Programmable CUDA/C++ GPU Graph Analytics
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Updated
Apr 21, 2024 - C++
Programmable CUDA/C++ GPU Graph Analytics
A computation-centric distributed graph processing system.
A graph database written in rust
Out-of-core graph processing on a single machine.
The Refreshingly Simple Cross-Platform C++ Dataflow / Patching / Pipelining / Graph Processing / Stream Processing / Reactive Programming Framework
GraphMat graph analytics framework
HLS-based Graph Processing Framework on FPGAs
Software implementation of semantic network storage and processing
Cross-Platform Graphical Tool for DSPatch
Transforming Graphs for Efficient Irregular Graph Processing on GPUs
A collection of resources on dynamic/streaming/temporal/evolving graph processing systems, databases, data structures, datasets, and related academic and industrial work
A distributed in-memory key-value storage for billions of small objects.
Incremental view maintenance for openCypher graph queries.
Node-based image processing with GEGL and Flowhub
An efficient concurrent graph processing system
G3: A Programmable GNN Training System on GPU
DGraph is a system for directed graph processing with taking advantage of the strongly connected component structure. On this system, most graph partitions are able to reach convergence in order and need to be loaded into the main memory for exactly once, getting much lower data access cost and faster convergence.
DSPatch Component Repository
Memory allocator and management for billions of very small objects
A parallel packed CSR data structure for large-scale dynamic graphs
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