Proceedings of the ASPLOS '22: 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Lausanne, Switzerland, 28 February 2022, 2022

2021

Core Placement Optimization for Multi-chip Many-core Neural Network Systems with Reinforcement Learning.

[BibT_eX]

[DOI]

ACM Trans. Design Autom. Electr. Syst., 2021

Effective and Efficient Batch Normalization Using a Few Uncorrelated Data for Statistics Estimation.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2021

Target Controllability of Two-Layer Multiplex Networks Based on Network Flow Theory.

[BibT_eX]

[DOI]

IEEE Trans. Cybern., 2021

Practical Attacks on Deep Neural Networks by Memory Trojaning.

[BibT_eX]

[DOI]

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2021

Nonlinear tensor train format for deep neural network compression.

[BibT_eX]

[DOI]

Neural Networks, 2021

QTTNet: Quantized tensor train neural networks for 3D object and video recognition.

[BibT_eX]

[DOI]

Neural Networks, 2021

Fast Search of the Optimal Contraction Sequence in Tensor Networks.

[BibT_eX]

[DOI]

IEEE J. Sel. Top. Signal Process., 2021

Training and inference for integer-based semantic segmentation network.

[BibT_eX]

[DOI]

Neurocomputing, 2021

Tensor train decomposition for solving large-scale linear equations.

[BibT_eX]

[DOI]

Neurocomputing, 2021

Editorial: Understanding and Bridging the Gap Between Neuromorphic Computing and Machine Learning.

[BibT_eX]

[DOI]

Lei Deng

Huajin Tang

Kaushik Roy

Frontiers Comput. Neurosci., 2021

Advancing Residual Learning towards Powerful Deep Spiking Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2021

ES-ImageNet: A Million Event-Stream Classification Dataset for Spiking Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2021

Hardware Acceleration for GCNs via Bidirectional Fusion.

[BibT_eX]

[DOI]

IEEE Comput. Archit. Lett., 2021

GNNAdvisor: An Adaptive and Efficient Runtime System for GNN Acceleration on GPUs.

[BibT_eX]

[DOI]

Proceedings of the 15th USENIX Symposium on Operating Systems Design and Implementation, 2021

Exploiting Spiking Dynamics with Spatial-temporal Feature Normalization in Graph Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

SpaceA: Sparse Matrix Vector Multiplication on Processing-in-Memory Accelerator.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2021

TiAcc: Triangle-inequality based Hardware Accelerator for K-means on FPGAs.

[BibT_eX]

[DOI]

Proceedings of the 21st IEEE/ACM International Symposium on Cluster, 2021

Going Deeper With Directly-Trained Larger Spiking Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

SemiMap: A Semi-Folded Convolution Mapping for Speed-Overhead Balance on Crossbars.

[BibT_eX]

[DOI]

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2020

Scanning the Issue.

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[DOI]

H.-S. Philip Wong

Kerem Akarvardar

Dimitri A. Antoniadis

Proc. IEEE, 2020

Model Compression and Hardware Acceleration for Neural Networks: A Comprehensive Survey.

[BibT_eX]

[DOI]

Proc. IEEE, 2020

Training high-performance and large-scale deep neural networks with full 8-bit integers.

[BibT_eX]

[DOI]

Neural Networks, 2020

Hybrid tensor decomposition in neural network compression.

[BibT_eX]

[DOI]

Neural Networks, 2020

Compressing 3DCNNs based on tensor train decomposition.

[BibT_eX]

[DOI]

Neural Networks, 2020

Comparing SNNs and RNNs on neuromorphic vision datasets: Similarities and differences.

[BibT_eX]

[DOI]

Neural Networks, 2020

Rethinking the performance comparison between SNNS and ANNS.

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[DOI]

Neural Networks, 2020

Tianjic: A Unified and Scalable Chip Bridging Spike-Based and Continuous Neural Computation.

[BibT_eX]

[DOI]

IEEE J. Solid State Circuits, 2020

A deadlock-free physical mapping method on the many-core neural network chip.

[BibT_eX]

[DOI]

Neurocomputing, 2020

Rubik: A Hierarchical Architecture for Efficient Graph Learning.

[BibT_eX]

[DOI]

CoRR, 2020

Kronecker CP Decomposition with Fast Multiplication for Compressing RNNs.

[BibT_eX]

[DOI]

CoRR, 2020

GNNAdvisor: An Efficient Runtime System for GNN Acceleration on GPUs.

[BibT_eX]

[DOI]

CoRR, 2020

Brain-inspired global-local hybrid learning towards human-like intelligence.

[BibT_eX]

[DOI]

CoRR, 2020

Characterizing and Understanding GCNs on GPU.

[BibT_eX]

[DOI]

IEEE Comput. Archit. Lett., 2020

DUET: Boosting Deep Neural Network Efficiency on Dual-Module Architecture.

[BibT_eX]

[DOI]

Proceedings of the 53rd Annual IEEE/ACM International Symposium on Microarchitecture, 2020

Boosting Deep Neural Network Efficiency with Dual-Module Inference.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

fuseGNN: Accelerating Graph Convolutional Neural Network Training on GPGPU.

[BibT_eX]

[DOI]

Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2020

HyGCN: A GCN Accelerator with Hybrid Architecture.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on High Performance Computer Architecture, 2020

DeepSniffer: A DNN Model Extraction Framework Based on Learning Architectural Hints.

[BibT_eX]

[DOI]

Proceedings of the ASPLOS '20: Architectural Support for Programming Languages and Operating Systems, 2020

2019

L1-Norm Batch Normalization for Efficient Training of Deep Neural Networks.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2019

Transfer Learning in General Lensless Imaging through Scattering Media.

[BibT_eX]

[DOI]

CoRR, 2019

Lossless Compression for 3DCNNs Based on Tensor Train Decomposition.

[BibT_eX]

[DOI]

CoRR, 2019

DashNet: A Hybrid Artificial and Spiking Neural Network for High-speed Object Tracking.

[BibT_eX]

[DOI]

CoRR, 2019

AccD: A Compiler-based Framework for Accelerating Distance-related Algorithms on CPU-FPGA Platforms.

[BibT_eX]

[DOI]

CoRR, 2019

Neural Network Model Extraction Attacks in Edge Devices by Hearing Architectural Hints.

[BibT_eX]

[DOI]

CoRR, 2019

Alleviating Irregularity in Graph Analytics Acceleration: a Hardware/Software Co-Design Approach.

[BibT_eX]

[DOI]

Proceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture, 2019

Balancing Memory Accesses for Energy-Efficient Graph Analytics Accelerators.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE/ACM International Symposium on Low Power Electronics and Design, 2019

Dynamic Sparse Graph for Efficient Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

Efficient Mapping without Deadlock on the Many-core Neural Network Chip.

[BibT_eX]

[DOI]

Proceedings of the 15th IEEE International Conference on Control and Automation, 2019

CNNWire: Boosting Convolutional Neural Network with Winograd on ReRAM based Accelerators.

[BibT_eX]

[DOI]

Proceedings of the 2019 on Great Lakes Symposium on VLSI, 2019

KPynq: A Work-Efficient Triangle-Inequality Based K-Means on FPGA.

[BibT_eX]

[DOI]

Proceedings of the 27th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2019

Memory Trojan Attack on Neural Network Accelerators.

[BibT_eX]

[DOI]

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2019

Direct Training for Spiking Neural Networks: Faster, Larger, Better.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

GXNOR-Net: Training deep neural networks with ternary weights and activations without full-precision memory under a unified discretization framework.

[BibT_eX]

[DOI]

Neural Networks, 2018

Towards the minimum-cost control of target nodes in directed networks with linear dynamics.

[BibT_eX]

[DOI]

J. Frankl. Inst., 2018

Training deep neural networks with discrete state transition.

[BibT_eX]

[DOI]

Neurocomputing, 2018

Batch Normalization Sampling.

[BibT_eX]

[DOI]

CoRR, 2018

In-memory multiplication engine with SOT-MRAM based stochastic computing.

[BibT_eX]

[DOI]

CoRR, 2018

Direct Training for Spiking Neural Networks: Faster, Larger, Better.

[BibT_eX]

[DOI]

CoRR, 2018

L1-Norm Batch Normalization for Efficient Training of Deep Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2018

Towards a Unified Framework of Matrix Derivatives.

[BibT_eX]

[DOI]

IEEE Access, 2018

Crossbar-Aware Neural Network Pruning.

[BibT_eX]

[DOI]

IEEE Access, 2018

HitNet: Hybrid Ternary Recurrent Neural Network.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

TETRIS: TilE-matching the TRemendous Irregular Sparsity.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Spatio-Temporal Backpropagation for Training High-performance Spiking Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2017

Gated XNOR Networks: Deep Neural Networks with Ternary Weights and Activations under a Unified Discretization Framework.

[BibT_eX]

[DOI]

CoRR, 2017

2016

Hierarchical Chunking of Sequential Memory on Neuromorphic Architecture with Reduced Synaptic Plasticity.

[BibT_eX]

[DOI]

Frontiers Comput. Neurosci., 2016

2015

FPGA-based neuromorphic computing system with a scalable routing network.

[BibT_eX]

[DOI]

Proceedings of the 15th Non-Volatile Memory Technology Symposium, 2015

A new computing rule for neuromorphic engineering.

[BibT_eX]

[DOI]

Proceedings of the 15th Non-Volatile Memory Technology Symposium, 2015

Lei Deng

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