1. 1 Evolving ATLAS Computing Model and Requirements Michael Ernst, BNL With slides from Borut Kersevan and Karsten Koeneke U.S. ATLAS Distributed Facilities Meeting UCSC November 13, 2012

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3. 3 ATLAS Computing Mar-Aug 2012

4. 4 Computing Resource Usage in 2012, 2013-2015

5. 5 Current Resource Usage

6. 6 Resource Usage at Tier-2s

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8. 8 Contributions by Country (Production and Analysis) Includes beyond pledge resources

9. 9 Contribution by Job Type Production Analysis US: 22% of available CPU used for Analysis 77% of Analysis done At Tier-2s T1 T2

10. 10 Contribution to Simulation (Aug-Oct) (3843) (1867)(1762) (1067) (896) Avg # of fully Utilized cores

11. 11 Contribution to Pile (Aug-Oct) (1818) (374) (1128) (526) Avg # of fully Utilized cores

12. 12 Contribution to Analysis (Aug-Oct) (342) (1024) (590) (720) (395) Avg # of fully Utilized cores

13. 13 Contribution to Reco (Aug-Oct) (342) (1024) (590) (720) (395) Avg # of fully Utilized cores (512) (108) (122) (112)

14. 14 Balancing Resources across the Tier-1 and Tier-2s for cost/benefit optimization E. Lancon (ICB Chair) at the Oct ICB Meeting

15. 15 Resource Development

16. 16 Evolution and Prediction of price/performance of CPU Servers B. Panzer/CERN In the US we have observed prices going up slightly between 2011 and 2012. Moore’s law hasn’t helped to improve price/performance ratio – Future?

17. 17 Multi-core vs. Many-core  A typical modern compute server has 12-16 cores  Number of cores in commodity machines grows arithmetically  Number of cores in the enterprise space still grows geometrically  Number of cores in our datacenters grows between the two, expected to slow down in the long run  Many-core is not multi-core  Observing memory hierarchy issues  Cache coherency  NUMA  Memory b/w or I/O paths may be constraining  Multiprocess is a convenient model, but it’s neither sustainable nor scalable

18. 18 Evolution and Prediction of Price for Disk Space B. Panzer/CERN Disk prices are ~1.5x compared to 2010 predictions

19. 19 Medium-term hardware trends  Pricing follows market pressure, not technology  I/O, disk and memory not progressing at the same rate as compute power  Bulk of improvements in x86 still comes from Moore’s Law  Enterprise and HPC-targeted developments, where cost-effective, trickle down to our datacenter environment  Heterogeneous architectures  Cross-platform, cross socket, hybrid CPUs, accelerators, throughput vs. classic computing

20. 20 Non-Intel Hardware  GPUs  NVIDIA working hard but process technology lacking  P2P communication improved  Software getting better  MIC: Tesla might be no longer competitive  ARM  Slow penetration of the server space  64-bit instruction set defined (you can buy today 32 bit CPUs)  Software improvements make ARM look like a viable option  AMD  Lagging behind, recent experiments not compelling  FPGA  Still too far off for mainstream accelerators, software issues  Upcoming: low power/micro servers 192 cores, 1 GB/core $35k

21. 21 First Projections for 2015 - 2016

22. 22 Computing Requirements vs LHC Bunch Spacing

23. 23 Computing Requirements vs LHC Bunch Spacing S. McMahon

24. 24 Resource requests rising after LS1

25. 25 Computing Model Changes

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27. 27 Offline Core Analysis Simulation

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34. 34 Summary  The Facilities have reliably delivered in all areas according to our obligations, and in may areas beyond  The overall system, comprising facility hardware and services, and the ATLAS software needs to evolve to improve the efficiency and to cope with sharply growing requirements after LS1  Resources were used more effectively with “Life w/o “ESDs”, PD2P, reduced # of DS replicas but the potential for more – significant- is shrinking  A combined effort, driven by analysis and software experts, is needed to get ATLAS Computing prepared for the challenges ahead  Convinced the LHC machine will deliver …  LS1 is around the corner but my impression from the last SW&C week is, there is not much activity in the SW area to address issues