عنوان

Multi-GPU Graph Analytics

شماره

LA39r145g1

عنوان اصلي

Multi-GPU Graph Analytics

نام عام مواد

[Article]

نام نخستين پديدآور

Pan, Yuechao; Wang, Yangzihao; Wu, Yuduo; Yang, Carl; Owens, John D.

متن يادداشت

We present a single-node, multi-GPU programmable graph processing library that allows programmers to easily extend single-GPU graph algorithms to achieve scalable performance on large graphs with billions of edges. Directly using the single-GPU implementations, our design only requires programmers to specify a few algorithm-dependent concerns, hiding most multi-GPU related implementation details. We analyze the theoretical and practical limits to scalability in the context of varying graph primitives and datasets. We describe several optimizations, such as direction optimizing traversal, and a just-enough memory allocation scheme, for better performance and smaller memory consumption. Compared to previous work, we achieve best-of-class performance across operations and datasets, including excellent strong and weak scalability on most primitives as we increase the number of GPUs in the system.

تاريخ نشر

2017

عنوان

UC Davis

نام الکترونيکي

نوع ماده

[Article]

کد کاربرگه

275578

سطح دسترسي

a

تكميل شده

Y