Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/98782
Title: An overview of Medusa : simplified graph processing on GPUS
Authors: Zhong, Jianlong
He, Bingsheng
Issue Date: 2012
Source: Zhong, J., & He, B. (2012). An overview of Medusa: Simplified graph processing on GPUS. Proceedings of the 17th ACM SIGPLAN symposium on Principles and Practice of Parallel Programming - PPoPP '12, 283-284.
Conference: Symposium on Principles and Practice of Parallel Programming (17th : 2012)
Abstract: Graphs are the de facto data structures for many applications, and efficient graph processing is a must for the application performance. GPUs have an order of magnitude higher computational power and memory bandwidth compared to CPUs and have been adopted to accelerate several common graph algorithms. However, it is difficult to write correct and efficient GPU programs and even more difficult for graph processing due to the irregularities of graph structures. To address those difficulties, we propose a programming framework named Medusa to simplify graph processing on GPUs. Medusa offers a small set of APIs, based on which developers can define their application logics by writing sequential code without awareness of GPU architectures. The Medusa runtime system automatically executes the developer defined APIs in parallel on the GPU, with a series of graph-centric optimizations. This poster gives an overview of Medusa, and presents some preliminary results.
URI: https://hdl.handle.net/10356/98782
http://hdl.handle.net/10220/12653
DOI: 10.1145/2145816.2145855
Schools: School of Computer Engineering 
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Conference Papers

SCOPUSTM   
Citations 50

3
Updated on Mar 15, 2025

Page view(s) 50

656
Updated on Mar 17, 2025

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.