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

• The Graph 500 List
• The High Performance Conjugate Gradients (HPCG)
• GraphChallenge

1. Papers on Graph Aanlytics

• 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

This work is licensed under a Creative Commons Attribution 4.0 International License.