Developing an Architecture-independent Graph Framework for Modern Vector Processors and NVIDIA GPUs

Abstract

This paper describes the first-in-the-world attempt to develop an architectural-independent graph framework named VGL, designed for different modern architectures with high-bandwidth memory. Currently VGL supports two classes of architectures: NEC SX-Aurora TSUBASA vector processors and NVIDIA GPUs. However, VGL can be easily extended to other architectures due to its flexible software structure. VGL is designed to provide users with the possibility of selecting the most suitable architecture for solving a specific graph problem on a given input data, which, in return, allows to significantly outperform existing frameworks and libraries, developed for modern multicore CPUs and NVIDIA GPUs. Since VGL uses an identical set of computational and data abstractions for all architectures, its users can easily port graph algorithms between different target architectures without any source code modifications. Additionally, in this paper we show how graph algorithms should be implemented and optimised for NVIDIA GPU and NEC SX-Aurora TSUBASA architectures, demonstrating that both architectures have multiple similar properties and hardware features.