摘要
并行处理与并行计算机是当今计算机科学研究的热点之一,并行计算机以其卓越的性能日益受到世人的瞩目。其中,基于消息传递的并行计算机逐渐成为了超级计算机发展的主流,它包括两种机型:大规模并行处理机和机群。本文以基于消息传递的机群系统为原型,给出了机群机间通讯系统的性能评价模型,并详细地介绍了该系统的实现方案。
随着半导体工艺的日新月异,处理器越来越快,并行计算机的性能提高越来越依赖于相对较慢的通讯系统功能和效率的改善。一方面,通讯系统带宽和延时性能的提高,能直接加快消息传递的过程,使解题速度加快;另一方面,实现计算与通讯在时间上的重叠,能从宏观上隐藏通讯开销,从而使延时大大减小。通讯系统设计的好坏,直接关系到并行计算机的解题速度和解题规模。
本文讨论了机群机间通讯系统的数据链路构成,将其大致分为两种链路模型:单链路缓冲机制和基于Wormhole机制的二维Mesh网络。文中详细分析了它们的带宽、延时性能与数据流量和数据缓冲区的关系,给出了机群机间通讯系统的性能评价模型。
根据这样的性能评价模型,当数据流量比较小、Mesh网络负载比较轻时,机群机间通讯系统的延时与通讯距离近似无关;在数据流量比较大、Mesh网络负载比较重时,随着网络负载率的升高系统延时迅速增大。在稳定的数据流量下,系统带宽取决于最小的子链路带宽;在数据流量不稳定或网络出现阻塞时,缓冲机制将适时地发挥作用。同时,在考虑信道噪声的情况下,一定间隔的数据缓冲区将有可能使误码率降低。
机群机间通讯系统的关键设备—PMI的实现,是本文进
Parallel processing is one of the hottest topics of the computer science today. And of all kinds of parallel computers two ones are becoming the mainstream which take advantages of the message-passing technique. These two kinds of parallel computers are massively parallel processors(MPP) and clusters. This thesis gives a model to evaluate the performance of the inter-node communication subsystem of cluster and tells the details of its implementation.
With the fast development of micro-processors the performance of parallel computers are becoming more and more dependent on the functions and efficiency of their communication subsystems. On the one way the acceleration of communication subsystems can reduce the overhead and latency so as to make applications run faster, on the other hand overlapping of computation and communication can hide the communication latency so applications can see little of it.
This thesis analyses all the data links of cluster and classifies them as two types of channels: buffered single-link and wormhole Mesh. The models to evaluate their performance are given and then equations listed which tell the relations of bandwidth, latency, flow rate and buffer sizes.
Following these models we can see: when the rate of data flow is low or the load of Mesh is light the latency of such a communication subsystem seems approximately irrelevant to the communication distance; when the flow rate rises or the load of Mesh becomes heavier the latency rises much more rapidly. And with the stable data flow the bandwidth of communication subsystem keeps identical with the minimum one of all sublinks. When the flow fluctuate or the Mesh becomes blocked data buffers will work to sustain the bandwidth. At the same time if the noise of channels is considered the buffers which divide a long link into some shorter ones may make errors fewer.
The implementation of PMI which is one of the key devices of inter-node communication subsystem of cluster is the basis to
引文
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