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![1. About Jisc
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![1. About Jisc
Janet network
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Uploaded byMartin Hamilton
Shared services - the future of HPC and big data facilities for UK research
The document discusses shared services and advancements in high-performance computing (HPC) and big data facilities for UK research, emphasizing the role of JISC in enabling collaboration among institutions. Key topics include recent developments in HPC, data management, and equipment sharing initiatives, along with insights from panel discussions involving leaders from various universities and research institutions. The document outlines challenges faced in integrating technologies and the future potential for enhancing research efficiency through improved infrastructure and support systems.
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Shared services - the future of HPC and big data facilities for UK research
- 1. Shared services –the future of HPC & big data facilities for UK research? Martin Hamilton, Jisc David Fergusson & Bruno Silva, Francis Crick Institute Andreas Biternas, King’s College london Thomas King, Queen Mary University of London Photo credit: CC-BY-NC-ND JiscHPC & Big Data 2016
- 2. Shared services forHPC & big data 1. About Jisc – Who, why and what? – Success stories 2. Recent developments 3. Personal perspectives & panel discussion – David Fergusson & Bruno Silva, Francis Crick Institute – Andreas Biternas, King’sCollege London – Thomas King, Queen Mary University of London
- 3. 1. About Jisc HPC& Big Data 2016
- 4. 1. About Jisc Jiscis the UK higher education, further education and skills sectors’ not-for-profit organisation for digital services and solutions.This is what we do: › Operate shared digital infrastructure and services for universities and colleges › Negotiate sector-wide deals, e.g. with IT vendors and commercial publishers › Provide trusted advice and practical assistance
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- 6. 1. About Jisc Janetnetwork [Image credit: Dan Perry]
- 7. 1. About Jisc Janetnetwork [Image credit: Dan Perry]
- 8. 1. About Jisc Netflix Voicenet Akamai VirginRadio Bogons Logicalis UK Pipex / GXN BBC Datahop InTechnology INUK Simplecall LINX multicast Gamma Google Simplecall Redstone Updata aql Voicenet Google Limelight Limelight Akamai BTnet Init7 Amazon Microsoft EU (viaTN) Telekom Malaysia Globelynx 10Gbit/s 1Gbit/s 100Gbit/s GÉANT GÉANT+ LINX Microsoft EU (viaTW) Total external connectivity ≈ 1Tbit/s Leeds Akamai Google VM for LGfLInTechnology NHS N3 Exa Networks Synetrix BBC (HD 4K pilots) One Connect Glasgow & Edinburgh HEAnet BBC (Pacific Quay) Gamma BBC (HD 4K pilots) NHS N3 SWAN (Glas) SWAN (Edin) Manchester Telecity Harbour Exch. Telehouse North & West VM for LGfL RM for Schools VM for LGfL RM for Schools GlobalTransit Tata IXManchester IXLeeds GlobalTransit Level3 GlobalTransit Level3
- 9. 1. About Jisc Doingmore, for less
- 10. 1. About Jisc www.jisc.ac.uk/about/vat-cost-sharing-group VATCost Sharing Group › Largest in UK (we believe) › 93% of HEIs › 256 institutions participating
- 11. 2. Recent developments HPC& Big Data 2016
- 12. 2. Recent developments www.jisc.ac.uk/financial-x-ray FinancialX-Ray › Easily understand and compare overall costs for services › Develop business cases for changes to IT infrastructure › Mechanism for dialogue between finance and IT departments › Highlight comparative cost of shared and commercial third party services
- 13. 2. Recent developments Assent(formerly Project Moonshot) › Single, unifying technology that enables you to effectively manage and control access to a wide range of web and non- web services and applications. › These include cloud infrastructures, High Performance Computing, Grid Computing and commonly deployed services such as email, file store, remote access and instant messaging www.jisc.ac.uk/assent
- 14. 2. Recent developments Equipmentsharing › Brokered industry access to £60m public investment in HPC › Piloting the Kit-Catalogue software, helping institutions to share details of high value equipment › Newcastle University alone is sharing £16m+ of >£20K value equipment via Kit-Catalogue Photo credit: HPC Midlands http://bit.ly/jiscsharing
- 15. 2. Recent developments http://bit.ly/jiscsharing Equipmentsharing › Working with EPSRC and University of Southampton to operationalise equipment.data as a national service › 45 organisations sharing details of over 12,000 items of equipment › Conservative estimate: £240m value › Evidencing utilisation & sharing?
- 16. 2. Recent developments JanetReach: › £4M funding from BIS to work towards a Janet which is "open and accessible" to industry › Provides industry access to university e-infrastructure facilities to facilitate further investment in science, engineering and technology with the active participation of business and industry › Modelled on Innovate UK competition process bit.ly/janetreach
- 17. 2. Recent developments JanetReach: › £4M funding from BIS to work towards a Janet which is "open and accessible" to industry › Provides industry access to university e-infrastructure facilities to facilitate further investment in science, engineering and technology with the active participation of business and industry › Modelled on Innovate UK competition process bit.ly/jisc-hpc
- 18. 2. Recent developments ResearchData Management Shared Service › Procurement under way › Aiming to pilot for 24 months starting this summer › 13 pilot institutions › Research Data Network › Find out more: researchdata.jiscinvolve.org
- 19. 2. Recent developments ResearchData Discovery Service › Alpha! › Uses CKAN to aggregate research data from institutions › Test system has 16.7K datasets from 14 organisations so far › Search and browse: ckan.data.alpha.jisc.ac.uk
- 20. 3. Personal perspectives& panel discussion HPC & Big Data 2016
- 21. 3 . Personalperspectives www.jisc.ac.uk/shared-data-centre
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- 23. 3. Personal perspectives ›David Fergusson › Head of Scientific Computing › Bruno Silva › HPC Lead › Francis Crick Institute
- 24. eMedLab: Merging HPC andCloud for Biomedical Research Dr Bruno Silva eMedLab Service Operations Manager HPC Lead - The Francis Crick Institute bruno.silva@crick.ac.uk 01/12/2015
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- 29. Federated Institutional support eMedLab Ops team Inst.Support Inst. Support Inst. Support Inst. Support Inst. Support Inst. Support No funding available for dedicated staff!
- 30. Winning bid • 6048cores (E5-2695v2) • 252 IBM Flex servers, each with • 24 cores • 512GB RAM per compute server • 240GB SSD (2x120GB RAID0) • 2x10Gb Ethernet • 3:1 Mellanox Ethernet fabric • IBM GSS26 – Scratch 1.2PB • IBM GSS24 – General Purpose (Bulk) 4.3PB • Cloud OS – OpenStack
- 32. Benchmark results preliminary • AggregateHPL (one run per server – embarrassingly parallel) • Peak 460Gflops*252 = 116Tflops • Max – 94% • Min – 84% • VM ≈ Bare metal HPL runs (16 core)
- 33. Benchmark results preliminary –bare metal only • Storage throughput Bulk File System (gpfsperf GB/s) Scratch File System (gpfsperf GB/s) Create Read Write Create Read Write Sequential Sequential Random Sequential Random Sequential Sequential Random Sequential Random 16M 16M 512K 16M 512K 16M 512K 16M 512K 16M 16M 512K 16M 512K 16M 512K 16M 512K 100 88 86 131 22 96 97 89 60 141 84 83 107 20 137 137 125 28
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- 37. Projects • Principal Investigator/ Project lead • Reports to eMedLab governance • Controls who has access to project resources • Project Systems Administrator • Institutional resource and / or • Specialised research team member(s) • Works closely with eMedLab support • Researchers • Those who utilise the software and data available in eMedLab for the project
- 38. Governance MRC eMedLab Project Board (Board) Executive Committee(Exec) Resource Allocation Committee (RAC) Technical Governance Group (TGG) Research Projects Operations
- 39. Federated Institutional support OperationsTeam Support (Support to facilitators and Systems Administrators) Institutional Support (direct support to research) Tickets Training Documentation elasticluster
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- 41. Pilot Projects • SpirosDenaxas - Integrating EHR into i2b2 data marts
- 42. Pilot Projects • TaaneClark – Biobank Data Analysis – evaluation of analysis tools
- 43. Pilot Projects • MichaelBarnes - TranSMART
- 44. Pilot Projects • ChelaJames - Gene discovery, rapid genome sequencing, somatic mutation analysis and high-definition phenotyping VM Image Installing OS CPU RAM Disk “Flavours” VM Instanc e 1 VM Instanc e N Network Start/Stop/Hold/Checkpoint Instance Horizon Console SSH - External IP SSH – Tunnel Web interface, etc…
- 45. Pilot Projects • PeterVan Loo – Scalable, Collaborative, Cancer Genomics Cluster elasticluster
- 46. Pilot Projects • JavierHerrero - Collaborative Medical Genomics Analysis Using Arvados
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- 50. Challenges - Support •High Barrier to entry • Provide environments that resemble HPC or Desktop, or more intuitive interfaces • Engender new thinking about workflows • Promote Planning and Resource management • Train support staff as well as researchers • Resource-intensive support • Promote community-based support and documentation • Provide basic common tools and templates • Upskill and mobilise local IT staff in departments • Move IT support closer to the research project – Research Technologist
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- 52. Challenges - Integration •Suitability of POSIX Parallel file systems for Cloud Storage • Working closely with IBM • Copy-on-write feature of SS (GPFS) is quite useful for fast instance creation • SS has actually quite a lot of the scaffolding required for a good object store • Presentation SS or NAS to VMs requires additional AAAI layer • Working closely with Red Hat and OCF to deliver IdM • Presentation of SS to VMs introduces stability problems that could be worked- around with additional SS licenses and some bespoke scripting • Non-standard Network and Storage architecture • Additional effort by vendors to ensure stable and performant infrastructure up-to- date infrastructure – great efforts by everyone involved! • Network re-design
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- 54. Challenges - Performance •File System Block Re-Mapping • SS performs extremely well with 16MB blocks – we want to leverage this • Hypervisor overhead (not all cores used for compute) • Minimise number of cores “wasted” on cloud management • On the other hand fewer cores means more memory bandwidth • VM IO performance potentially affected by virtual network stack • Leverage features available in the Mellanox NICs such as RoCE, SR-IOV, and offload capabilities
- 55. Challenges – Performance BlockRe-Mapping • SS (GPFS) is very good at handling many small files – by design • VMs perform random IO reads and a few writes with their storage • VM storage (and Cinder storage pools) are very large files on top of GPFS • VM block size does not match SS (GPFS) block size Bulk File System (gpfsperf GB/s) Scratch File System (gpfsperf GB/s) Create Read Write Create Read Write Sequential Sequential Random Sequential Random Sequential Sequential Random Sequential Random 16M 16M 512K 16M 512K 16M 512K 16M 512K 16M 16M 512K 16M 512K 16M 512K 16M 512K 100 88 86 131 22 96 97 89 60 141 84 83 107 20 137 137 125 28
- 56. Challenges – Performance BlockRe-Mapping • Idea: turn random into sequential IO • Have a GPFS standing Bulk File System (gpfsperf GB/s) Scratch File System (gpfsperf GB/s) Create Read Write Create Read Write Sequential Sequential Random Sequential Random Sequential Sequential Random Sequential Random 16M 16M 512K 16M 512K 16M 512K 16M 512K 16M 16M 512K 16M 512K 16M 512K 16M 512K 100 88 86 131 22 96 97 89 60 141 84 83 107 20 137 137 125 28
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- 58. Challenges - Presentation •Access to eMedLab through VPN only • Increases security • Limits upload throughput • Rigid, non-standard networking • Immediately provides a secure environment with complete separation • Projects only need to add VMs to the existing network • Very inflexible, limits the possibility of a shared ecosystem of “public” services • Introduces great administration overheads when creating new projects – space for improvement
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- 62. Challenges - Security •Presentation of SS shared storage to VMs raises security concerns • VMs will have root access – even with squash, user can sidestep identity • Re-export SS with a server-side authentication NAS protocol • Alternatively, abstract shared storage with another service such as iRODS • Ability of OpenStack users to maintain security of VMs • Particularly problematic when deploying “from scratch” systems • A competent, dedicated PSA mitigates this
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- 64. Challenges - Allocation •Politics and Economics of “unscheduled” cloud • Resource allocation in rigid portions of infrastructure (large, medium, small) • Onus of resource utilisation is with Project team • A charging model may have to be introduced to promote good behaviour • The infrastructure supplier does not care about efficiency, as long as cost is recovered • Scheduling over unallocated portions of infrastructure may help maximise utilisation • Benefits applications that function as Direct Acyclid Graphs (DAGs) • Private cloud is finite and limited • Once it is fully allocated, projects will be on a waiting list, rather than a queue • Cloud bursting can “de-limit” the cloud, if funding permits it • This would be a talk on its own.
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- 66. Future Developments • VMand Storage performance analysis • Create optimal settings recommendations for Project Systems Administrators and Ops team • Revisit Network configuration • Provide a simpler, more standard OpenStack environment • Simplify service delivery, account creation, other administrative tasks • Research Data Management for Shared Data • Could be a service within the VM services ecosystem • IRODS is a possibility • Explore potential of Scratch • Integration with Assent (Moonshot tech) • Access to infrastructure through remote credentials and local authorisation • First step to securely sharing data across sites (Safe Share project)
- 67. Conclusions • eMedLab isground breaking in terms • Institutional collaboration around a shared infrastructure • Federated support model • Large scale High Performance Computing Cloud (it can be done!) • Enabling a large scale highly customisable workloads for Biomedical research • Linux cluster still required (POSIX legacy applications) • SS guarantees this flexibility at very high performance • We can introduce Bare Metal (Ironic) if needed for a highly versatile platform • Automated scheduling of granular workloads • Can be done inside the Cloud • True Parnership - OCF, Red Hat, IBM, Lenovo, and Mellanox • Partnership working very well • All vendors highly invested in eMedLab’s success
- 68. The Technical DesignGroup • Mike Atkins – UCL (Project Manager) • Andy Cafferkey – EBI • Richard Christie – QMUL (Chair) • Pete Clapham – Sanger • David Fergusson – the Crick • Thomas King – QMUL • Richard Passey – UCL • Bruno Silva – the Crick
- 69. Institutional Support Teams UCL: Facilitator:David Wong PSA: Faruque Sarker Crick: Facilitator: David Fergusson/Bruno Silva PSA: Adam Huffman, Luke Raimbach, John Bouquiere LSHTM: Facilitator: Jackie Stewart PSA: Steve Whitbread, Kuba Purebski
- 70. Institutional Support Teams Sanger: Facilitator:Tim Cutts, Josh Randall PSA: Peter Clapham, James Beal EMBL-EBI: Facilitator: Steven Newhouse/Andy Cafferkey PSA: Gianni Dalla Torre QMUL: Tom King
- 71. Operations Team Thomas Jones(UCL) Pete Clapham (Sanger) William Hay (UCL) James Beale (Sanger) Luke Sudbery (UCL) Tom King (QMUL) Bruno Silva (Ops Manager, Crick) Adam Huffman (Crick) Andy Cafferkey (EMBL-EBI) Luke Raimbach (Crick) Rich Boyce (EMBL-EBI) Stefan Boeing (Data Manager, Crick) David Ocana (EMBL-EBI)
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- 73. VM Image Installing OS CPU RAMDisk “Flavours” VM Instanc e 1 VM Instanc e N Network Start/Stop/Hold/Checkpoint Instance Horizon Console SSH - External IP SSH – Tunnel Web interface, etc…
- 74. VM Instanc e 1 VM Instanc e N Tenant Network Open Stack Cinder BlockStorage (single VM access) The Internet Tenant Network
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- 76. example research themesto be studied in the Academy Labs; by exploiting the commonalities underl the datasets, we shall build tools and algorithms that cut across the spectrum of diseases. Storage,)Compute,)Security,)Networking) Access)to)Infrastructure) Tools)&)analy<cs) Genomic,)imaging,)clinical)datasets) Cancer,)rare)and)cardiovascular)diseases) GSK,)Saran)Cannon,) DDN,)Intel,)IBM,) Aridhia)) Farr)Ins<tute,) Genomics)England,) UCLH)BRC) Informa<on)flow) links) ELIXIR,)ENCODE,) 1000)Genomes,) Ensembl) Proposed)funding) External)funding) Fig#1.
- 77. users to sh withinmul will also services a developed systems. programme infrastructu resources technologie parts of th others. Ea guaranteed Private( Secure( Collabora0ve( Space( Partner( projects( eMedLab( Partner( projects( Partner( projects( EBI( Partner( projects( FARR@UCLP( Kings(( Health( Partners( Fig#3.!The!co shared!data resources!al
- 78. Winning bid • StandardCompute cluster • Ethernet network fabric • Spectrum Scale storage • Cloud OS
- 79. Initial requirements • Hardwaregeared towards very high data throughput work – capable for running an HPC cluster and a Cloud based on VMs • Cloud OS (open source and commercial option) • Tiered storage system for: • High performance data processing • Data Sharing • Project storage • VM storage
- 80. Bid responses –interesting facts • Majority providing OpenStack as the Cloud OS • Half included an HPC and a Cloud environment • One provided a Vmware-based solution • One provided a OpenStack-only solution • Half tender responses offered Lustre • One provided Ceph for VM storage
- 81. 3. Personal perspectives ›Andreas Biternas › HPC & Linux Lead › King’s College London
- 82. CHALLENGES HAVING ASERVER FARM IN THE CENTER OF LONDON A N D R EAS B I T ER NAS F A CU LTY OF N A TU RAL A N D M A T HEMATICAL S C I ENCES King’s College HPC infrastructure in JISC DC
- 83. • Cost ofSpace: Roughly £25k per square meter in Strand; • Power: • Expensive switches and UPS which require annual maintenance; • Unreliable power supply due to high demand in center of London; • Cooling: • Expensive cooling system similar to one in Virtus DC; • High cost for running and maintenance of the system; • Weight: Due to the oldness of the building, there are strict weight restrictions as an auditorium is below the server farm(!); • Noise pollution: There is strong noise from the server farm up to 2 floors below; Problems and costs of having server farm in Strand campus
- 84. King’s college infrastructurein Virtus DC • Total 25 cabinets with ~200 racks in Data Hall 1: • 16 cabinets HPC cluster ADA+Rosalind; • Rest King’s Central IT infrastructure: fileservers, firewalls etc.; • Rosalind, a consortium between Faculty of Natural and Mathematical Sciences, South London and Maudsley NHS Foundation Trust BRC( Biomedical Research Centre) and Guy’s and St Thomas’ NHS Foundation Trust BRC; • Rosalind has around 5000 cores, ~150 Teraflops, HPC and Cloud part using OpenStack;
- 85. Features of VirtusDatacentre • Power: • Two Redundant central power connections; • UPS & onsite power generator; • Two redundant PSU in each rack ; • Cooling: • Chilled water system cooled via fresh air; • Configures as hot and cold aisles; • Services: • Remote hands; • Installation and maintenance; • Office, storing spaces and wifi; • Secure access control environment;
- 86. • Better internetconnection; • No “single” connections; • Fully resilient network; • The bandwidth requirements of large data sets were being met; Connectivity with Virtus Datacentre
- 87. • Due tothe contract with JISC, tenants(Francis Crick Institute, Queen Mary University, King’s College etc.) have special rates; • Costs: • Standard fee for each rack which includes costs of space, cooling, connectivity etc.; • Power consumed form each rack in normal market(education) prices; Costs of Virtus Datacentre
- 88. 3. Personal perspectives ›Thomas King › Head of Research Infrastructure › Queen Mary University of London
- 89. Queen Mary University ofLondon Tom King Head of Research Infrastructure, IT Services
- 90. Who are we? 20,000 students and 4,000 staff 5 campuses in London 3 faculties Humanities & Social Sciences Science & Engineering Barts & the London School of Medicine and Dentistry
- 91. Copyright Tim Peake,ESA, NASA
- 92. Old World IT Small central provision Lots of independent teams offering a lot of overlap in services and bespoke solutions 21 machine rooms
- 93. IT Transformation Programme2012-15 Centralisation of staff and services ~200 people Consolidation into two data centres On-site ~20 racks Off-site facility within fibre channel latency distances Highly virtualised environment Enterprise services run in active-active JISC Janet6 upgrades
- 94. Research IT Serviceswe support – HPC Research Storage Hardware hosting Clinical and secure systems Enterprise virtualisation is not what we’re after Five nines is not our issue – bang for buck No room at the inn Build our own on-site? The OAP home
- 95. Benefits of shareddata centre Buying power and tenant’s association Better PUE than smaller on-site DC contribution to sustainability commitment Transparent costing for power use Network redundancy – L2 and L3 of JISC network Collaboration – it’s all about the data Cloudier projects Emotional detachment from blinking LEDs Direction of funding – GridPP, Environmental omics Cloud
- 96. That’s all folks… Exceptwhere otherwise noted, this work is licensed under CC-BY Martin Hamilton Futurist, Jisc, London @martin_hamilton martin.hamilton@jisc.ac.uk HPC & Big Data 2016