Philippe Laurens, Michigan State University, for USATLAS. Atlas Great Lakes Tier 2 collocated at MSU and the University of Michigan

Transcription

1 Philippe Laurens, Michigan State University, for USATLAS Atlas Great Lakes Tier 2 collocated at MSU and the University of Michigan ESCC/Internet2 Joint Techs July 2011

2 Content Introduction LHC, ATLAS, USATLAS Data Deluge Hierarchical Tiers of Computing Robust Network is key Network Infrastructure monitoring Distributed perfsonar nodes at USATLAS T1 & T2s Centralized Dashboard Examples of diagnostics Prospects after our pilot deployment 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 2

3 Large Hadron Collider at the European Center for Nuclear Research 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 3

4 Large Hadron Collider 2x circulating beams of protons guided by superconducting magnets cooled down to -271 o C 27 km (~17 miles) circumference Underground: m ATLAS is one of the two primary experiments at LHC 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 4

5 ATLAS Particle Physics Experiment to explore the fundamental forces and the structure of matter in our universe One quark or gluon from each proton collide at the center of the ATLAS detector and produce other particles, which themselves decay or further collide with material in the detector giving jets and showers of secondary particles A Russian doll set of sub-detector components surround the collision point (altogether 7,000 tons, 25m high) Particle paths and energies are measured using millions of channels of data acquisition repeat 25ns later, up to 30 million times/sec 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 5

6 The ATLAS Collaboration A Torroidal LHC ApparatuS The collaboration 38 Countries ~170 Institutes/Universities ~3000 physicists Including ~1000 students One of the largest efforts in physical sciences 2011: Started 2 year run of data taking at 3.5 TeV per beam (7 TeV total) Already produced papers and new physics results from 2010 low luminosity data, more results coming at this summer conferences 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 6

7 Data Deluge Proton beams cross at 40 MHz but only ~30MHz of collisions Trigger System: multi-level online event selection, down to < 1kHz of recorded events Huge Data Volume > 300 MB/s Huge Computer Storage and Analysis resources needed for simulation (Monte Carlo) and event reconstruction Worldwide Grid 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 7

8 ATLAS Tiered Computing Model To address these computing needs (Storage and CPU) ATLAS has chosen a Tiered Computing Model: Tier 0 : at CERN Tier 1 : ~10 national centers Tier 2 : Regional centers Tier 3 : Institutional/group centers (Tier 4 : Desktops) Raw data is duplicated among Tier-0 and Tier-1s for backup Reconstructed data and simulation data are available to all Tier-1s and Tier-2s Tier-2s primarily handle Simulation (MC production) & Analysis Tasks Implicit in this distributed model and central to its success are: High-performance, ubiquitous and robust networks Grid middleware to securely find, prioritize and manage resources User jobs need to find the data they need 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 8

9 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 9

10 USATLAS sites US Tier 1 BNL Brookhaven National Lab (Long Island, NY) Five US Tier 2 centers AGLT2 Atlas Great Lakes Tier 2 MSU Michigan State University UM University of Michigan MWT2 Mid-West Tier 2 IU Indiana University Purdue University Indianapolis UC University of Chicago NET2 North-East Tier 2 BU Boston University HU Harvard SWT2 South-West Tier 2 OU University of Oklahoma UTA University of Texas at Arlington WT2 West Tier 2 SLAC SLAC National Accelerator Laboratory 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 10

11 T2 Site example: AGLT2 Split between MSU and UM 10Gb network between MSU and UM and between each site and the rest of the world ~20 file server nodes > 1.9 PB of data ~ 375 compute nodes > 4,500 job slots 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 11

12 Robust Network is Key Desire to instrument the network connections between US Tier 1 and all US Tier 2 sites in one uniform way Primary motives Aid in problem diagnosis and location identification Archive of standard regular measurements over time USATLAS Adopted perfsonar-ps Implemented end points in each facility Define mesh of connection tests between all facilities 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 12

13 perfsonar-ps Deployment at USATLAS Deploy same inexpensive hardware at all sites ~$600 per KOI 1U system, 1Gb NIC Used same linux based ps perfsonar Toolkit LiveCD now most sites use the new net-install, rpm distribution Dedicate one node for throughput and one node for latency at each site Throughput tests are resource intensive and tend to bias latency test results Define a common set of test Mesh of Throughput tests to/from all T1/T2 perfsonar nodes Mesh of Latency tests to/from all T1/T2 perfsonar nodes Now augmented with summary via Dashboard (more later) 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 13

14 perfsonar-ps Project A deployable measurement infrastructure perfsonar-ps is comprised of several members: Esnet, Fermilab, Georgia Tech, Indiana University, Internet2, SLAC, The University of Delaware perfsonar-ps products are written in the perl programming language and are available for installation via source or RPM (Red Hat Compatible) packages perfsonar-ps is also a major component of the ps Performance Toolkit A bootable Linux CD containing measurement tools and GUI ready to be configured for desired tests. 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 14

15 perfsonar-ps Tools Web based GUIs for admin to configure and for user to display measurements After initial setup of local disk, IP, NTP Nodes may be declared being part of some communities (e.g. LHC or USATLAS) to help identification in a directory lookup service Two main test types Throughput tests (bwctl) non-concurrent Two-way Ping Latency tests (PingER) and One-Way Latency tests with packet loss accounting (owamp), can run concurrently Tests are scheduled and a Measurement Archive manages results Also available traceroute and ping (i.e. reverse route from remote PS host) Network Diagnostic Tools (NDT,NPAD) on demand Cacti pre-installed 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 15

16 perfsonar: Web GUI 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 16

17 perfsonar: Throughput Tests web page 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 17

18 perfsonar: Throughput graphs 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 18

19 perfsonar: Latency Tests web page 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 19

20 perfsonar: Latency Graph Graph for current time shown here, but one can also retrieve older time slices from archive, or zoom in on a particular time within such graph. 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 20

21 perfsonar: reverse traceroute 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 21

22 Centralized Monitoring of our Distributed Monitoring: the BNL Dashboard 9 separate T1/T2 sites monitored, i.e. 18 perfsonar nodes Total of 108 critical services, 72 throughput tests, 72 one-way latency tests Need a centralized Dashboard to keep track of the overall mesh Developed by BNL (Tom Wlodek) for USATLAS (and now other clouds) First within Nagios (but complex and hard to access) Now rewritten as a standalone project accessible by all (and portable) Use probes to monitor proper operation of critical services on each node Alert s sent to site admin on failing services Use probes to retrieve the latest test results on pre-defined mesh of measurements (throughput & Latency) Both measurements about link A B measured by A & B Thresholds on results for label (OK, CRITICAL, etc) and color code History and time plots of service status and mesh of measurements Present a compact overview of all USATLAS inter-site network connections (and perfsonar nodes health) 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 22

23 Dashboard: in Nagios first 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 23

24 Dashboard: now standalone version 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 24

25 Dashboard: Primitive Services 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 25

26 Dashboard: Service History 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 26

27 Dashboard: Throughput Measurement plot 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 27

28 Dashboard: Latency Measurement plot 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 28

29 Dashboard: other ATLAS clouds 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 29

30 Diagnostics Throughput: Notice and localize problems to help debug network, also help differentiate server problems from path problems Latency: Notice route changes, asymmetric routes Watch for excessive Packet Loss Optionally: Install additional perfsonar nodes inside local network and/or at periphery Characterize local performance and internal packet loss Separate WAN performance from LAN performance Daily Dashboard check of own site, and peers 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 30

31 Example of diagnostics Asymmetric throughput between peer sites IU & AGLT2 was documented, then resolved 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 31

32 Other example of diagnostics Most recent case, right after routing upgrade work, quickly noticed small 0.7ms latency increase Traceroute showed an unintended minor route change (packets to MSU were going through UM) router config quickly fixed 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 32

33 Prospects after our pilot deployment perfsonar-ps Has proven extremely useful for USATLAS to-date! perfsonar-ps will be recommended for US T3 sites perfsonar is being deployed in other ATLAS clouds Italy has started, Canada also in process BNL Dashboard already monitoring IT cloud (at least for now) Dashboard code will be packaged & distributed perfsonar is being deployed at LHC T1 sites LHCOPN already plans to deploy it LHCONE is considering perfsonar-ps for their monitoring Will continue usage at USATLAS T1&T2s Expand to Inter-cloud monitoring, between T2s of different clouds Add 10Gb throughput tests perfsonar is open source with new release ~twice/year e.g. work underway to use single multi-core node for both throughput and latency The more test points along the paths the better Integrating information from backbone, routing points Allows a divide-and-conquer approach to problem isolation 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 33

34 Thank you perfsonar Jason Zurawski USATLAS perfsonar Dashboard Nagios needs BNL login Standalone Dashboard Tom Wlodek AGLT2 Our Compute Summary page My 7/12/2011 Philippe Laurens, MSU AGLT2 USATLAS 34