Toward a software transactional memory for heterogeneous CPU–GPU processors
PARCO(2018)
摘要
The heterogeneous accelerated processing units (APUs) integrate a multi-core CPU and a GPU within the same chip. Modern APUs implement CPU–GPU platform atomics for simple data types. However, ensuring atomicity for complex data types is a task delegated to programmers. Transactional memory (TM) is an optimistic approach to achieve this goal. With TM, shared data can be accessed by multiple computing threads speculatively, but changes are only visible if a transaction ends with no conflict with others in its memory accesses. In this paper we present APUTM, a software TM designed for APU processors which focuses on minimizing the access to shared metadata. The main goal of APUTM is to understand the trade-offs of implementing a software TM on such platform. In our experiments, APUTM is able to outperform sequential execution of the applications. Additionally, we compare its adaptability to execute in one of the devices or in both simultaneously.
更多查看译文
关键词
Transactional memory,APU processors,Parallel programming,Data sharing
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络