The long list from MIT

Other List

GNN papers

NN-on-Silicon

Graph Sampling with Fast Random Walker on HBM-enabled FPGA Accelerators FPL'21

IntersectX: An Accelerator for Graph Mining

A Locality-Aware Energy-Efficient Accelerator for Graph Mining Applications MICRO'20

The TrieJax Architecture: Accelerating Graph Operations Through Relational Joins ASPLOS'20

A Collection

Computing Graph Neural Networks: A Survey from Algorithms to Accelerators

I-GCN: A Graph Convolutional Network Accelerator with Runtime Locality Enhancement through Islandization MICRO'21

Crossbar based Processing in Memory Accelerator Architecture for Graph Convolutional Networks ICCAD'21

A Deep Dive Into Understanding The Random Walk-Based Temporal Graph Learning IISWC'21

GCNear: A Hybrid Architecture for Efficient GCN Training with Near-Memory Processing

GCNAX: A Flexible and Energy-efficient Accelerator for Graph Convolutional Neural Networks HPCA'21

Hardware Acceleration of Graph Neural Networks DAC'20

AWB-GCN: A Graph Convolutional Network Accelerator with Runtime Workload Rebalancing MICRO'20

HyGCN: A GCN Accelerator with Hybrid Architecture HPCA'20

GraphACT: Accelerating GCN Training on CPU-FPGA Heterogeneous Platforms FPGA'20

A Taxonomy for Classification and Comparison of Dataflows for GNN Accelerators

Architectural Implication of Graph Neural Networks

GReTA: Hardware Optimized Graph Processing for GNNs

GRIP: A Graph Neural Network Accelerator Architecture

Skywalker: Efficient Alias-method-based Graph Sampling and Random Walk on GPUs PACT'21 Skywalker website

KnightKing: A Fast Distributed Graph RandomWalk Engine SOSP'19 KnightKing website

Accelerating Graph Sampling for Graph Machine Learning using GPUs EuroSys'21 NextDoor website

C-SAW: A Framework for Graph Sampling and Random Walk on GPUs SC'20 C-SAW website

ThunderRW: An In-Memory Graph RandomWalk Engine VLDB'21 ThunderRW website

Memory-Aware Framework for Efficient Second-Order Random Walk on Large Graphs SIGMOD'20

First: Fast interactive attributed subgraph matching KDD'17

In-Memory Subgraph Matching: An In-depth Study SIGMOD'2020 website

Efficient Subgraph Matching: Harmonizing Dynamic Programming, Adaptive Matching Order, and Failing Set Together SIGMOD'19 DAF website

Scaling Up Subgraph Query Processing with Efficient Subgraph Matching ICDE'19

Efficient Parallel Subgraph Enumeration on a Single Machine ICDE'19

Fast and Robust Distributed Subgraph Enumeration VLDB'19

Peregrine: A Pattern-Aware Graph Mining System Eurosys'20

Optimizing Subgraph Queries by Combining Binary and Worst-Case Optimal Joins VLDB'19

EmptyHeaded: A Relational Engine for Graph Processing SIGMOD'16

The Power of Pivoting for Exact Clique Counting WSDM'20

DUALSIM: Parallel Subgraph Enumeration in a Massive Graph on a Single Machine SIGMOD'16

AutoMine SOSP'19

Arabesque SOSP'2015

RStream OSDI'18

GraphPi website SC'20

Understanding and Bridging the Gaps in Current GNN Performance Optimizations PPoPP'21

Dorylus: Affordable, Scalable, and Accurate GNN Training over Billion-Edge Graphs OSDI'21

GNNAdvisor: An Efficient Runtime System for GNN Acceleration on GPUs OSDI'21

Rubik: A Hierarchical Architecture for Efficient Graph Learning TCAD'21

fuseGNN: Accelerating Graph Convolutional Neural Network Training on GPGPU ICCAD'20

Deep Graph Library Optimizations for Intel(R) x86 Architecture

Improving the Accuracy, Scalability, and Performance of Graph Neural Networks with Roc MLSys'20 Roc website

FeatGraph: A Flexible and Efficient Backend for Graph Neural Network Systems SC'20 FeatGraph website

GraphSAINT: Graph Sampling Based Inductive Learning Method ICLR'20 GraphSAINT website

Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs ICLR'19 DGL website

Fast Graph Representation Learning with PyTorch Geometric ICLR'19 PyG website

NeuGraph: Parallel Deep Neural Network Computation on Large Graphs USENIX ATC'19 NeuGraph website

CAGNET website SC'20

AGL: a scalable system for industrial-purpose graph machine learning VLDB'20

Accurate, Efficient and Scalable Graph Embedding IPDPS'19

Semi-Supervised Classification with Graph Convolutional Networks ICLR'17 GCN website

The Logical Expressiveness of Graph Neural Networks

How Powerful are Graph Neural Networks? ICLR'19 GIN website

Hierarchical Graph Representation Learning with Differentiable Pooling NeurIPS'18 diffpool website

Inductive Representation Learning on Large Graphs NIPS'17 GraphSAGE website

Stochastic Training of Graph Convolutional Networks with Variance Reduction ICML'18 S-GCN

Adaptive Sampling Towards Fast Graph Representation Learning NIPS'18 AS-GCN website

Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks KDD'19 ClusterGCN website

FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling ICLR'18 FastGCN website

Large-Scale Learnable Graph Convolutional Networks KDD'18 LGCN website

Representation Learning on Graphs with Jumping Knowledge Networks KDD'18 JK-net code

DeepWalk: Online Learning of Social Representations KDD'14

node2vec: Scalable Feature Learning for Networks KDD'16

GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding WWW'19 GraphVite website

DepGraph: A Dependency-Driven Accelerator for Efficient Iterative Graph Processing HPCA'21

P-OPT: Practical Optimal Cache Replacement for Graph Analytics HPCA'21

ThunderGP: HLS-based Graph Processing Framework on FPGAs FPGA'21

HitGraph: High-throughput Graph Processing Framework on FPGA TPDS'19

Exploiting Locality in Graph Analytics through Hardware-Accelerated Traversal Scheduling MICRO'18

UWB-GCN: Accelerating Graph Convolutional Networks through Runtime Workload Rebalancing

Graphicionado: A High-Performance and Energy Efficient Accelerator for Graph Analytics MICRO'16

GraphR: Accelerating Graph Processing Using ReRAM HPCA'18

GraphQ: Scalable PIM-Based Graph Processing MICRO'19

GraphP: Reducing Communication of PIM-based Graph Processing with Efficient Data Partition HPCA'18

GraphSAR: A Sparsity-Aware Processing-in-Memory Architecture for Large-Scale Graph Processing on ReRAMs ASPDAC'19

Alleviating Irregularity in Graph Analytics Acceleration: a Hardware/Software Co-Design Approach MICRO'19

GraphABCD: Scaling Out Graph Analytics with Asynchronous Block Coordinate Descent ISCA'20

GaaS-X: Graph Analytics Accelerator Supporting Sparse Data Representation Using Crossbar Architectures ISCA'20

POSTER: Domain-Specialized Cache Management for Graph Analytics PACT'19 code

Domain-Specialized Cache Management for Graph Analytics HPCA'20

Q100: The architecture and design of a database processing unit ASPLOS'14

Analysis and Optimization of the Memory Hierarchy for Graph Processing Workloads HPCA'19

SCU: a GPU stream compaction unit for graph processing ISCA'19

Balancing Memory Accesses for Energy-Efficient Graph Analytics Accelerators ISLPED'19

Energy Efficient Architecture for Graph Analytics Accelerators ISCA'16

GraphH: A Processing-in-Memory Architecture for Large-Scale Graph Processing TCADICS

GraFBoost: Using accelerated flash storage for external graph analytics ISCA'18

Galois

Ligra

PowerGraph

Introduction to Graph Neural Networks Book

The Ubiquity of Large Graphs and Surprising Challenges of Graph Processing VLDB'18

Link prediction in complex networks: A survey

Survey on social community detection

Practice of Streaming Processing of Dynamic Graphs: Concepts, Models, and Systems