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08/16/2023
Accelerating Generic Graph Neural Networks via Architecture, Compiler, Partition Method Co-Design
Graph neural networks (GNNs) have shown significant accuracy improvement...
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07/23/2023
MARS: Exploiting Multi-Level Parallelism for DNN Workloads on Adaptive Multi-Accelerator Systems
Along with the fast evolution of deep neural networks, the hardware syst...
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07/19/2023
Density-invariant Features for Distant Point Cloud Registration
Registration of distant outdoor LiDAR point clouds is crucial to extendi...
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06/19/2023
DFlow: Efficient Dataflow-based Invocation Workflow Execution for Function-as-a-Service
The Serverless Computing is becoming increasingly popular due to its eas...
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05/27/2023
AdaptGear: Accelerating GNN Training via Adaptive Subgraph-Level Kernels on GPUs
Graph neural networks (GNNs) are powerful tools for exploring and learni...
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05/04/2023
APR: Online Distant Point Cloud Registration Through Aggregated Point Cloud Reconstruction
For many driving safety applications, it is of great importance to accur...
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04/15/2023
OliVe: Accelerating Large Language Models via Hardware-friendly Outlier-Victim Pair Quantization
Transformer-based large language models (LLMs) have achieved great succe...
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03/23/2023
MoGDE: Boosting Mobile Monocular 3D Object Detection with Ground Depth Estimation
Monocular 3D object detection (Mono3D) in mobile settings (e.g., on a ve...
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03/23/2023
MonoATT: Online Monocular 3D Object Detection with Adaptive Token Transformer
Mobile monocular 3D object detection (Mono3D) (e.g., on a vehicle, a dro...
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01/14/2023
Async-fork: Mitigating Query Latency Spikes Incurred by the Fork-based Snapshot Mechanism from the OS Level
In-memory key-value stores (IMKVSes) serve many online applications beca...
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12/02/2022
MMBench: Benchmarking End-to-End Multi-modal DNNs and Understanding Their Hardware-Software Implications
The explosive growth of various types of big data and advances in AI tec...
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09/22/2022
Nesting Forward Automatic Differentiation for Memory-Efficient Deep Neural Network Training
An activation function is an element-wise mathematical function and play...
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08/30/2022
ANT: Exploiting Adaptive Numerical Data Type for Low-bit Deep Neural Network Quantization
Quantization is a technique to reduce the computation and memory cost of...
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08/25/2022
Efficient Activation Quantization via Adaptive Rounding Border for Post-Training Quantization
Post-training quantization (PTQ) attracts increasing attention due to it...
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06/29/2022
SALO: An Efficient Spatial Accelerator Enabling Hybrid Sparse Attention Mechanisms for Long Sequences
The attention mechanisms of transformers effectively extract pertinent i...
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05/15/2022
Transkimmer: Transformer Learns to Layer-wise Skim
Transformer architecture has become the de-facto model for many machine ...
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02/14/2022
SQuant: On-the-Fly Data-Free Quantization via Diagonal Hessian Approximation
Quantization of deep neural networks (DNN) has been proven effective for...
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01/17/2022
VELTAIR: Towards High-Performance Multi-tenant Deep Learning Services via Adaptive Compilation and Scheduling
Deep learning (DL) models have achieved great success in many applicatio...
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12/24/2021
The Serverless Computing Survey: A Technical Primer for Design Architecture
The development of cloud infrastructures inspires the emergence of cloud...
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12/16/2021
Block-Skim: Efficient Question Answering for Transformer
Transformer models have achieved promising results on natural language p...
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10/08/2021
Characterizing and Demystifying the Implicit Convolution Algorithm on Commercial Matrix-Multiplication Accelerators
Many of today's deep neural network accelerators, e.g., Google's TPU and...
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09/08/2021
Dubhe: Towards Data Unbiasedness with Homomorphic Encryption in Federated Learning Client Selection
Federated learning (FL) is a distributed machine learning paradigm that ...
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08/25/2021
Pagurus: Eliminating Cold Startup in Serverless Computing with Inter-Action Container Sharing
Serverless computing provides fine-grain resource sharing between Cloud ...
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07/19/2021
ZIPPER: Exploiting Tile- and Operator-level Parallelism for General and Scalable Graph Neural Network Acceleration
Graph neural networks (GNNs) start to gain momentum after showing signif...
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11/11/2020
DLFusion: An Auto-Tuning Compiler for Layer Fusion on Deep Neural Network Accelerator
Many hardware vendors have introduced specialized deep neural networks (...
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11/02/2020
How Far Does BERT Look At:Distance-based Clustering and Analysis of BERT's Attention
Recent research on the multi-head attention mechanism, especially that i...
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09/02/2020
Architectural Implications of Graph Neural Networks
Graph neural networks (GNN) represent an emerging line of deep learning ...
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08/29/2020
Accelerating Sparse DNN Models without Hardware-Support via Tile-Wise Sparsity
Network pruning can reduce the high computation cost of deep neural netw...
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08/23/2020
Ptolemy: Architecture Support for Robust Deep Learning
Deep learning is vulnerable to adversarial attacks, where carefully-craf...
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05/05/2020
Towards QoS-Aware and Resource-Efficient GPU Microservices Based on Spatial Multitasking GPUs In Datacenters
While prior researches focus on CPU-based microservices, they are not ap...
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02/18/2020
Balancing Efficiency and Flexibility for DNN Acceleration via Temporal GPU-Systolic Array Integration
The research interest in specialized hardware accelerators for deep neur...
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12/27/2019
URSA: Precise Capacity Planning and Contention-aware Scheduling for Public Clouds
Database platform-as-a-service (dbPaaS) is developing rapidly and a larg...
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04/17/2019
Adversarial Defense Through Network Profiling Based Path Extraction
Recently, researchers have started decomposing deep neural network model...
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04/12/2019
Position-Aware Convolutional Networks for Traffic Prediction
Forecasting the future traffic flow distribution in an area is an import...
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03/18/2019
Knowledge Graph Convolutional Networks for Recommender Systems
To alleviate sparsity and cold start problem of collaborative filtering ...
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01/23/2019
Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation
Collaborative filtering often suffers from sparsity and cold start probl...
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03/09/2018
Ripple Network: Propagating User Preferences on the Knowledge Graph for Recommender Systems
To address the sparsity and cold start problem of collaborative filterin...
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03/06/2018
Personalized Attention-Aware Exposure Control Using Reinforcement Learning
We propose a reinforcement learning approach for real-time exposure cont...
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01/25/2018
DKN: Deep Knowledge-Aware Network for News Recommendation
Online news recommender systems aim to address the information explosion...
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12/03/2017
SHINE: Signed Heterogeneous Information Network Embedding for Sentiment Link Prediction
In online social networks people often express attitudes towards others,...
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12/03/2017
Joint Topic-Semantic-aware Social Recommendation for Online Voting
Online voting is an emerging feature in social networks, in which users ...
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11/22/2017
GraphGAN: Graph Representation Learning with Generative Adversarial Nets
The goal of graph representation learning is to embed each vertex in a g...
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10/06/2015
Unsupervised Extraction of Video Highlights Via Robust Recurrent Auto-encoders
With the growing popularity of short-form video sharing platforms such a...
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09/19/2014
Rank-Aware Dynamic Migrations and Adaptive Demotions for DRAM Power Management
Modern DRAM architectures allow a number of low-power states on individu...
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11/04/2012
