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By Jean-Paul Tremblay

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Use More Independent Threads on the Same Node The first approach we will discuss harnesses several threads belonging to one program that can simultaneously access the same memory locations. Application threads can communicate through this shared memory with each other and avoid redundant copies of data. Shared memory is an efficient means of passing data between program threads. To connect multiple processors (each with multiple cores), the underlying system needs to have robust hardware to support arbitration and ordering of the memory requests.

The software stack needs to support message passing between the nodes, so that it becomes more sophisticated. Two dual-processor servers with two Intel Xeon Phi coprocessors each clustered together with InfiniBand interconnect are shown in Figure 2-16. Figure 2-16. Cluster of two nodes All of the most popular interconnects use the PCIe bus to connect to the processors in the system, and thus they inherit all the latency and bandwidth limitations specific to PCIe. On top of this, since both Ethernet and InfiniBand are designed to scale to a much larger number of communicating agents in the network (at least tens of thousands) than PCIe, their protocol overheads and cost of packet routing are significantly higher compared to the PCIe bus used inside the server.

For example, if each job takes a couple of minutes to run, but there are many jobs (up to tens of thousands have been observed in real life), the relative time taken by the job scheduler becomes very visible. Most job schedules offer special support for large number of smaller jobs with identical parameters via so-called job arrays. If your application is of that kind, please take some time to study how to make effective use of your cluster’s scheduling software. Summary This chapter briefly overviewed the main terms and concepts pertaining to the performance analysis and gave an overview of the modern high-performance computing platforms.

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