Tao Luo

Orcid: 0000-0002-3415-3676

Affiliations:
  • Nanyang Technological University, Institute of High Performance Computing, Singapore


According to our database1, Tao Luo authored at least 52 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2024
Optimizing for In-Memory Deep Learning With Emerging Memory Technology.
IEEE Trans. Neural Networks Learn. Syst., November, 2024

Hierarchical Weight Averaging for Deep Neural Networks.
IEEE Trans. Neural Networks Learn. Syst., September, 2024

Evolutionary Architecture Search for Generative Adversarial Networks Based on Weight Sharing.
IEEE Trans. Evol. Comput., June, 2024

MedNAS: Multiscale Training-Free Neural Architecture Search for Medical Image Analysis.
IEEE Trans. Evol. Comput., June, 2024

Efficient Spiking Neural Networks With Radix Encoding.
IEEE Trans. Neural Networks Learn. Syst., March, 2024

RCT: Resource Constrained Training for Edge AI.
IEEE Trans. Neural Networks Learn. Syst., February, 2024

EDCompress: Energy-Aware Model Compression for Dataflows.
IEEE Trans. Neural Networks Learn. Syst., January, 2024

A principled framework for explainable multimodal disentanglement.
Inf. Sci., 2024

IMI: In-memory Multi-job Inference Acceleration for Large Language Models.
Proceedings of the 53rd International Conference on Parallel Processing, 2024

Table-Lookup MAC: Scalable Processing of Quantised Neural Networks in FPGA Soft Logic.
Proceedings of the 2024 ACM/SIGDA International Symposium on Field Programmable Gate Arrays, 2024

UniM<sup>2</sup>AE: Multi-modal Masked Autoencoders with Unified 3D Representation for 3D Perception in Autonomous Driving.
Proceedings of the Computer Vision - ECCV 2024, 2024

2023
Soft Error Reliability Analysis of Vision Transformers.
IEEE Trans. Very Large Scale Integr. Syst., December, 2023

Desire backpropagation: A lightweight training algorithm for multi-layer spiking neural networks based on spike-timing-dependent plasticity.
Neurocomputing, December, 2023

Exploring Winograd Convolution for Cost-Effective Neural Network Fault Tolerance.
IEEE Trans. Very Large Scale Integr. Syst., November, 2023

Statistical Modeling of Soft Error Influence on Neural Networks.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., November, 2023

Simeuro: A Hybrid CPU-GPU Parallel Simulator for Neuromorphic Computing Chips.
IEEE Trans. Parallel Distributed Syst., October, 2023

DeepFire2: A Convolutional Spiking Neural Network Accelerator on FPGAs.
IEEE Trans. Computers, October, 2023

Accelerating Deformable Convolution Networks with Dynamic and Irregular Memory Accesses.
ACM Trans. Design Autom. Electr. Syst., July, 2023

Achieving Green AI with Energy-Efficient Deep Learning Using Neuromorphic Computing.
Commun. ACM, July, 2023

Benchmarking Quantum(-Inspired) Annealing Hardware on Practical Use Cases.
IEEE Trans. Computers, June, 2023

When quantum annealing meets multitasking: Potentials, challenges and opportunities.
Array, March, 2023

VQA4CIR: Boosting Composed Image Retrieval with Visual Question Answering.
CoRR, 2023

Ultra-Long Sequence Distributed Transformer.
CoRR, 2023

ApproxABFT: Approximate Algorithm-Based Fault Tolerance for Vision Transformers.
CoRR, 2023

Reliability Analysis of Vision Transformers.
CoRR, 2023

MA-BERT: Towards Matrix Arithmetic-only BERT Inference by Eliminating Complex Non-Linear Functions.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
E3NE: An End-to-End Framework for Accelerating Spiking Neural Networks With Emerging Neural Encoding on FPGAs.
IEEE Trans. Parallel Distributed Syst., 2022

NC-Net: Efficient Neuromorphic Computing Using Aggregated Subnets on a Crossbar-Based Architecture With Nonvolatile Memory.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022

Hardware-software co-exploration with racetrack memory based in-memory computing for CNN inference in embedded systems.
J. Syst. Archit., 2022

APT: The master-copy-free training method for quantised neural network on edge devices.
J. Parallel Distributed Comput., 2022

Corrigendum to "Coreset: Hierarchical neuromorphic computing supporting large-scale neural networks with improved resource efficiency" [Neurocomputing (2022) 128-140].
Neurocomputing, 2022

Coreset: Hierarchical neuromorphic computing supporting large-scale neural networks with improved resource efficiency.
Neurocomputing, 2022

Temperature Annealing Knowledge Distillation from Averaged Teacher.
Proceedings of the 42nd IEEE International Conference on Distributed Computing Systems, 2022

A Resource-efficient Spiking Neural Network Accelerator Supporting Emerging Neural Encoding.
Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition, 2022

Winograd convolution: a perspective from fault tolerance.
Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

2021
DTNN: Energy-efficient Inference with Dendrite Tree Inspired Neural Networks for Edge Vision Applications.
CoRR, 2021

Evolutionary Multi-Objective Model Compression for Deep Neural Networks.
IEEE Comput. Intell. Mag., 2021

QROSS: QUBO Relaxation Parameter optimisation via Learning Solver Surrogates.
Proceedings of the 41st IEEE International Conference on Distributed Computing Systems Workshops, 2021

DeepFire: Acceleration of Convolutional Spiking Neural Network on Modern Field Programmable Gate Arrays.
Proceedings of the 31st International Conference on Field-Programmable Logic and Applications, 2021

2020
An FPGA-Based Hardware Emulator for Neuromorphic Chip With RRAM.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2020

EDCompress: Energy-Aware Model Compression with Dataflow.
CoRR, 2020

NCPower: Power Modelling for NVM-based Neuromorphic Chip.
Proceedings of the International Conference on Neuromorphic Systems, 2020

Energy Efficient In-memory Integer Multiplication Based on Racetrack Memory.
Proceedings of the 40th IEEE International Conference on Distributed Computing Systems, 2020

Adaptive Precision Training for Resource Constrained Devices.
Proceedings of the 40th IEEE International Conference on Distributed Computing Systems, 2020

0.5V 4.8 pJ/SOP 0.93µW Leakage/core Neuromorphic Processor with Asynchronous NoC and Reconfigurable LIF Neuron.
Proceedings of the IEEE Asian Solid-State Circuits Conference, 2020

2019
A System-Level Simulator for RRAM-Based Neuromorphic Computing Chips.
ACM Trans. Archit. Code Optim., 2019

2018
Racetrack memory based logic design for in-memory computing
PhD thesis, 2018

2017
A Hybrid Logic Block Architecture in FPGA for Holistic Efficiency.
IEEE Trans. Circuits Syst. II Express Briefs, 2017

A novel two-stage modular multiplier based on racetrack memory for asymmetric cryptography.
Proceedings of the 2017 IEEE/ACM International Conference on Computer-Aided Design, 2017

2016
Cost-efficient Acceleration of Hardware Trojan Detection Through Fan-Out Cone Analysis and Weighted Random Pattern Technique.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2016

A racetrack memory based in-memory booth multiplier for cryptography application.
Proceedings of the 21st Asia and South Pacific Design Automation Conference, 2016

2015
Hierarchical Library Based Power Estimator for Versatile FPGAs.
Proceedings of the IEEE 9th International Symposium on Embedded Multicore/Many-core Systems-on-Chip, 2015


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