A collection of awesome papers about graph processing.
- GraphLab -
GraphLab: A New Framework For Parallel Machine Learning(UAI'10). [paper] - Galois -
A Lightweight Infrastructure for Graph Analytics(SOSP'13). [paper] - GRACE -
Asynchronous Large-Scale Graph Processing Made Easy(CIDR'13). [paper] - Ligra -
Ligra: A Lightweight Graph Processing Framework for Shared Memory(PPoPP'13). [paper], [code] - Polymer -
NUMA-Aware Graph-Structured Analytics(PPoPP'15). [paper], [code] - GraphMat -
GraphMat: High performance graph analytics made productive(VLDB'15). [paper], [code] - Graph Ordering -
Speedup Graph Processing by Graph Ordering(SIGMOD'16). [paper], [slides], [code] - GPOP -
GPOP: A cache and memory-efficient framework for Graph Processing Over Partitions(PPoPP'19 poster). [poster], [arxiv], [code]
- Pregel -
Pregel: A System for Large-Scale Graph Processing(SIGMOD'10). [paper] - Distributed GraphLab -
Distributed GraphLab: A Framework for Machine Learning and Data Mining in the Cloud(VLDB'12). [paper] - PowerGraph -
PowerGraph: Distributed Graph-Parallel Computation on Natural Graphs(OSDI'12). [paper], [code] - GPS -
GPS: A Graph Processing System(SSDBM'13). [paper] - Mizan -
Mizan: A System for Dynamic Load Balancing in Large-scale Graph Processing(EuroSys'13). [paper], [code] - Blogel -
Blogel: A Block-Centric Framework for Distributed Computation on Real-World Graphs(VLDB'14). [paper], [code] - Giraph++ -
From "Think Like a Vertex" to "Think Like a Graph"(VLDB'14). [paper] - GraphX -
GraphX: Graph Processing in a Distributed Dataflow Framework(OSDI'14). [paper], [code] - PowerLyra -
PowerLyra: Differentiated Graph Computation and Partitioning on Skewed Graphs(EuroSys'15). [paper], [code] - PowerSwith -
SYNC or ASYNC: Time to Fuse for Distributed Graph-Parallel Computation(PPoPP'15). [paper] - Gemini -
Gemini: A Computation-Centric Distributed Graph Processing System(OSDI'16). [paper], [code] - GRAPE -
Parallelizing Sequential Graph Computations(SIGMOD'17). [paper]
- GraphChi -
GraphChi: Large-Scale Graph Computation on Just a PC(OSDI'12). [paper], [code] - X-Stream -
X-Stream: Edge-centric Graph Processing using Streaming Partitions(SOSP'13). [paper], [code] - TurboGraph -
TurboGraph: A Fast Parallel Graph Engine Handling Billion-scale Graphs in a Single PC(KDD'13). [paper] - PathGraph -
Fast Iterative Graph Computation: A Path Centric Approach(SC'14). [paper], [code] - GridGraph -
GridGraph: Large-Scale Graph Processing on a Single Machine Using 2-Level Hierarchical Partitioning(USENIX ATC'15). [paper], [code] - VENUS -
VENUS: Vertex-Centric Streamlined Graph Computation on a Single PC(ICDE'15). [paper] - FlashGraph -
FlashGraph: Processing Billion-Node Graphs on an Array of Commodity SSDs(FAST'15). [paper], [code] - Dynamic Shards -
Load the Edges You Need: A Generic I/O Optimization for Disk-based Graph Processing(ATC'16). [paper], [slides], [similar code] - Graphene -
Graphene: Fine-Grained IO Management for Graph Computing(FAST'17). [paper], [slides], [code] - Mosaic -
Mosaic: Processing a Trillion-Edge Graph on a Single Machine(EuroSys'17). [paper], [slides], [code] - pre-processing trade-off -
Everything you always wanted to know about multicore graph processing but were afraid to ask(ATC'17). [paper], [slides], [code] - CLIP -
Squeezing out All the Value of Loaded Data: An Out-of-core Graph Processing System with Reduced Disk I/O(ATC'17). [paper], [slides], [author] - GraFBoost -
GraFBoost: Accelerated Flash Storage for External Graph Analytics(ISCA'18). [paper], [code] - GraphOne -
GraphOne: A Data Store for Real-time Analytics on Evolving Graphs(FAST'19). [paper], [code]
- Chaos -
Chaos: Scale-out Graph Processing from Secondary Storage(SOSP'15). [paper], [code] - Pregelix -
Pregelix: Big(ger) Graph Analytics on A Dataflow Engine(VLDB'15). [paper], [code] - TurboGraph++ -
TurboGraph++: A Scalable and Fast Graph Analytics System(SIGMOD'18). [paper] - GraphD -
GraphD: Distributed Vertex-Centric Graph Processing Beyond the Memory Limit(TPDS'18). [paper], [code]
- graph2vec -
graph2vec: Learning Distributed Representations of Graphs(MLG'17, Held in conjunction with KDD). [paper], [arxiv], [code] - GraphSage -
GraphSage: Representation Learning on Large Graphs(NIPS'17). [paper], [arxiv], [code], [pytorch version], [project] - graph2gauss -
Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking(ICLR'18). [paper], [code] - Must-read papers on NRL/NE
- Awesome Graph Embedding
- Awesome Network Embedding
- Deep Learning on Graphs: a roadmap
- Dynamic Knowledge Graph Completion
- Graph Neural Network Review
- Large Scale Network Analytics with SNAP
- Representation Learning on Networks
- 6.886: Graph Analytics at MIT
- A curated list of awesome network analysis resources
- A curated list of resources for graph databases and graph computing tools
- Graph Database Acceleration Survey
- Primitives & Graph Processing
- Awesome Community Detection
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