Hp StorageWorks Scalable File Share User Manual download pdf (Page 71)

Figure A-6 Multi-Client Throughput Scaling

In general, Lustre scales quite well with additional OSS servers if the workload is evenly

distributed over the OSTs, and the load on the metadata server remains reasonable.

Neither the stripe size nor the I/O size had much effect on throughput when each client wrote

to or read from its own OST. Changing the stripe count for each file did have an effect as shown

in Figure A-7.

Figure A-7 Multi-Client Throughput and File Stripe Count

Here, 16 clients wrote or read 16 files of 16 GB each. The first bars on this chart represent the

same data as the points on the right side of the previous graph. In the five cases, the stripe count

of the file ranged from 1 to 16. Because the number of clients equaled the number of OSTs, this

count was also the number of clients that shared each OST.

Figure A-7 shows that write throughput can improve slightly with increased stripe count, up to

a point. However, read throughput is best when each stream has its own OST.

A.3 Throughput Scaling 71

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Hp StorageWorks Scalable File Share User Manual Page 71