SuperStack Next Exit Challenges on CC*IIE at UF Xiaolin (Andy) Li Associate Professor Director, Scalable Software Systems Laboratory (S3Lab) Area Chair of Computer Engineering Division Department of Electrical and Computer Engineering University of Florida, USA http://www.s3lab.ece.ufl.edu/ Acknowledgement: NSF MRI, CC-NIE, GENI, CAREER, PetaApps UF Campus CI Units • RC = Research Compu=ng • UFIT = UF Informa=on Technology – CNS: Computing & Networking Services • FLR = Florida Lambda Rail • SSERCA = Sunshine State Educa=on and Research Compu=ng Alliance – FAU, FIU, FSU, UCF, UF, UM, USF – FAMU, UNF, UWF UF CI Goal • Increase research porHolio – From about $700 million per year – To $1 billion per year • Meet a wide spectrum of research needs – Health, Engineering, Science – Agriculture – Business, Law – Computer Science and Engineering • Cloud, Big Data, Future Internet, Storage • Machine Learning, Data Mining, Bioinforma=cs, CDN • CPS, Internet of Things, Mobile Social Networks RC infrastructure before 2010 • • • • • • • Compute system with 3,500 cores Storage system of 200 TB Networking of 20Gbps Staff of 3.20 FTE 95 research groups from 29 departments 400 users 35 investors RC resources in 2014 • Compute system with 21,000 cores (x6) • Storage system total of 5 PB (x25) • Networking of 200Gbps (x10) – NSF CC-‐NIE (Gateway), MRI (CRNv2/GatorCloud) – ExoGENI Rack – FutureGrid • • • • • • Staff of 10.25 FTE (x3) UF Informa=cs Ins=tute 327 research groups from 87 departments (x3) 1067 users (x2.5) 150 investors (x4) Suppor=ng over $300M in grant ac=vity Science DMZ: Campus Research Network National Lambda Rail, Internet2, GENI (via Jacksonville) 2*10Gb/s upgraded to 2*100Gb/s FLR SSRB CNS Lab Physics HPC Center - Phy SSRB Campus Datacenter 2 100G 2*10Gb/s upgraded to 2*100Gb/s UF 2 GatorVisor 100G 40G 100G 2 2 Physics CMS/OSG 46 U 8 U ECDC HPC Center - ES 100G 2 40G 4 10G 4 4 100G 46 U Data Center 8 U 2 U 1 U CISE Lab Nets Controller 2 U 1 U 3 U 3 U 3 U 3 U 3 U Cloud Green 3 U 8 U Cloud Orange Data Cloud VM Cloud Larsen HPC Center - Eng 8 U 8 U Larsen HCS Lab Hybrid Controller Golfer Cloud Portal VM Cloud Data Cloud 8 U NEB S3Lab Apps Controller Golfer SDN Switch Phase 1 SDN, 40G/10G Phase 2 SDN, 100G SDN Control Plane New Datacenter Major Data Centers at UF HiPerGator Supercomputer Ranking from top500 supercomputer list # 10 among public universi=es in US # 14 among universi=es in US # 493 among all machines listed HiPerGator Supercomputer CMS/OSG Physics HPC Centers ICBR: Interdisciplinary Center for Biotech Research CTSI: Clinical and Transla=onal Science Ins=tute ACIS/CAC Data Center CHREC Data Center NEB Data Center Stakeholders Security Physics Science Artifacts CNS UFIT/ CIO Chemistry RC/HPC Biology/ Bioinform atics BigData/ HPC/CS&E Research Health Energy Others Labor Resources Cost Astronomy MAE Climate/ Ag EE/ SmartGrid Usage RC: Research Computing CNS: Computing & Networking Services CS&E: Computer Science & Engineering Example Uses of RC Infrastructure • The RC infrastructure adds value • Complex mul=disciplinary research endeavors: – CCMT = Center for Compressible Mul=phase Turbulence, PI: S. Balachandar – SECIM = Southeast Center for Integra=ve Metabolomics, PI: A. Edison – Super-‐app for gene-‐sequencing, PI: L. Moroz – Medical sensing, analy=cs, and knowledge fusion, PI: X. Li CMS Experiment $500M experiment Highlighted in red is the endcap muon system whose design and construc=on was led by UF CMS Collabora=on 38 countries 182 ins=tu=ons 3,000 scien;sts and engineers US CMS Collabora=on 48 ins=tu=ons: 2 Na=onal Labs and 46 universi=es UF CMS With almost 40 scien=sts, UF is the 3rd largest US CMS ins=tu=on behind only Fermilab and Univ. of Wisconsin-‐Madison (and ahead of MIT, Princeton, Caltech, Cornell, CMU, and 39 others ) Compressible Mul;phase Turbulence Goals of the Center § To radically advance the field of Compressible Mul=phase Turbulence § To advance predic=ve simula=on science through high performance compu=ng § To advance a co-‐design strategy that combines exascale emula=on, exascale algorithms, exascale M&S § To educate students/postdocs in simula=on science and place them at Na=onal laboratories T1-‐ 14 Integra=ve Metabolomics Core 1: Tim Garrej DRCC at UCSD Within 2 months Core 3: Rick Yost UF RC Storage Process/Normalize Galaxy + Command line Core 2: Art Edison Client mee=ng PI and group members working on the project Gene sequencing from a ship Medical Sensing, Analy=cs, and Fusion Near-line Stream Processing Two-‐Way Knowledge Fusion Context-‐Aware Medical Diagnosis Advanced Signal Processing BLE Noncontact Sensing Brokers Pub/Sub Streaming 2.7cm Sensor PlaRorm Online Query, Interaction, Decision Making Interface Offline Big Data Engine Platform Multiplexing Brokers Sensor Data Streaming Distributed File System Nova Swift Cinder Glance Keystone VitalCloud: Noncontact Vital Sensing Cloud Healthcare Providers Pub/Sub Interaction BLE Features, PaIerns, Symptoms 2.7cm 4.8cm Mobile Apps, Third-‐Party Apps Web Portals/Browsers Mobile Devices Security & Privacy Mechanisms Healthcare Providers Social Friends/Rela;ves Pa;ents, Elders 4.8cm Social Networks/Rela;ves Data Exchange Middleware Neutron EHR Medical Facili;es Challenges & Opportuni=es • Build services on top of this infrastructure • Large need with non-‐tradi=onal users – Tradi=onal Linux cmdline users are just a frac=on – Turbo-‐charge the desktop – Seamless connec=on over networks to storage and compute • Cloud is the way people expect services – Self-‐provision – Self-‐configure – Always on – Accessible from anywhere on any device Emerging Programming Models -‐ for Big Data, Big System, Big Science • Emerging frameworks and rapid innova=ons CIEL" Pregel Pig Percolator Dryad Conven;onal Prac;ces • Rela=vely sta=c environments – HPC administrators are responsible for maintaining the sonware stack – Use PBS/Torque for batch job execu=on – Focusing on MPI framework – (Op=onal) Maintain separated cluster for other frameworks, e.g., MapReduce, OpenStack. Inadequate Support -‐ Mismatch between Requirements of Rapid Innova=on and Rela=vely Rigid Resource Configura=on • Users – Try new frameworks for big data analy=cs; – Innovate on current data analysis frameworks; – Cooperate with other organiza=ons; – …… HPC Clusters » Reduce administrative operation overhead; » Improve resource utilization; » Enrich user experience; » …… q No privileges to users; q No guarantee for cross-‐organiza=on compa=bility; q No method for fine-‐grained, dynamic resource alloca=on; q …… Time for Change Current Sta;c, Par;;oned Target Unified, Mul;plexed, Dynamic Hadoop CIEL" Pregel Pig Percolator Dryad OpenStack Container Torque Virtual Machine Bare Metal OpenFlow SuperStack: Unified Campus Cloud Software-Defined Ecosystem *-as-a-Service Compute, Storage, Network, Platform, Big Data, HPC, CPS, Cloud, AppStore/AppEngine (Res, Net, Sec)
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