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05/31/2023
ReDSEa: Automated Acceleration of Triangular Solver on Supercloud Heterogeneous Systems
When utilized effectively, Supercloud heterogeneous systems have the pot...
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05/08/2023
Flex-SFU: Accelerating DNN Activation Functions by Non-Uniform Piecewise Approximation
Modern DNN workloads increasingly rely on activation functions consistin...
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10/17/2022
A ”New Ara” for Vector Computing: An Open Source Highly Efficient RISC-V V 1.0 Vector Processor Design
Vector architectures are gaining traction for highly efficient processin...
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09/26/2022
Going Further With Winograd Convolutions: Tap-Wise Quantization for Efficient Inference on 4x4 Tile
Most of today's computer vision pipelines are built around deep neural n...
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02/14/2022
Vau da muntanialas: Energy-efficient multi-die scalable acceleration of RNN inference
Recurrent neural networks such as Long Short-Term Memories (LSTMs) learn...
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01/10/2022
Sub-mW Keyword Spotting on an MCU: Analog Binary Feature Extraction and Binary Neural Networks
Keyword spotting (KWS) is a crucial function enabling the interaction wi...
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05/04/2021
Reinforcement Learning for Scalable Logic Optimization with Graph Neural Networks
Logic optimization is an NP-hard problem commonly approached through han...
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03/25/2021
ECG-TCN: Wearable Cardiac Arrhythmia Detection with a Temporal Convolutional Network
Personalized ubiquitous healthcare solutions require energy-efficient we...
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01/12/2021
Sound Event Detection with Binary Neural Networks on Tightly Power-Constrained IoT Devices
Sound event detection (SED) is a hot topic in consumer and smart city ap...
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11/03/2020
CUTIE: Beyond PetaOp/s/W Ternary DNN Inference Acceleration with Better-than-Binary Energy Efficiency
We present a 3.1 POp/s/W fully digital hardware accelerator for ternary ...
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05/31/2020
EEG-TCNet: An Accurate Temporal Convolutional Network for Embedded Motor-Imagery Brain-Machine Interfaces
In recent years, deep learning (DL) has contributed significantly to the...
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05/12/2020
ChewBaccaNN: A Flexible 223 TOPS/W BNN Accelerator
Binary Neural Networks enable smart IoT devices, as they significantly r...
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04/24/2020
Q-EEGNet: an Energy-Efficient 8-bit Quantized Parallel EEGNet Implementation for Edge Motor-Imagery Brain–Machine Interfaces
Motor-Imagery Brain-Machine Interfaces (MI-BMIs) promise direct and acce...
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01/04/2020
RPR: Random Partition Relaxation for Training; Binary and Ternary Weight Neural Networks
We present Random Partition Relaxation (RPR), a method for strong quanti...
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12/10/2019
HR-SAR-Net: A Deep Neural Network for Urban Scene Segmentation from High-Resolution SAR Data
Synthetic aperture radar (SAR) data is becoming increasingly available t...
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11/08/2019
FANN-on-MCU: An Open-Source Toolkit for Energy-Efficient Neural Network Inference at the Edge of the Internet of Things
The growing number of low-power smart devices in the Internet of Things ...
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08/30/2019
EBPC: Extended Bit-Plane Compression for Deep Neural Network Inference and Training Accelerators
In the wake of the success of convolutional neural networks in image cla...
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05/24/2019
Additive Noise Annealing and Approximation Properties of Quantized Neural Networks
We present a theoretical and experimental investigation of the quantizat...
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10/01/2018
Extended Bit-Plane Compression for Convolutional Neural Network Accelerators
After the tremendous success of convolutional neural networks in image c...
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08/15/2018
CBinfer: Exploiting Frame-to-Frame Locality for Faster Convolutional Network Inference on Video Streams
The last few years have brought advances in computer vision at an amazin...
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03/05/2018
Hyperdrive: A Multi-Chip Systolically Scalable Binary-Weight CNN Inference Engine
Deep neural networks have achieved impressive results in computer vision...
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03/05/2018
Hyperdrive: A Systolically Scalable Binary-Weight CNN Inference Engine for mW IoT End-Nodes
Deep neural networks have achieved impressive results in computer vision...
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03/05/2018
XNORBIN: A 95 TOp/s/W Hardware Accelerator for Binary Convolutional Neural Networks
Deploying state-of-the-art CNNs requires power-hungry processors and off...
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11/21/2017
Design Automation for Binarized Neural Networks: A Quantum Leap Opportunity?
Design automation in general, and in particular logic synthesis, can pla...
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11/15/2017
Chipmunk: A Systolically Scalable 0.9 mm^2, 3.08 Gop/s/mW @ 1.2 mW Accelerator for Near-Sensor Recurrent Neural Network Inference
Recurrent neural networks (RNNs) are state-of-the-art in voice awareness...
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11/08/2017
Hydra: An Accelerator for Real-Time Edge-Aware Permeability Filtering in 65nm CMOS
Many modern video processing pipelines rely on edge-aware (EA) filtering...
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09/28/2017
Efficient Convolutional Neural Network For Audio Event Detection
Wireless distributed systems as used in sensor networks, Internet-of-Thi...
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04/14/2017
CBinfer: Change-Based Inference for Convolutional Neural Networks on Video Data
Extracting per-frame features using convolutional neural networks for re...
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04/03/2017
Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations
We present a new approach to learn compressible representations in deep ...
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11/22/2016
CAS-CNN: A Deep Convolutional Neural Network for Image Compression Artifact Suppression
Lossy image compression algorithms are pervasively used to reduce the si...
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11/09/2016
Computationally Efficient Target Classification in Multispectral Image Data with Deep Neural Networks
Detecting and classifying targets in video streams from surveillance cam...
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09/26/2016
Deep Structured Features for Semantic Segmentation
We propose a highly structured neural network architecture for semantic ...
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06/17/2016
YodaNN: An Architecture for Ultra-Low Power Binary-Weight CNN Acceleration
Convolutional neural networks (CNNs) have revolutionized the world of co...
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12/14/2015
