Graph Analytics

Sep 18, 2024

Event: Developer Day for Financial Services

Join this virtual developer day to learn how AI and Machine Learning can revolutionize fraud detection and financial crime prevention.
1 MIN READ
Decorative image of a datacenter with an overlay of a network model.
Sep 04, 2024

Accelerated, Production-Ready Graph Analytics for NetworkX Users

NetworkX is a popular, easy-to-use Python library for graph analytics. However, its performance and scalability may be unsatisfactory for medium-to-large-sized...
11 MIN READ
May 09, 2024

Revolutionizing Graph Analytics: Next-Gen Architecture with NVIDIA cuGraph Acceleration

In our previous exploration of graph analytics, we uncovered the transformative power of GPU-CPU fusion using NVIDIA cuGraph. Building upon those insights, we...
9 MIN READ
Decorative image of graphs as light web.
Apr 03, 2024

Optimizing Memory and Retrieval for Graph Neural Networks with WholeGraph, Part 2

Large-scale graph neural network (GNN) training presents formidable challenges, particularly concerning the scale and complexity of graph data. These challenges...
5 MIN READ
An illustration representing WholeGraph.
Mar 08, 2024

Optimizing Memory and Retrieval for Graph Neural Networks with WholeGraph, Part 1

Graph neural networks (GNNs) have revolutionized machine learning for graph-structured data. Unlike traditional neural networks, GNNs are good at capturing...
9 MIN READ
Decorative image of concentric circles of light with linked points of light at the top.
Nov 08, 2023

Accelerating NetworkX on NVIDIA GPUs for High Performance Graph Analytics

NetworkX states in its documentation that it is “…a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of...
12 MIN READ
Promo card for AMA with two people in a conversation.
Apr 06, 2023

Ask Me Anything: Experts Answer Your NVIDIA cuGraph Questions Live

Join us April 12 and ask experts about NVIDIA cuGraph with added support for GNN, accelerated aggregators, models, and extensions to DGL and PyG.
1 MIN READ
Web of wires forming geometric shapes.
Aug 17, 2022

Using Network Graphs to Visualize Potential Fraud on Ethereum Blockchain

Beyond the unimaginable prices for monkey pictures, NFT's underlying technology provides companies with a new avenue to directly monetize their online...
9 MIN READ
Aug 16, 2022

Running Large-Scale Graph Analytics with Memgraph and NVIDIA cuGraph Algorithms

With the latest Memgraph Advanced Graph Extensions (MAGE) release, you can now run GPU-powered graph analytics from Memgraph in seconds, while working in...
9 MIN READ
Apr 23, 2021

Similarity in Graphs: Jaccard Versus the Overlap Coefficient

There is a wide range of graph applications and algorithms that I hope to discuss through this series of blog posts, all with a bias toward what is in RAPIDS...
12 MIN READ
Sep 26, 2016

The Intersection of Large-Scale Graph Analytics and Deep Learning

Figure 1: An example graph in which entities are represented by nodes and relationships are...
14 MIN READ
May 12, 2016

Fast Spectral Graph Partitioning on GPUs

Graphs are mathematical structures used to model many types of relationships and processes in physical, biological, social and information systems. They are...
15 MIN READ
Apr 05, 2016

CUDA 8 Features Revealed

Today I'm excited to announce the general availability of CUDA 8, the latest update to NVIDIA's powerful parallel computing platform and programming model. In...
19 MIN READ
Figure 1: Graph algorithms exhibit non-locality and data-dependent parallelism. Large graphs, such as this map of the internet, represent billion-edge challenges that push the bandwidth limits of existing hardware architectures.
Mar 21, 2016

What to Do with All That Bandwidth? GPUs for Graph and Predictive Analytics

Figure 1: Graph algorithms exhibit non-locality and data-dependent parallelism. Large graphs, such...
14 MIN READ