一种在复杂环境中支持容错的高性能规约框架

规约是并行应用最常用的集合通信操作之一，现存规约算法存在2方面主要问题。第一，不适应复杂环境，当计算环境出现干扰时，规约效率显著降低。第二，不支持容错，当节点发生故障时，规约被迫中断。针对上述问题，提出一种基于任务并行的高性能分布式规约框架。首先，该框架将规约拆分为一系列独立的计算任务，使用任务调度器以保证就绪任务被优先调度到具有较高性能的节点上执行，从而有效避免了慢节点对整体性能的影响。其次，该框架基于规约数据的可靠性存储和故障侦听机制，以任务为粒度，可在应用不退出的前提下实现故障恢复。在复杂环境中的实验结果表明，分布式规约框架具有高可靠性，与现有规约算法相比，规约性能最高提升了2.2倍，并发规约性能最高提升了4倍。

A fault tolerant high-performance reduction framework in complex environment

Reduction is one of the most commonly used collective communication operations for parallel applications. There are two problems for the existing reduction algorithms:First, they cannot adapt to complex environment. When interferences appear in computing environment, the efficiency of reduction degrades significantly. Second, they are not fault tolerant. The reduction operation is interrupted when a node failure occurs. To solve these problems, this paper proposes a task-based parallel high-performance distributed reduction framework. Firstly, each reduction operation is divided into a series of independent computing tasks. The task scheduler is adopted to guarantee that ready tasks will take precedence in execution and each task will be scheduled to the computing node with better performance. Thus, the side effect of slow nodes on the whole efficiency can be reduced. Secondly, based on the reliability storage for reduction data and fault detecting mechanism, fault tolerance can be implemented in tasks without stopping the application. The experimental results in complex environment show that the distributed reduction framework promises high availability and, compared with the existing reduction algorithm, the reduction performance and concurrent reduction performance of distributed reduction framework are improved by 2.2 times and 4 times, respectively.