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.
The Refreshingly Simple Cross-Platform C++ Dataflow / Patching / Pipelining / Graph Processing / Stream Processing / Reactive Programming Framework
HLS-based Graph Processing Framework on FPGAs
Out-of-core graph processing on a single machine.
GraphMat graph analytics framework
Cross-Platform Graphical Tool for DSPatch
A graph linear algebra overlay
An efficient concurrent graph processing system
DSPatch Component Repository
Software implementation of semantic network storage and processing
Personalized PageRank (PPR) on GraphLab PowerGraph
A parallel packed CSR data structure for large-scale dynamic graphs
VGL is a high-performance graph processing framework, designed for modern NEC SX-Aurora TSUBASA vector architecture. VGL significantly outperforms many state-of the art graph-processing frameworks for modern multicore CPUs and NVIDIA GPUs, such as Gunrock, CuSHA, Ligra, Galois, GAPBS.
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.
🌌 Flexible graph construction and data pre-processing engine
Software implementation of semantic network program interpreter
a distributed graph processing system based on key-value store
Spatial Graph Extractor. Library and scripts to study graphs extracted from binary images, or to generate graphs and analyze them completely in-silico. Used at least in biopolymers simulations and vascular networks.
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