systems Lens
Shashank Yadav
43
1
0
26 Nov 2021
The Computational Limits of Deep Learning
Neil C. Thompson
Kristjan Greenewald
Keeheon Lee
Gabriel F. Manso
VLM
23
506
0
10 Jul 2020
1