Tong Geng | DeepAI

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∙ 08/22/2023

Accel-GCN: High-Performance GPU Accelerator Design for Graph Convolution Networks

Graph Convolutional Networks (GCNs) are pivotal in extracting latent inf...

0 Xi Xie, et al. ∙

∙ 06/27/2023

PASNet: Polynomial Architecture Search Framework for Two-party Computation-based Secure Neural Network Deployment

Two-party computation (2PC) is promising to enable privacy-preserving de...

0 Hongwu Peng, et al. ∙

∙ 04/23/2023

TransFlow: Transformer as Flow Learner

Optical flow is an indispensable building block for various important co...

0 Yawen Lu, et al. ∙

∙ 03/20/2023

Machine Learning Automated Approach for Enormous Synchrotron X-Ray Diffraction Data Interpretation

Manual analysis of XRD data is usually laborious and time consuming. The...

0 Xiaodong Zhao, et al. ∙

∙ 02/05/2023

RRNet: Towards ReLU-Reduced Neural Network for Two-party Computation Based Private Inference

The proliferation of deep learning (DL) has led to the emergence of priv...

0 Hongwu Peng, et al. ∙

∙ 10/08/2022

Towards Real-Time Temporal Graph Learning

In recent years, graph representation learning has gained significant po...

0 Deniz Gurevin, et al. ∙

∙ 09/20/2022

PolyMPCNet: Towards ReLU-free Neural Architecture Search in Two-party Computation Based Private Inference

The rapid growth and deployment of deep learning (DL) has witnessed emer...

7 Hongwu Peng, et al. ∙

∙ 09/14/2022

Empowering GNNs with Fine-grained Communication-Computation Pipelining on Multi-GPU Platforms

The increasing size of input graphs for graph neural networks (GNNs) hig...

0 Yuke Wang, et al. ∙

∙ 09/11/2022

Towards Sparsification of Graph Neural Networks

As real-world graphs expand in size, larger GNN models with billions of ...

0 Hongwu Peng, et al. ∙

∙ 08/07/2022

A Length Adaptive Algorithm-Hardware Co-design of Transformer on FPGA Through Sparse Attention and Dynamic Pipelining

Transformers are considered one of the most important deep learning mode...

0 Hongwu Peng, et al. ∙

∙ 06/28/2022

H-GCN: A Graph Convolutional Network Accelerator on Versal ACAP Architecture

Graph Neural Networks (GNNs) have drawn tremendous attention due to thei...

0 Chengming Zhang, et al. ∙

∙ 06/16/2022

GMI-DRL: Empowering Multi-GPU Deep Reinforcement Learning with GPU Spatial Multiplexing

With the increasing popularity of robotics in industrial control and aut...

0 Yuke Wang, et al. ∙

∙ 06/06/2022

Dissecting Tensor Cores via Microbenchmarks: Latency, Throughput and Numerical Behaviors

Tensor Cores have been an important unit to accelerate Fused Matrix Mult...

0 Wei Sun, et al. ∙

∙ 06/05/2022

GAAF: Searching Activation Functions for Binary Neural Networks through Genetic Algorithm

Binary neural networks (BNNs) show promising utilization in cost and pow...

0 Yanfei Li, et al. ∙

∙ 03/07/2022

I-GCN: A Graph Convolutional Network Accelerator with Runtime Locality Enhancement through Islandization

Graph Convolutional Networks (GCNs) have drawn tremendous attention in t...

52 Tong Geng, et al. ∙

∙ 12/22/2021

GCoD: Graph Convolutional Network Acceleration via Dedicated Algorithm and Accelerator Co-Design

Graph Convolutional Networks (GCNs) have emerged as the state-of-the-art...

10 Haoran You, et al. ∙

∙ 09/18/2021

G-CoS: GNN-Accelerator Co-Search Towards Both Better Accuracy and Efficiency

Graph Neural Networks (GNNs) have emerged as the state-of-the-art (SOTA)...

0 Yongan Zhang, et al. ∙

∙ 09/13/2021

Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search

Molecular similarity search has been widely used in drug discovery to id...

0 Hongwu Peng, et al. ∙

∙ 08/10/2021

Binary Complex Neural Network Acceleration on FPGA

Being able to learn from complex data with phase information is imperati...

26 Hongwu Peng, et al. ∙

∙ 06/24/2021

CEAZ: Accelerating Parallel I/O via Hardware-Algorithm Co-Design of Efficient and Adaptive Lossy Compression

As supercomputers continue to grow to exascale, the amount of data that ...

0 Chengming Zhang, et al. ∙

∙ 06/23/2021

APNN-TC: Accelerating Arbitrary Precision Neural Networks on Ampere GPU Tensor Cores

Over the years, accelerating neural networks with quantization has been ...

0 Boyuan Feng, et al. ∙

∙ 03/28/2021

BCNN: Binary Complex Neural Network

Binarized neural networks, or BNNs, show great promise in edge-side appl...

0 Yanfei Li, et al. ∙

∙ 09/16/2020

Comparison Lift: Bandit-based Experimentation System for Online Advertising

Comparison Lift is an experimentation-as-a-service (EaaS) application fo...

0 Tong Geng, et al. ∙

∙ 05/11/2020

CSB-RNN: A Faster-than-Realtime RNN Acceleration Framework with Compressed Structured Blocks

Recurrent neural networks (RNNs) have been widely adopted in temporal se...

0 Runbin Shi, et al. ∙

∙ 08/23/2019

UWB-GCN: Hardware Acceleration of Graph-Convolution-Network through Runtime Workload Rebalancing

The recent development of deep learning has mostly been focusing on Eucl...

0 Tong Geng, et al. ∙

∙ 07/04/2019

Online Evaluation of Audiences for Targeted Advertising via Bandit Experiments

Firms implementing digital advertising campaigns face a complex problem ...

0 Tong Geng, et al. ∙

∙ 05/14/2019

Fully Integrated On-FPGA Molecular Dynamics Simulations

The implementation of Molecular Dynamics (MD) on FPGAs has received subs...

0 Chen Yang, et al. ∙

∙ 01/04/2019

A Scalable Framework for Acceleration of CNN Training on Deeply-Pipelined FPGA Clusters with Weight and Workload Balancing

Deep Neural Networks (DNNs) have revolutionized numerous applications, b...

10 Tong Geng, et al. ∙

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