首页> 外文期刊>IEEE Transactions on Computers >Architecture scalability of parallel vector computers with a shared memory
【24h】

Architecture scalability of parallel vector computers with a shared memory

机译:具有共享内存的并行向量计算机的体系结构可伸缩性

获取原文
获取原文并翻译 | 示例

摘要

Based on a model of a parallel vector computer with a shared memory, its scalability properties are derived. The processor-memory interconnection network is assumed to be composed of crossbar switches of size b/spl times/b. This paper analyzes sustainable peak performance under optimal conditions, i.e., no memory bank conflicts, sufficient processor-memory bank pathways, and no interconnection network conflicts. It will be shown that, with fully vectorizable algorithms and no communication overhead, the sustainable peak performance does not scale up linearly with the number of processors p. If the interconnection network is unbuffered, the number of memory banks must increase at least with O(p log/sub b/ p) to sustain peak performance. If the network is buffered, this bottleneck can be alleviated; however, the half performance vector length still increases with O(log/sub b/ p). The paper confirms the validity of the model by examining the performance behavior of the LINPACK benchmark.
机译:基于具有共享内存的并行向量计算机的模型,得出其可伸缩性属性。假定处理器-内存互连网络由大小为b / spl times / b的纵横开关组成。本文分析了最佳条件下的可持续峰值性能,即没有内存条冲突,足够的处理器-内存条路径以及没有互连网络冲突的情况。将显示出,利用完全可矢量化的算法并且没有通信开销,可持续的峰值性能不会随处理器数量p线性增加。如果互连网络没有缓冲,则存储库的数量必须至少增加O(p log / sub b / p),才能保持最佳性能。如果网络是缓冲的,则可以缓解此瓶颈。但是,半性能矢量的长度仍然随O(log / sub b / p)的增加而增加。本文通过检查LINPACK基准测试的性能行为来确认模型的有效性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号