The st-connectivity problem (ST-CON) is a decision problem that asks, for vertices s and t in a graph, if t is reachable from s. Although originally defined for directed graphs, it can also be studied on undirected graphs and used as a building block for solving more complex tasks on large scale graphs. We present solutions to ST-CON based on a high performance Breadth First Search (BFS) executed on clusters of Graphics Processing Units (GPUs) using the Nvidia CUDA platform. To measure performances, we use the number of ST-CONs per second. We present the results for two different implementations that highlight the impact of atomic operations in CUDA.
The st-connectivity problem (ST-CON) is a decision problem that asks, for vertices s and t in a graph, if t is reachable from s. Although originally defined for directed graphs, it can also be studied on undirected graphs and used as a building block for solving more complex tasks on large scale graphs. We present solutions to ST-CON based on a high performance Breadth First Search (BFS) executed on clusters of Graphics Processing Units (GPUs) using the Nvidia CUDA platform. To measure performances, we use the number of ST-CONs per second. We present the results for two different implementations that highlight the impact of atomic operations in CUDA.
Solutions to the st-connectivity problem using a GPU-based distributed BFS / Bernaschi, Massimo; Carbone, Giancarlo; Mastrostefano, Enrico; Vella, Flavio. - In: JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING. - ISSN 0743-7315. - 76:(2015), pp. 145-153. [10.1016/j.jpdc.2014.09.013]
Solutions to the st-connectivity problem using a GPU-based distributed BFS
Flavio Vella
2015-01-01
Abstract
The st-connectivity problem (ST-CON) is a decision problem that asks, for vertices s and t in a graph, if t is reachable from s. Although originally defined for directed graphs, it can also be studied on undirected graphs and used as a building block for solving more complex tasks on large scale graphs. We present solutions to ST-CON based on a high performance Breadth First Search (BFS) executed on clusters of Graphics Processing Units (GPUs) using the Nvidia CUDA platform. To measure performances, we use the number of ST-CONs per second. We present the results for two different implementations that highlight the impact of atomic operations in CUDA.| File | Dimensione | Formato | |
|---|---|---|---|
|
1-s2.0-S0743731514001865-main.pdf
Solo gestori archivio
Tipologia:
Versione editoriale (Publisher’s layout)
Licenza:
Tutti i diritti riservati (All rights reserved)
Dimensione
1.32 MB
Formato
Adobe PDF
|
1.32 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione
