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03/20/2023
Hardware-Aware Graph Neural Network Automated Design for Edge Computing Platforms
Graph neural networks (GNNs) have emerged as a popular strategy for hand...
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06/22/2022
Towards Systems Education for Artificial Intelligence: A Course Practice in Intelligent Computing Architectures
With the rapid development of artificial intelligence (AI) community, ed...
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03/29/2022
Eventor: An Efficient Event-Based Monocular Multi-View Stereo Accelerator on FPGA Platform
Event cameras are bio-inspired vision sensors that asynchronously repres...
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12/01/2021
Triangle Counting Accelerations: From Algorithm to In-Memory Computing Architecture
Triangles are the basic substructure of networks and triangle counting (...
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08/20/2021
FedSkel: Efficient Federated Learning on Heterogeneous Systems with Skeleton Gradients Update
Federated learning aims to protect users' privacy while performing data ...
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07/23/2021
Forecasting the outcome of spintronic experiments with Neural Ordinary Differential Equations
Deep learning has an increasing impact to assist research, allowing, for...
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06/15/2021
S2Engine: A Novel Systolic Architecture for Sparse Convolutional Neural Networks
Convolutional neural networks (CNNs) have achieved great success in perf...
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04/07/2021
Optimizing Memory Efficiency of Graph NeuralNetworks on Edge Computing Platforms
Graph neural networks (GNN) have achieved state-of-the-art performance o...
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07/21/2020
SparseTrain: Exploiting Dataflow Sparsity for Efficient Convolutional Neural Networks Training
Training Convolutional Neural Networks (CNNs) usually requires a large n...
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07/21/2020
TCIM: Triangle Counting Acceleration With Processing-In-MRAM Architecture
Triangle counting (TC) is a fundamental problem in graph analysis and ha...
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06/02/2020
Hardware Security in Spin-Based Computing-In-Memory: Analysis, Exploits, and Mitigation Techniques
Computing-in-memory (CIM) is proposed to alleviate the processor-memory ...
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05/08/2020
Efficient Computation Reduction in Bayesian Neural Networks Through Feature Decomposition and Memorization
Bayesian method is capable of capturing real world uncertainties/incompl...
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08/01/2019
Accelerating CNN Training by Sparsifying Activation Gradients
Gradients to activations get involved in most of the calculations during...
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06/03/2019
eSLAM: An Energy-Efficient Accelerator for Real-Time ORB-SLAM on FPGA Platform
Simultaneous Localization and Mapping (SLAM) is a critical task for auto...
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02/19/2019
SPINBIS: Spintronics based Bayesian Inference System with Stochastic Computing
Bayesian inference is an effective approach for solving statistical lear...
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10/26/2018
A Scalable Pipelined Dataflow Accelerator for Object Region Proposals on FPGA Platform
Region proposal is critical for object detection while it usually poses ...
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02/08/2018
Exploiting Spin-Orbit Torque Devices as Reconfigurable Logic for Circuit Obfuscation
Circuit obfuscation is a frequently used approach to conceal logic funct...
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11/03/2017
Spintronics based Stochastic Computing for Efficient Bayesian Inference System
Bayesian inference is an effective approach for solving statistical lear...
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08/29/2016