Campus Bridging in XSEDE, OSG, and Beyond

Transcription

1 Campus Bridging in XSEDE, OSG, and Beyond Dan Fraser, OSG Jim Ferguson, NICS Andrew Grimshaw, UVA Rich Knepper, IU David Lifka, Cornell Internet2 Spring Members Meeting, Arlington, VA

2 April 23, 2012 Overview Campus Bridging introduction Open Science Grid and software deployment XSEDE Campus Bridging Program Global Federated File System Campus Initiatives RedCloud POD at IU

3 April 23, 2012 Campus Bridging: Formation NSF Advisory Committee for CyberInfrastructure Community input at multiple workshops Surveys ACCI Campus Bridging Task Force Report

4 April 23, 2012 Campus Bridging: Concepts Making it easier for users to transition from their laptop to large-scale resources Gathering best practices to deploy resources in a way that makes them familiar to users Providing training and documentation that covers research computation at multiple scales

5 OSG Campus Bridging (Campus High Throughput Computing Infrastructures) Dan Fraser OSG Production Coordinator Campus Infrastructure Lead Internet2 Spring Members Meeting Arlington, VA Sept 24, 2012

6 The Open Science Grid The Open Science Grid (OSG) has focused on campuses from its inception. All OSG computing power comes from campuses. OSG has a footprint on over 100 campuses in the US and abroad.

7 OSG Campus Bridging Focus Focus on the Researcher ( or Artist) One step at a time

8 Simple interfaces are good

9 Engaging with the Campus Campuses each have their own culture Terminology Access patterns Security Operational styles Processes (autn, autz, monitoring, accounting, data management, ) The most fundamental issues are not technological in nature Campus Bridging = Cultural Bridging

10 Campus Bridging Direction Help the researcher use local resources Run on a local cluster (on campus) Run on several local clusters Use/share resources with a collaborator on another campus Access to the national cyberinfrastructure OSG (and also XSEDE) resources (BTW, OSG is also an XSEDE service provider) Submit Locally, Run Globally

11 OSG Campus Bridging Today Campus LSF PBS Local User Credential Condor Local Cluster Submit Host (Bosco) OSG Cloud External Campus (could also submit to XSEDE)

12 Summary OSG is focused on the researcher/artist Campus bridging = cultural bridging A single submit model (Bosco) can be useful OSG is exploring how best to collaborate with XSEDE on campus bridging

13 April 23, 2012 Introduction to XSEDE and its Campus Bridging Program Jim Ferguson, XSEDE TEOS team Education, Outreach & Training Director, NICS

14 Acknowledgements Craig Stewart, Rich Knepper, and Therese Miller of Indiana University, and others on the XSEDE campus bridging team. John Towns, NCSA, XSEDE PI 14

15 XD Solicitation/XD Program extreme Digital Resources for Science and Engineering (NSF ) High-Performance Computing and Storage Services aka Track 2 awardees High-Performance Remote Visualization and Data Analysis Services 2 awards; 5 years; $3M/year proposals due November 4, 2008 Integrating Services (5 years, $26M/year) Coordination and Management Service (CMS) 5 years; $12M/year Technology Audit and Insertion Service (TAIS) 5 years; $3M/year Advanced User Support Service (AUSS) 5 years; $8M/year Training, Education and Outreach Service (TEOS) 5 years, $3M/year

16 16 XSEDE Vision The extreme Science and Engineering Discovery Environment (XSEDE): enhances the productivity of scientists and engineers by providing them with new and innovative capabilities and thus facilitates scientific discovery while enabling transformational science/engineering and innovative educational programs

17 Science requires diverse digital capabilities XSEDE is a comprehensive, expertly managed and evolving set of advanced heterogeneous high-end digital services, integrated into a general-purpose infrastructure. XSEDE is about increased user productivity increased productivity leads to more science increased productivity is sometimes the difference between a feasible project and an impractical one 17

18 XSEDE s Distinguishing Characteristics - Governance World-class leadership partnership will be led by NCSA, NICS, PSC, TACC and SDSC CI centers with deep experience partners who strongly complement these CI centers with expertise in science, engineering, technology and education Balanced governance model strong central management provides rapid response to issues and opportunities delegation and decentralization of decision-making authority openness to genuine stakeholder participation stakeholder engagement, advisory committees improved professional project management practices formal risk management and change control 18

19 What is campus bridging? Term originated by Ed Seidel as he charged six task forces of the NSF Advisory Committee for Cyberinfrastructure. Considerable info and final ACCI Task force report, online at pti.iu.edu/campusbridging The Taskforce definition: Campus bridging is the seamlessly integrated use of cyberinfrastructure operated by a scientist or engineer with other cyberinfrastructure on the scientist s campus, at other campuses, and at the regional, national, and international levels as if they were proximate to the scientist... Catchy name, great ideas interest > our ability to implement yet Vision: Help XSEDE create the software, tools and training that will allow excellent interoperation between XSEDE infrastructure researchers local (campus) cyberinfrastructure; Enable excellent usability from the researcher s standpoint for a variety of modalities and types of computing: HPC, HTC, and data intensive computing Promote better use of local, regional and national CI resources 19

20 Campus Bridging Use Cases InCommon Authentication Economies of scale in training and usability Long term remote interactive graphic session Use of data resources from campus on XSEDE, or from XSEDE at a campus Support for distributed workflows spanning XSEDE and campus-based data, computational, and/or visualization resources Shared use of computational facilities mediated or facilitated by XSEDE Access to as a Service mediated or facilitated by XSEDE 20

21 Year 2 Strategic Plan Leveraging the XSEDE process of implementing new services via the systems engineering process (Architecture & Design => Software Development and Integration => Operations), begin deploying some new services that deliver campus bridging services Communicate effectively via Campus Champions, advocates for XSEDE now located at over 100 institutions. Develop relationship and terminology with OSG, as they have been bridging between institutions for several years. 21

22 Year 2 Strategic Plan Complete planned pilot projects GFFS Pilot Program CUNY PI: Paul Muzio KU PI: Thorbjorn Axelsson Miami PI: Joel Zysman TAMU PI: Guy Almes Begin delivering selected campus-bridging related tools GFFS Documentation ROCKS Rolls Communicate what is campus bridging 22

23 Example: More consistency in CI setups => economies of scale for all In reality, the four cluster admins depicted here being in agreement are all right. Experienced cluster admins all learned how to use what they learn when the tools were still developing, so the tool each sysadmin knows the best is the tool that lets that sysadmin do their work the best The only way to develop consistency is to provide installers that will make their work easier The XSEDE architecture group is developing installers for file management tools *A la Steven Colbert, the 4 out of 5 comment is not intended to be a factual statement 23

24 Your Comments, Please! Do we have the right direction? What is Campus Bridging to You? 24

25 25 Thank You!

26 April 23, 2012 Global Federated File System GFFS Andrew Grimshaw

27 Basic idea and canonical use cases Accessing the GFFS Attaching (provisioning) data to the GFFS Deployment 27

28 Basic idea: Map resources into a global directory structure Map global directory structure into local file system PDB NCBI EMBL Cluster 1 Cluster 2 APP 1 APP 2 Data SEQ_1 Cluster N Processing APP N Applications SEQ_1 Partner Institution APP 1 SEQ_2 Biology Research Institution SEQ_3 Biochemistry APP 2 Partner Institution

29 Canonical use cases Definitions Resource is {compute job data identity } Access means create, read, update, delete 1. Access center resource from campus 2. Access campus resource from center 3. Access campus resource from another campus Sharing file system or instrument data Sharing clusters 29

30 Basic idea and canonical use cases Accessing the GFFS Attaching (provisioning) data to the GFFS Deployment 30

31 Accessing the GFFS Via a file system mount Global directory structure mapped directly into the local operating system via FUSE mount XSEDE resources regardless of location can be accessed via the file system Files and directories can be accessed by programs and shell scripts as if they were local files Jobs can be started by copying job descriptions into directories One can see the jobs running or queued by doing an ls. One can cd into a running job and access the working directory where the job is running directly mkdir XSEDE nohup grid fuse mount local:xsede & 31

32 E.g., Access a job s running directory 32

33 Accessing the GFFS Via a command line tools, e.g., cp local:fred.txt /home/grimshaw/fred.txt rm /home/grimshaw/fred.txt 33

34 GUI Grid Client Typical folder based tool Tools to define, run, manage jobs Tools to manage grid queues Tools to export data Grid shell Shell has tab completion, history, help, scripting, etc. 34

35 GUI Grid Client: View Access Control To view access control information: Browse to and highlight resource, then select Security tab 35

36 Basic idea and canonical use cases Accessing the GFFS Attaching (provisioning) data to the GFFS Deployment 36

37 Exporting (mapping) data into the Grid Data clients Data clients Links directories and files from source location to GFFS directory and user-specified name Presents unified view of the data across platforms, locations, domains, etc. Sarah controls authorization policy. Sarah s department file server Sarah s instrument in the lab Sarah s TACC workspace Linux Windows TACC

38 Exporting/sharing data User selects Server that will perform the export Directory path on that server Path in GFFS to link it to grid export /containers/big-state-u/sarah-server /development/sources /home/sarah/dev Can also export Windows shares Directory structures via ssh (slow like sshfx) 38

39 Basic idea and canonical use cases Accessing the GFFS Attaching (provisioning) data to the GFFS Deployment 39

40 Deployment Sites that wish to export or share resources must run a Genesis II or UNICORE 6 container There will be an installer for the GFFS package for SPs, and a Campus Bridging package There is an installer for client side access There are training materials Used at TG 11 In the process of being turned into videos 40

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42 On-Demand Research Computing - Infrastructure as a Service - - Software as a Service -

43 Infrastructure as a Service (IaaS) Cloud Red Cloud provides on-demand: Computing Cycles: Virtual Servers in Cloud Instances Storage: Virtual Disks in Elastic Block Storage ( EBS ) Volumes Virtual Servers Cloud Instances Cloud Management Red Cloud Virtual Disks Elastic Block Storage (EBS) Virtual Server Users

44 Software as a Service (SaaS) Cloud with MATLAB NVIDIA Tesla M2070s GPU Chassis Dell C410x Compute Nodes Dell C6100 Web Server Head Node DDN Storage SQL Server MyProxy Server GridFTP Server

45 Motivation Research computing means many different things Scientific workflows have different requirements at each step Cloud is only part of the solution Connecting to and from other CI resources is important Nobody likes a bad surprise Transparency, no hidden costs Need a way to bound financial risk Economies of scale Sharing hardware and software where it makes sense Pay for what you need, when you need it Customized environments for various disciplines Collaboration tools Data storage & analysis tools Flexibility to support different computing models (e.g. Hadoop)

46 Provides Predictable, Reproducible, Reliable Performance We publish hardware specifications (CPU, RAM, network) and do not oversubscribe. Convenient Need system up and running yesterday. Need a big fast machine for only a few months, weeks or days. Need a small server to run continuously. No Hidden Costs No cost for network traffic in or out of the cloud. Fast Access to Your Data Fast data transfers via 10Gb Ethernet in or out of the cloud at no additional charge. Globus Online access Economies of scale IaaS: Infrastructure SaaS: Software Expert Help System, application, and programming consulting are available. Easy Budgeting with Subscriptions No billing surprises! IaaS is Amazon API Compatible Migrate when your requirements outgrow Red Cloud.

47 Some Use Cases to Consider Support for Scientific Workflows Pre & post-processing of data and results Data analysis Globus Online for fast reliable data transfer Collaboration Wiki hosting Customized data analysis & computational environments Web Portals Science Gateways Domain Specific Portals Hub Zero Event-Driven Science Education, Outreach & Training Pre-configured systems & software tools providing consistent training platform Common laboratory computing environment Bursting Additional software and hardware on demand

48 Subscription-based Recovery Model with MATLAB Cornell University $500/core year* Cornell University $750/core year Other Academic Institutions $750/core year Other Academic Institutions $1200/core year *A core year is equal to 8585 hours Each subscription account includes 50GB of storage

49 What if??? Storage Consulting Additional Cornell Users $59.90/hour $0.91/GB/year Other Academic $85.47/hour $1.45/GB/year Institutions

50 Penguin Computing / IU Partnership HPC cluster as a service and Cloud Services Internet2 Spring Members Meeting 2012 Rich Knepper (rich@iu.edu) Manager, Campus Bridging Indiana University Copyright 2011 Penguin Computing, Inc. All rights reserved

51 What is POD On-demand HPC system > Compute, storage, low latency fabrics, GPU, non-virtualized Robust software infrastructure > Full automation Internet (150Mb, burstable to 1Gb) > User and administration space controls > Secure and seamless job migration > Extensible framework > Complete billing infrastructure Services > Custom product design > Site and workflow integration > Managed services > Application support HPC support expertise > Skilled HPC administrators > Leverage 13 yrs serving HPC market Copyright 2011 Penguin Computing, Inc. All rights reserved 51

52 Clouds look serene enough - But is ignorance bliss? In the cloud, do you know: > Where your data are? > What laws prevail over the physical location of your data? > What license you really agreed to? > What is the security (electronic / physical) around your data? > And how exactly do you get to that cloud, or get things out of it? > How secure your provider is financially? (The fact that something seems unimaginable, like cloud provider such-and-such going out of business abruptly, does not mean it is impossible!) Photo by es/z/in/photostream/

53 Penguin Computing & IU partner for Cluster as a Service Just what it says: Cluster as a Service Cluster physically located on IU s campus, in IU s Data Center Available to anyone at a.edu or FFRDC (Federally Funded Research and Development Center) To use it: > Go to podiu.penguincomputing.com > Fill out registration form > Verify via your > Get out your credit card > Go computing This builds on Penguin s experience - currently host Life Technologies' BioScope and LifeScope in the cloud (

54 We know where the data are and they are secure

55 An example of NET+ Services / Campus Bridging "We are seeing the early emergence of a meta-university a transcendent, accessible, empowering, dynamic, communally constructed framework of open materials and platforms on which much of higher education worldwide can be constructed or enhanced. Charles Vest, president emeritus of MIT, 2006 NET+ Goal: achieve economy of scale and retain reasonable measure of control See: Brad Wheeler and Shelton Waggener Above-Campus Services: Shaping the Promise of Cloud Computing for Higher Education. EDUCAUSE Review, vol. 44, no. 6 (November/December 2009): Campus Bridging goal make it all feel like it s just a peripheral to your laptop (see pti.iu.edu/campusbridging)

56 IU POD Innovation Through Partnership True On-Demand HPC for Internet2 Creative Public/Private model to address HPC shortfall Turning lost EC2 dollars into central IT expansion Tiered channel strategy expansion to EDU sector Program and discipline-specific enhancements under way Objective third party resource for collaboration > EDU, Federal and Commercial Copyright 2011 Penguin Computing, Inc. All rights reserved 56

57 POD IU (Rockhopper) specifications Server Information Architecture Penguin Computing Altus 1804 TFLOPS 4.4 Clock Speed 2.1GHz Nodes 11 compute; 2 login; 4 management; 3 servers CPUs 4 x 2.1GHz 12-core AMD Opteron 6172 processors per compute node Memory Type Distributed and Shared Total Memory 1408 GB Memory per Node 128GB 1333MHz DDR3 ECC Local Scratch Storage 6TB locally attached SATA2 Cluster Scratch 100TB Lustre Further Details OS CentOS 5 Network QDR (40Gb/s) Infiniband, 1Gb/s ethernet Job Management Software SGE Job Scheduling Software SGE Job Scheduling policy Fair Share Access keybased ssh login to headnodes remote job control via Penguin's PODShell

58 Available applications at POD IU (Rockhopper) Package name COAMPS Desmond GAMESS Galaxy GROMACS HMMER Intel LAMMPS MM5 mpiblast NAMD Summary Coupled ocean / atmosphere meoscale prediction system Desmond is a software package developed at D. E. Shaw Research to perform high-speed molecular dynamics simulations of biological systems on conventional commodity clusters. GAMESS is a program for ab initio molecular quantum chemistry. Galaxy is an open, web-based platform for data intensive biomedical research. GROMACS is a versatile package to perform molecular dynamics, i.e. simulate the Newtonian equations of motion for systems with hundreds to millions of particles. HMMER is used for searching sequence databases for homologs of protein sequences, and for making protein sequence alignments. compilers and libraries LAMMPS is a classical molecular dynamics code, and an acronym for Large-scale Atomic/Molecular Massively Parallel Simulator. The PSU/NCAR mesoscale model (known as MM5) is a limited-area, nonhydrostatic, terrain-following sigma-coordinate model designed to simulate or predict mesoscale atmospheric circulation. The model is supported by several pre- and post-processing programs, which are referred to collectively as the MM5 modeling system. mpiblast is a freely available, open-source, parallel implementation of NCBI BLAST. NAMD is a parallel molecular dynamics code for large biomolecular systems.

59 Thank you! Questions? Copyright 2011 Penguin Computing, Inc. All rights reserved 59