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GTC ON-DEMAND

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Abstract:
We will present the latest development in the Gunrock library, mainly in programability and scalability, in the talk. Gunrock (http://gunrock.github.io/) is a high performance GPU graph processing library for large graphs. We revise the APIs of the library, aiming to make programming with Gunrock easier, and also to support more graph formats (including goai open format for data analytics) and operations. We also develop some new techniques to scale graph traversal on more GPUs, and can process graphs with several hundreds of billion edges around half a second on more than 100 Tesla P100 GPUs.
We will present the latest development in the Gunrock library, mainly in programability and scalability, in the talk. Gunrock (http://gunrock.github.io/) is a high performance GPU graph processing library for large graphs. We revise the APIs of the library, aiming to make programming with Gunrock easier, and also to support more graph formats (including goai open format for data analytics) and operations. We also develop some new techniques to scale graph traversal on more GPUs, and can process graphs with several hundreds of billion edges around half a second on more than 100 Tesla P100 GPUs.  Back
 
Topics:
HPC and Supercomputing, Tools & Libraries
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8594
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Abstract:
We present Gunrock, a multi-GPU graph processing library, that enables easy graph algorithm implementation and extension onto multiple GPUs for scalable performance on large graphs with billions of edges. Attendees can learn how to 1) solve large-scale graph problems with high-performance GPU computing primitives and optimization strategies, using our high-level data-centric abstraction that focuses on vertex or edge frontier operations, and 2) utilize multi-GPU computing power by just a few algorithm-dependent blocks, using our multi-GPU framework that handles most multi-GPU implementation details and memory allocation. We will also share experience on the library's design and implementation that helps it achieve the best performance among programmable GPU graph libraries.
We present Gunrock, a multi-GPU graph processing library, that enables easy graph algorithm implementation and extension onto multiple GPUs for scalable performance on large graphs with billions of edges. Attendees can learn how to 1) solve large-scale graph problems with high-performance GPU computing primitives and optimization strategies, using our high-level data-centric abstraction that focuses on vertex or edge frontier operations, and 2) utilize multi-GPU computing power by just a few algorithm-dependent blocks, using our multi-GPU framework that handles most multi-GPU implementation details and memory allocation. We will also share experience on the library's design and implementation that helps it achieve the best performance among programmable GPU graph libraries.  Back
 
Topics:
Big Data Analytics, Tools & Libraries, HPC and Supercomputing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2016
Session ID:
S6374
Streaming:
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