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08/13/2023
When Monte-Carlo Dropout Meets Multi-Exit: Optimizing Bayesian Neural Networks on FPGA
Bayesian Neural Networks (BayesNNs) have demonstrated their capability o...
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06/14/2023
MetaML: Automating Customizable Cross-Stage Design-Flow for Deep Learning Acceleration
This paper introduces a novel optimization framework for deep neural net...
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09/28/2022
LL-GNN: Low Latency Graph Neural Networks on FPGAs for Particle Detectors
This work proposes a novel reconfigurable architecture for low latency G...
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09/20/2022
Adaptable Butterfly Accelerator for Attention-based NNs via Hardware and Algorithm Co-design
Attention-based neural networks have become pervasive in many AI tasks. ...
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12/10/2021
FLiMS: a Fast Lightweight 2-way Merger for Sorting
In this paper, we present FLiMS, a highly-efficient and simple parallel ...
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11/24/2021
Algorithm and Hardware Co-design for Reconfigurable CNN Accelerator
Recent advances in algorithm-hardware co-design for deep neural networks...
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06/26/2021
Accelerating Recurrent Neural Networks for Gravitational Wave Experiments
This paper presents novel reconfigurable architectures for reducing the ...
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06/14/2021
Extending the RISC-V ISA for exploring advanced reconfigurable SIMD instructions
This paper presents a novel, non-standard set of vector instruction type...
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05/12/2021
High-Performance FPGA-based Accelerator for Bayesian Neural Networks
Neural networks (NNs) have demonstrated their potential in a wide range ...
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09/06/2020
An Analysis of Alternating Direction Method of Multipliers for Feed-forward Neural Networks
In this work, we present a hardware compatible neural network training a...
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09/06/2020
An FPGA Accelerated Method for Training Feed-forward Neural Networks Using Alternating Direction Method of Multipliers and LSMR
In this project, we have successfully designed, implemented, deployed an...
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01/28/2020
Learning Absolute Sound Source Localisation With Limited Supervisions
An accurate auditory space map can be learned from auditory experience, ...
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06/27/2019
Convolution Based Spectral Partitioning Architecture for Hyperspectral Image Classification
Hyperspectral images (HSIs) can distinguish materials with high number o...
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06/27/2019
Optimizing CNN-based Hyperspectral ImageClassification on FPGAs
Hyperspectral image (HSI) classification has been widely adopted in appl...
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06/03/2019
Pangloss: a novel Markov chain prefetcher
We present Pangloss, an efficient high-performance data prefetcher that ...
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01/21/2019
Deep Neural Network Approximation for Custom Hardware: Where We've Been, Where We're Going
Deep neural networks have proven to be particularly effective in visual ...
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11/23/2018
Learning Grouped Convolution for Efficient Domain Adaptation
This paper presents Dokei, an effective supervised domain adaptation met...
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09/04/2018