【摘要】 随着高性能计算需求的日益增长,多核处理器在高性能计算中间得到了广泛的普及.为了保证高性能计算机系统的效率,需要保持计算和通信的平衡性,多核的广泛使用对通信系统的效率提出了更高的要求.集合通信作为通信系统中的重要组成部分,研究多核环境下的高效集合通信具有十分重要的意义.文中首先研究了多核对集合通信性能的影响,并根据多核处理器共享Cache以及内存竞争的特点,提出了层次化算法、限制并发、NUMA感知的优化方法和Cache友好的优化算法,并分别在MPI_Barrier、MPI_Bcast和MPI_Alltoall中进行了验证.实验结果表明优化方法能够有效地利用多核结构特点,降低竞争带来的影响,提高了多核环境下集合通信的性能和可扩展性.更多还原

【Abstract】 With the rapid increase in HPC computing requirement,the multicore is widely deployed in HPC systems.To keep the efficiency of application in large scale systems,it is very important keep up the balance of communication to computation,thus multicore brings more requirement for communication systems.As collective communication is an important part in communication systems and is critical for the whole systems,thus it is important to research on the impacts of multicore environment on collective performance.This paper first analyzes how multicore impacts on collective communication.It is found out that multicore SMP clusters brings two conflict impacts,it not only has faster intra-socket communication path which can speed up the performance of collective communications,but also it brings memory/cache contention which might degrade the communication performance.Based on these aspects,this paper proposes multicore-aware collecitves optimization techniques,which includes:hierarchy-aware algorithms,limited-concurrency,NUMA-aware algorithms and cache-friendly optimization.These optimization methods are implemented in MPI_Barrier,MPI_Bcast and MPI_Alltoall.Experiments show that the proposed algorithms increase the performance and scalability of collective communication.更多还原