English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Given the growing importance of large-scale graph analytics, there is a needto improve the performance of graph analysis frameworks without compromising onproductivity. GraphMat is our solution to bridge this gap between auser-friendly graph analytics framework and native, hand-optimized code.GraphMat functions by taking vertex programs and mapping them to highperformance sparse matrix operations in the backend. We get the productivitybenefits of a vertex programming framework without sacrificing performance.GraphMat is in C++, and we have been able to write a diverse set of graphalgorithms in this framework with the same effort compared to other vertexprogramming frameworks. GraphMat performs 1.2-7X faster than high performanceframeworks such as GraphLab, CombBLAS and Galois. It achieves better multicorescalability (13-15X on 24 cores) than other frameworks and is 1.2X off native,hand-optimized code on a variety of different graph algorithms. Since GraphMatperformance depends mainly on a few scalable and well-understood sparse matrixoperations, GraphMatcan naturally benefit from the trend of increasingparallelism on future hardware.

GraphMat: High performance graph analytics made productive