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- 1. WP3 Tools: distributed molecular simulations and remote submission interface Toni Giorgino Computational Biochemistry and Biophysics Lab / GRIB-IMIM www.multiscalelab.org 22-23 jan 2009
- 2. VPH NoE Meeting - Oxford Thursday, January 22, 2009 Toni Giorgino 13 MD at the microsecond scale Full-atom MD is computationally expensive All solvation water molecules modeled Non-bonded interactions All degrees of freedom in a protein z
- 3. VPH NoE Meeting - Oxford Thursday, January 22, 2009 Toni Giorgino 14 MD at the microsecond scale Full-atom MD is computationally expensive All solvation water molecules modeled Non-bonded interactions All degrees of freedom in a protein z
- 4. VPH NoE Meeting - Oxford Thursday, January 22, 2009 Toni Giorgino 15 Tackled at several scales Combine advances of large-scale infrastructures ⇒ distributed computing ...with those in commodity computing architectures ⇒ GPU One node (CPU) 0.4 ns/day 1
- 5. VPH NoE Meeting - Oxford Thursday, January 22, 2009 Toni Giorgino 16 Tackled at several scales Combine advances of large-scale infrastructures ⇒ distributed computing ...with those in commodity computing architectures ⇒ GPU One node (CPU) 0.4 ns/day Within-node 1
- 6. VPH NoE Meeting - Oxford Thursday, January 22, 2009 Toni Giorgino 17 Tackled at several scales Combine advances of large-scale infrastructures ⇒ distributed computing ...with those in commodity computing architectures ⇒ GPU One node (CPU) 0.4 ns/day One node, accelerated 4.5 ns/day Within-node 1
- 7. VPH NoE Meeting - Oxford Thursday, January 22, 2009 Toni Giorgino 18 Tackled at several scales Combine advances of large-scale infrastructures ⇒ distributed computing ...with those in commodity computing architectures ⇒ GPU One node (CPU) 0.4 ns/day One node, accelerated 4.5 ns/day Within-node Among-nodes1
- 8. VPH NoE Meeting - Oxford Thursday, January 22, 2009 Toni Giorgino 19 Tackled at several scales Combine advances of large-scale infrastructures ⇒ distributed computing ...with those in commodity computing architectures ⇒ GPU One node (CPU) 0.4 ns/day One node, accelerated 4.5 ns/day Distributed computing X 1,700, growing Within-node Among-nodes1
- 9. VPH NoE Meeting - Oxford Thursday, January 22, 2009 Toni Giorgino 20 Tools One node (CPU) 0.25 ns/day One node, accelerated 4.6 ns/day Distributed computing X 1,700, growing Within-node Among-nodes1
- 10. VPH NoE Meeting - Oxford Thursday, January 22, 2009 Toni Giorgino 21 Tools One node (CPU) 0.25 ns/day One node, accelerated 4.6 ns/day Distributed computing X 1,700, growing Within-node Among-nodes1 AceMD
- 11. VPH NoE Meeting - Oxford Thursday, January 22, 2009 Toni Giorgino 22 Tools One node (CPU) 0.25 ns/day One node, accelerated 4.6 ns/day Distributed computing X 1,700, growing Within-node Among-nodes1 AceMD Boinc
- 12. VPH NoE Meeting - Oxford Thursday, January 22, 2009 Toni Giorgino 23 Tools One node (CPU) 0.25 ns/day One node, accelerated 4.6 ns/day Distributed computing X 1,700, growing Within-node Among-nodes1 AceMD Boinc
- 13. VPH NoE Meeting - Oxford Thursday, January 22, 2009 Toni Giorgino 24 Computing architecture Based on BOINC (Berkeley Open Infrastructure for Network Computing) Allows (loosely-coupled) computations to be distributed over the Internet Volunteers contribute CPU cycles Not MD-specific Public statistics at www.boincstats.com
- 14. VPH NoE Meeting - Oxford Thursday, January 22, 2009 Toni Giorgino 25 Using computing power • The infrastructure becomes useful for the community with a distributed submission system One node (CPU) 0.25 ns/day One node, accelerated 4.6 ns/day Distributed computing × 2,000, growing Within-node Among-nodes1
- 15. VPH NoE Meeting - Oxford Thursday, January 22, 2009 Toni Giorgino 26 Using computing power • The infrastructure becomes useful for the community with a distributed submission system One node (CPU) 0.25 ns/day One node, accelerated 4.6 ns/day Distributed computing × 2,000, growing Within-node Among-nodes1 Sim.entry point
- 16. VPH NoE Meeting - Oxford Thursday, January 22, 2009 Toni Giorgino 27 Using computing power • The infrastructure becomes useful for the community with a distributed submission system One node (CPU) 0.25 ns/day One node, accelerated 4.6 ns/day Distributed computing × 2,000, growing Within-node Among-nodes1 Sim.entry point Research team 1 – hERG Scientist 2 – gA … Research team N – protN
- 17. VPH NoE Meeting - Oxford Thursday, January 22, 2009 Toni Giorgino 28 Remote simulation submission • Pre-defined “best practice” submission protocols • Researchers stage in/out files – They are taken in charge by Boinc • Accounting: – Given the scale of deployment, increasing “trustedness” associated to each simulation – FLOPS consumed
- 18. VPH NoE Meeting - Oxford Thursday, January 22, 2009 Toni Giorgino 29 Example: submission 1. Client parses local files and prepares a description of the simulation (may contain user-supplied metadata) 2. Inputs are uploaded to a staging area 3. Execution • Consis check • Move to execution area • Launch simulation 4. Results continuously produced; “work units” spanned until the protocol ends (# of ns × bins) 5. Clients periodically retrieve & delete results
- 19. VPH NoE Meeting - Oxford Thursday, January 22, 2009 Toni Giorgino 30 Technically boinc_submit − Uploads local input files − Creates config, launches WUs, etc − Returns immediately boinc_stat boinc_retrieve [boinc_cancel et al]
- 20. VPH NoE Meeting - Oxford Thursday, January 22, 2009 Toni Giorgino 31 Common traits All client commands have a notion of username and password to send for authentication Authentication checked with Boinc protocol Server remembers uploaded files for later deletion (server-side “RemoteWU” entity) A RemoteWU has an ID for the clients to retrieve − ideally equal to the usual WU id
- 21. VPH NoE Meeting - Oxford Thursday, January 22, 2009 Toni Giorgino 32 Outlook • Expose remote submission interfaces • Identify ontologies for inclusion of relevant annotations • Introduce metadata at least for annotating inputs (to be carried out in outputs)