Creating Clusters – Practical Coniderations创建集群–实际考虑.pptVIP

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2018-06-19 发布于福建
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Creating Clusters – Practical Coniderations创建集群–实际考虑.ppt

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Creating Clusters – Practical Coniderations创建集群–实际考虑

Designing a Cluster for a Small Research Group Jim Phillips, Tim Skirvin, John Stone Theoretical and Computational Biophysics Group Outline Why and why not clusters? Consider your… Users Application Budget Environment Hardware System Software Case study: local NAMD clusters Why Clusters? Cheap alternative to “big iron” Local development platform for “big iron” code Built to task (buy only what you need) Built from COTS components Runs COTS software (Linux/MPI) Lower yearly maintenance costs Re-deploy as desktops or “throw away” Why Not Clusters? Non-parallelizable or tightly coupled application Cost of porting large existing codebase too high No source code for application No local expertise (don’t know Unix) No vendor hand holding Massive I/O or memory requirements Know Your Users Who are you building the cluster for? Yourself and two grad students? Yourself and twenty grad students? Your entire department or university? Are they clueless, competitive, or malicious? How will you to allocate resources among them? Will they expect an existing infrastructure? How well will they tolerate system downtimes? Your Users’ Goals Do you want increased throughput? Large number of queued serial jobs. Standard applications, no changes needed. Or decreased turnaround time? Small number of highly parallel jobs. Parallelized applications, changes required. Your Application The best benchmark for making decisions is your application running your dataset. Designing a cluster is about trade-offs. Your application determines your choices. No supercomputer runs everything well either. Never buy hardware until the application is parallelized, ported, tested, and debugged. Your Application:Serial Performance How much memory do you need? Have you tried profiling and tuning? What does the program spend time doing? Floating point or integer and logic operations? Using data in cache or from main memory? Many or few operations per memory access? Run benchmarks on many platforms. Your Applica