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|Title:||An overview of Medusa : simplified graph processing on GPUS||Authors:||Zhong, Jianlong
|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.||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
|DOI:||10.1145/2145816.2145855||Fulltext Permission:||none||Fulltext Availability:||No Fulltext|
|Appears in Collections:||SCSE Conference Papers|
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