High-speed graph analytics with the galois system
High-speed graph analytics with the galois system
复制标题
使用伽罗瓦系统进行高速图形分析
DOI：
10.1145/2567634.2567648
复制
发表时间：
2014
期刊：
影响因子：
--
通讯作者：
K. Pingali
中科院分区：
文献类型：
--
作者：
K. Pingali
UT Austin的Galois项目开发了一个高级编程模型和一个轻量级并行执行引擎，使应用程序编写人员能够在高层次抽象上编写和调优复杂的并行应用程序。
The Galois project at UT Austin has developed a high-level programming model and a lightweight parallel execution engine that enable application writers to write and tune complex parallel applications at a high level of abstraction.
This talk describes the experiences of our group and of our industrial collaborators in using the Galois system for "big data" graph analytics. We show that (i) the rich programming model of Galois enables application programmers to write sophisticated graph analytics algorithms that cannot be expressed directly in current graph analytics DSLs, (ii) even when the same algorithm is used, the lightweight execution engine permits Galois programs to run much faster than programs in other DSLs, and (iii) the APIs of most current graph analytics DSLs can be implemented on top of the Galois system in a few hundred lines of code.