There is the significant interest nowadays in developing the frameworks of parallelizing the processing for the large graphs such as social networks, Web graphs, etc. Most parallel graph processing frameworks employ iterative processing model. However, by benchmarking the state-of-art GPU-based graph processing frameworks, we observed that the performance of iterative traversing-based graph algorithms (such as Bread First Search, Single Source Shortest Path and so on) on GPU is limited by the frequent data exchange between host and GPU. In order to tackle the problem, we develop a GPU-based graph framework called WolfPath to accelerate the processing of iterative traversing-based graph processing algorithms. In WolfPath, the iterative proce...
Graph-related applications have experienced significant growth in academia and industry, driven by t...
For large-scale graph analytics on the GPU, the irregularity of data access and control flow, and th...
In this thesis we investigate the relation between the structure of input graphs and the performance...
There is the significant interest nowadays in developing the frameworks for parallelizing the proces...
Graphs are de facto data structures for many applications, and efficient graph processing is a must ...
Abstract—Graphs are common data structures for many applications, and efficient graph processing is ...
Modern Graphics Processing Units (GPUs) provide high computation power at low costs and have been de...
We present a single-node, multi-GPU programmable graph processing library that allows programmers to...
The all-pairs shortest-path problem is an intricate part in numerous practical applications. We desc...
This chapter introduces the topic of graph algorithms on GPUs. It starts by presenting and comparing...
Multi-core and GPU-based systems offer unprecedented computational power. They are, however, challen...
This thesis proposes a reconfigurable computing approach for supporting parallel processing in large...
Abstract. Large graphs involving millions of vertices are common in many prac-tical applications and...
For large-scale graph analytics on the GPU, the irregularity of dataaccess/control flow and the comp...
There is growing interest in studying large scale graphs having millions of vertices and billions of...
Graph-related applications have experienced significant growth in academia and industry, driven by t...
For large-scale graph analytics on the GPU, the irregularity of data access and control flow, and th...
In this thesis we investigate the relation between the structure of input graphs and the performance...
There is the significant interest nowadays in developing the frameworks for parallelizing the proces...
Graphs are de facto data structures for many applications, and efficient graph processing is a must ...
Abstract—Graphs are common data structures for many applications, and efficient graph processing is ...
Modern Graphics Processing Units (GPUs) provide high computation power at low costs and have been de...
We present a single-node, multi-GPU programmable graph processing library that allows programmers to...
The all-pairs shortest-path problem is an intricate part in numerous practical applications. We desc...
This chapter introduces the topic of graph algorithms on GPUs. It starts by presenting and comparing...
Multi-core and GPU-based systems offer unprecedented computational power. They are, however, challen...
This thesis proposes a reconfigurable computing approach for supporting parallel processing in large...
Abstract. Large graphs involving millions of vertices are common in many prac-tical applications and...
For large-scale graph analytics on the GPU, the irregularity of dataaccess/control flow and the comp...
There is growing interest in studying large scale graphs having millions of vertices and billions of...
Graph-related applications have experienced significant growth in academia and industry, driven by t...
For large-scale graph analytics on the GPU, the irregularity of data access and control flow, and th...
In this thesis we investigate the relation between the structure of input graphs and the performance...