mapgraph Wiki

Massively Parallel Graph processing on GPUs -- now part of Blazegraph

Status: Beta

Brought to you by: beebs, hyandell, mrpersonick, thompsonbry

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Welcome to the MapGraph wiki!

The MapGraph API makes it easy to develop high performance graph analytics on GPUs. The API is based on the Gather-Apply-Scatter (GAS) model as used in GraphLab. To deliver high performance computation and efficiently utilize the high memory bandwidth of GPUs, MapGraph’s CUDA kernels use multiple sophisticated strategies, such as vertex-degree-dependent dynamic parallelism granularity and frontier compaction.

Download MapGraph today. See the README to get started.

ReleaseGuide

The wiki uses Markdown syntax.

Project Members:

Brad Bebee (admin)
Bryan Thompson (admin)
Henri Yandell (admin)
Mike Personick (admin)

Wiki: ReleaseGuide

Discussion

Walter - 2017-04-27

Hi, I 'm trying to profile load efficiency of MapGraph by using nvprof --metrics branch_efficiency there is a warning: "Warning: No CUDA application was profiled, exiting". I do not know why this is happening.
I used the Redhat 6.5 OS and CUDA 7.5 on K20M GPU card.
Thanks for your kindly response.

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