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Chipmunk: A Systolically Scalable 0.9 mm${}^2$, 3.08 Gop/s/mW @ 1.2 mW
  Accelerator for Near-Sensor Recurrent Neural Network Inference
v1v2 (latest)

Chipmunk: A Systolically Scalable 0.9 mm2{}^22, 3.08 Gop/s/mW @ 1.2 mW Accelerator for Near-Sensor Recurrent Neural Network Inference

15 November 2017
Francesco Conti
Lukas Cavigelli
G. Paulin
Igor Susmelj
Luca Benini
ArXiv (abs)PDFHTML

Papers citing "Chipmunk: A Systolically Scalable 0.9 mm${}^2$, 3.08 Gop/s/mW @ 1.2 mW Accelerator for Near-Sensor Recurrent Neural Network Inference"

10 / 10 papers shown
MINIMALIST: switched-capacitor circuits for efficient in-memory computation of gated recurrent units
MINIMALIST: switched-capacitor circuits for efficient in-memory computation of gated recurrent units
Sebastian Billaudelle
Laura Kriener
Filippo Moro
Tristan Torchet
Melika Payvand
317
0
0
13 May 2025
A Low-Power Streaming Speech Enhancement Accelerator For Edge Devices
A Low-Power Streaming Speech Enhancement Accelerator For Edge DevicesIEEE Open Journal of Circuits and Systems (OJ-CAS), 2025
Ci-Hao Wu
Tian-Sheuan Chang
278
2
0
27 Mar 2025
Language Modeling on a SpiNNaker 2 Neuromorphic Chip
Language Modeling on a SpiNNaker 2 Neuromorphic ChipInternational Conference on Artificial Intelligence Circuits and Systems (ICAICS), 2023
Khaleelulla Khan Nazeer
Mark Schöne
Rishav Mukherji
Bernhard Vogginger
Christian Mayr
David Kappel
Anand Subramoney
314
14
0
14 Dec 2023
RecLight: A Recurrent Neural Network Accelerator with Integrated Silicon
  Photonics
RecLight: A Recurrent Neural Network Accelerator with Integrated Silicon PhotonicsIEEE Computer Society Annual Symposium on VLSI (VLSI), 2022
Febin P. Sunny
Mahdi Nikdast
S. Pasricha
141
23
0
31 Aug 2022
Vau da muntanialas: Energy-efficient multi-die scalable acceleration of
  RNN inference
Vau da muntanialas: Energy-efficient multi-die scalable acceleration of RNN inferenceIEEE Transactions on Circuits and Systems Part 1: Regular Papers (TCAS-I), 2021
G. Paulin
Francesco Conti
Lukas Cavigelli
Luca Benini
156
14
0
14 Feb 2022
RNNAccel: A Fusion Recurrent Neural Network Accelerator for Edge
  Intelligence
RNNAccel: A Fusion Recurrent Neural Network Accelerator for Edge Intelligence
Chao-Yang Kao
Huang-Chih Kuo
Jian-Wen Chen
Chiung-Liang Lin
Pin-Han Chen
Y. Lin
63
6
0
26 Oct 2020
Data-Driven Neuromorphic DRAM-based CNN and RNN Accelerators
Data-Driven Neuromorphic DRAM-based CNN and RNN AcceleratorsAsilomar Conference on Signals, Systems and Computers (ACSSC), 2019
T. Delbruck
Shih-Chii Liu
168
6
0
29 Mar 2020
FANN-on-MCU: An Open-Source Toolkit for Energy-Efficient Neural Network
  Inference at the Edge of the Internet of Things
FANN-on-MCU: An Open-Source Toolkit for Energy-Efficient Neural Network Inference at the Edge of the Internet of ThingsIEEE Internet of Things Journal (IEEE IoT Journal), 2019
Xiaying Wang
Michele Magno
Lukas Cavigelli
Luca Benini
323
131
0
08 Nov 2019
ELSA: A Throughput-Optimized Design of an LSTM Accelerator for
  Energy-Constrained Devices
ELSA: A Throughput-Optimized Design of an LSTM Accelerator for Energy-Constrained DevicesACM Transactions on Embedded Computing Systems (ACM TECS), 2019
E. Azari
S. Vrudhula
180
5
0
19 Oct 2019
AIDA: Associative DNN Inference Accelerator
AIDA: Associative DNN Inference Accelerator
L. Yavits
R. Kaplan
R. Ginosar
59
1
0
20 Dec 2018
1
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