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"The Cutting Edge Can Hurt You"
The document summarizes challenges faced by early adopters of next generation DNA sequencing technology and potential solutions. It discusses issues such as high upfront costs of sequencers, data storage and management difficulties due to the large amount of data generated, networking and data transfer problems, and lack of laboratory information management systems. Potential solutions proposed include using virtualization and cloud computing through Amazon Web Services, developing a wiki-based laboratory information management system, simplifying storage architectures, and automated data capture and management.
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"The Cutting Edge Can Hurt You"
- 1. The Cutting EdgeCan Hurt You Stories from real-world adopters of next generation sequencing technology Christopher Dwan The Bioteam
- 2. Bioteam • Consultancy, witha software business • Vendor Neutral, Technology Agnostic • “Bridge the gap” between high performance computing and life sciences • Founded 2003 Shameless Plugs: • We’re in Booth 113 • Next Generation Sequencing Workshop (yesterday, plus next year) • http://bioteam.net • We’re hiring.
- 3. cdwan@bioteam.net Disclaimer • Most BioTeamclients don’t have 7 figure IT budgets, Petabyte SANs dedicated datacenters, and so on. • Many of these problems: – Are quite different for the largest Bio-HPC centers – Simply don’t matter to the nationally funded projects.
- 4. I offer noanswers… cdwan@bioteam.net
- 5. Review: 2007 Predictions •Multi-core commodity processors – Workstations are already insanely powerful. • Virtualization on the workstation – Why port code, when you can make a new machine? • Reconfigurable computing goes mainstream – Partnerships, Collaborations, and re-seller agreements. • Next generation DNA sequencing – Data tsunami
- 6. 2007 Predictions -Reviewed • Multi-core commodity processors – I touched a 16 core workstation with 10TB of disk. It “just worked.” • Virtualization on the workstation Everywhere! Including Data! – I saw a workstation replace 6 legacy OS’s in one shop. • Reconfigurable computing goes mainstream Seemingly not yet – Talk to the folks on the show floor to get strong contradictions. • Next generation DNA sequencing. Yup. – Data tsunami
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- 8. $5M: If youget one of these … cdwan@bioteam.net
- 9. You probably knowabout these cdwan@bioteam.net
- 10. cdwan@bioteam.net Next Generation Sequencing •Costs – Instrument cost: $5x105 to $106 – Reagent Cost: $3k - $10k – ~ 1 TB / machine / day – 4 or 5 vendors • Cost imbalance with IT components – $7k for an experiment – $3k for a new server • Opens high-throughput to much smaller labs.
- 11. Next Generation Sequencing •Naming is annoying: – “Next gen”, “new gen”, “now gen” • High Throughput DNA Sequencing – Helicos, Roche, Illumina, ABI, Church Lab – Also other domains: Cofocal microscopes, mass spec, … “The old days, which were about two years ago”
- 12. Fundamentals • Standard facilitiesquestsion: – Heat / Power / Floor capacity, just as much as ever • Network: – Moving 1TB of data from instrument to the next room, much less to a collaborator – Still with the sneakernet. • Security • Data • Lab information management
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- 14. Information Management • Day0 – Simply catching the data and not dropping it is a challenge. • 3 months – Postdocs carrying data around on firewire disks – Data management with post-it notes. • 6 months – Instrument vendor updates their software. – Re-analysis? • 1 year – New machine from a different vendor.
- 15. Networking / DataMotion • Data motion can interfere with data acquisition (go on, ask the instrument vendor) • Software updates can interfere with attempts to automate data motion • Move 1TB of data from lab to network closet – Old building network, instrument offline for hours – Small $200 4 port gigabit switch (see “security”) – Excuse for a building-wide upgrade, 1 year horizon
- 16. Security • Network andIT Security: serious job. • Labs must propose workable solutions, not wait for security staff to provide them. • Common observations: – Mess with building wide network = security audit – No solution = system offline. “Stay out of the news”
- 17. Humans are theproblem Lab Instruments Tape Backup Compute Cluster One-off Linux / Windows Machine RAID / Data Store Dev Workstation Management: Throughput? Status? Schedule? Security? Lab Staff Availability, quality, “did it work?” IT Staff Throughput? Status? Schedule Bioinformaticians Access to data, metadata,
- 18. Automation is thesolution Lab Instruments Tape Backup Compute Cluster One-off Linux / Windows Machine RAID / Data Store Dev Workstation Management Machines need to write web pages IT Staff Offer levels of service, negotiate directly with scientists Bioinformaticians Access to data, metadata, LIMS
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- 21. cdwan@bioteam.net Automatic data capture- Ra Most structured content can be captured and recorded by programs as it is generated
- 22. cdwan@bioteam.net File data raid Meta data wiki Wikilims:Next Gen Data Store
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- 24. cdwan@bioteam.net Launch an assembly Launchan assembly on the cluster
- 25. WikiLIMS • Still soldas a custom service – No long term license – Full source code access – Highly customizable • Variety of customers: – Navy Medical Research Labs – Cold Spring Harbor – Emory University – National Cancer Institute – … • Both 113, we’ll talk your ear off. This is the semantic web
- 26. All updates happeningat once cdwan@bioteam.net
- 27. STORAGE AND BACKUPS “Ontheir way to becoming a sick joke”
- 28. cdwan@bioteam.net Storage • Storage: Samein 2008 as in 2006 – Unhappy technology tradeoffs – ‘Exotic’ vendors offer blazing speed and a few features – ‘Mainstream’ vendors exclusively focused on enterprise – What I need: Massive scaling, decent speed & grab bag of enterprise features • Real World Solution, early 2008: – 100TB disk, backup, small cluster, plus all infrastructure – Price range: $225k - $998k Cut the problem into pieces.
- 29. Archive vs. Resequence •2007 – Shocking suggestion to delete primary data – Sanger suggested the MAID (Massive Array of Idle Disks) – Novartis reported that 97% of their files are never accessed 3 months after generation. • 2008 – Instrument vendors deleting large volumes of data inside the box. – Less shock, more “data lifecycle” “New instrument data would be different anyway”
- 30. Data Storage • 1TB – $200 @ Savers ($0.20 / GB) • 24 – 48TB – Commodity solutions, many vendors ($0.70 /GB) • 100TB+ – Interesting architectural tradeoffs – Decision should be based on support expectations – Below $3 / GB really scares me • 1 – 2PB – “Large”
- 31. cdwan@bioteam.net •100+TB SAN •50+ computenodes •One rather warm closet.
- 32. Backups are legion •Archive: – 1TB Firewire disk - $150 – 800GB LTO4 Tape - $90 (plus a sizable machine) • Disaster Recovery: – Failover, redundancy, etc. – Just buy two of everything. • Incremental Rollback – Traditional “backups” – Daily, weekly, differentials Talk to Finance people about backups.
- 35. Data Ingest (instruments) Legacy StorageArchitecture 4PB Tape Archive 24TB “hot” disk For analysis SGI SMP Machines Linux Cluster Caching problem Workstations Web / FTP access
- 36. Data Ingest (instruments) New RealitiesAllow Simplification 4PB Tape Backup 1PB “hot” disk For analysis SGI SMP Machines Linux Cluster Workstations Web / FTP access
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- 38. cdwan@bioteam.net Amazon Web Services •EC2 for virtualized computing – The economics are compelling • One month of serious experimentation: – $9.00 USD billed to credit card – Various money making approaches • Flexible pricing allows reselling & revenue sharing • Create a EC2 image and add my own fees on top to cover development and support costs – As a developer, I don’t need your credit card • Amazon handles all transactions & billing
- 39. Bioteam and AmazonEC2 • This is the grid: – Every Bioteam consultant independently deployed an EC2 solution in 2008. • Inquiry – Since 2004 - “bioinformatics on a cluster” – Apple, Microsoft CCS, Linux, etc. – May 1, 2008: Inquiry on Amazon EC2 – CPU Cost to customer: $10 / node day • Data service: 500GB, constantly updated: – $1400 yr: downloads, maintenance, and storage – $17 yr / cost to Bioteam to support a customer
- 40. Conclusion If scientists arewasting a bunch of time on IT, we’ve got more work to do.
- 41. Disturbing Observation I seemto have presented both a functional “grid” and an instance of a “semantic web” in the same talk.
- 42. Thank You • CambridgeHealthtech Institute – Cindy Crowninshield, Kevin Davies • Bioteam Customers – Ed Delong (MIT), Tim Read (NMRC), Yuri Kotliari (NIH), CSHL • Bioteam – Mike Cariaso, Chris Dagdigian, Stan Gloss, Brian Osborne, Bill Van Etten, Jiesheng Zhang • Community – Bioclusters, Sun Grid Engine, Bioinformatics.org
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