MPGraph is Massively Parallel Graph processing on GPUs.
- The MPGraph 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, MPGraph's CUDA kernels use multiple sophisticated strategies, such as vertex-degree-dependent dynamic parallelism granularity and frontier compaction.
- MPGraph is up to two orders of magnitude faster than parallel CPU implementations on up 24 CPU cores and has performance comparable to a state-of-the-art manually optimized GPU implementation.
- New algorithms can be implemented in a few hours that fully exploit the data-level parallelism of the GPU and offer throughput of up to 3 billion traversed edges per second on a single GPU.
This work was (partially) funded by the DARPA XDATA program under AFRL Contract #FA8750-13-C-0002.
- Graph Mining
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