Diamond Networks/Computing. Nick Rees January 2011

Transcription

1 Diamond Networks/Computing Nick Rees January 2011

2 2008 computing requirements Diamond originally had no provision for central science computing. Started to develop in , with a major development in 2008: Resilient high density computer room. Compute cluster with minimum 1500 SPECfp_rate2006 total. Resilient network with dual 10 Gbit core. 200 Tbytes storage with 20 Mbytes/sec scalable aggregated throughput and 8000 metadata operations/sec.

3 Overall a success Computer room Has up to 320 kw redundant power, (A and B) from two separate sub-stations. Power from A is UPS and generator backed up. Has up to 320 kw cooling water. Primary cooling is from site chilled water, 220 kw standby chiller in case of problems. Ran commissioning tests at 160 kw power load satisfactorily. Standby system has proved its worth a number of times.

4 Layout Cable Tray Water pipes

5 Testing with heat loads

6 Temperature rise on flow fail (0.5C/sec)

7 Now

8 This was a success. Easy to specify Compute cluster One supplier validated system against specification. They were the successful supplier A few teething problems Network driver had problems being both IPMI and normal interface at same time Sometimes need multiple restarts to get network I/F configure correctly. Problem fixed with updated Ethernet firmware and new switch hardware.

9 Computing solution 1U twin motherboard systems Each 1U motherboard is: Supermicro X7DWT Intel 5400 (Seaburg) Chipset Dual Intel Xeon E5420 (Quad Core, 2.5GHz) Processors 16GB DDR2-667 ECC RAM Installed as 4x4GB FBDIMMs 160GB SATA Hard Disk 1x16 PCI-Express slot (for GPU extension) Total 20 systems, 16 cores/system, 320 cores.

10 Current compute clusters Now have multiple compute clusters: Original IBM MX cluster New Supermicro cluster, 320 cores Accelerator Physics cluster, 240 Supermicro cores, but with InfiniBand interconnect. Nvidia Tesla cluster with Supermicro frontends for tomography. Feb 2010 Diamond Control System

11 Network Overall, another success Two core switches (from different vendors), in separate computer rooms Each beamline connected to both switches so either 2GBit or 20 GBit peak bandwidth available halved if one core switch fails Traffic routed by vendor-independent protocols OSPF, ECMP and LACP Cluster switch connected with 2 x 10 GBit to each switch. Storage system connected directly into core. Rack-top switches in both computer rooms also connected to both cores.

12 Network Layout

13 Network Layout Phase 1 Beamlines Phase 2 Beamlines Beamline Switch 1 Gbit/s Beamline Switch 1 Gbit/s 2 Gbit/s Disks 0.5 Gbit/s 10 Gbit/s 10 Gbit/s Central 40 Gbit/s Switch 80 Gbit/s Cluster Switch Disks 40x1 Gbit/s Cluster 60 Gbit/s Feb 2010 Diamond Control System

14 Network issues At high data rates packets get lost Standard TCP back off time is 200 ms, which is a lot of data at 10 Gbit/s See the problem mostly when 10 Gbit servers write to 1 Gbit clients. Other sites see similar issues use your favorite search engine to look up Data Center Ethernet or Data Center Bridging

15 Storage Requirements 200TBytes usable disk space 20 Mbytes/sec/Tbyte scalable aggregated throughput. 4 GBytes/sec aggregated throughput for 200 Tbytes. 100 MBytes/sec transfer rate for individual 1 Gbit clients 400 MBytes/sec for individual 10 Gbit clients 8000 metadata operations/sec Highly resilient Support for Linux clients (RHEL4U6 and RHEL5 or later) POSIX with extended attributes and ACLs Groups for file access control based (> 256 groups/user) Ethernet Clients. Extendable by at least 200TB for future growth.

16 Storage - solution Based on Data Direct Networks S2A9900 system Up to 5.7 GB/s throughput Fault-tolerant architecture Runs Lustre file system Open source file system acquired by Sun in 2008, and now part of Oracle Most popular file system in top 500 supercomputers

17 In initial tests: Storage - problems Sometimes got near 4 Gbytes/sec writing Only ever got about 3 Gbytes/sec reading Only got 8000 metadata operations/sec for the specific case of sequential creates of zero length files. Other metadata operations were slower (~2000/sec). In reality with real users: Primarily seem to be limited by metadata rates 8000 operations/sec specification based on 40 clients creating 200 files/sec. In practice a detector takes 3-5 metadata operations to create a file. The total rates also conceal that the latency for some individual files can be up to 15 seconds under load. This may now be fixed...

18 Storage status: Data sizes by beamline

19 Data growth by beamline 3,5E+10 b16 3E+10 2,5E+10 2E+10 1,5E+10 1E+10 5E /01/ /01/ /01/ /01/ /01/2011 b18 b22 b23 i02 i03 i04 i04-1 i06 i06-1 i07 i10 i11 i12 i15 i16 i18 i19 i20 i22 i24

20 Total data growth

21 Where to next? Data sizes , ,00 Total Size of DIam mond Data (TiB) 10000, ,00 100,00 10,00 Decreasing Exponential Model Best fit cubic Total Data Staff Data 1,00 0,10 janv. 07 janv. 09 janv. 11 janv. 13 janv. 15 janv. 17 janv. 19 janv. 21 janv. 23 Date

22 Where to next? - data rates ,00 Predicted rate of data produc ction at Diamond (TiB/year) , , ,00 100,00 10,00 1,00 Decreasing Exp. Rate Model Rate Best fit cubic Rate Actual Rate 0,10 janv. 07 janv. 09 janv. 11 janv. 13 janv. 15 janv. 17 janv. 19 janv. 21 janv. 23 Date

23 Where to next? Proposing to create a rolling programme for computing development based on Moore's Law and typical hardware lifetimes of 5 years Replace most hardware every 5 years Significant cluster and storage purchases every 2-3 years. A significant investment, but we must develop A significant investment, but we must develop computing proactively in parallel with beamline data rates, rather than reactively because of them.

24 Conclusions We have come from behind in computing but are gradually catching up. Probably one of the most challenging synchrotrons with a large proportion of MX and an ambitious tomography group. Must have long-term proactive approach to keep ahead of beamline requirements.