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Interactive Problem Solving: The Polder Meta Computing Inititiative. Peter Sloot Computational Science University of Amsterdam, The Netherlands. Ariadne’s Red-Rope. From PSE to Virtual Laboratory and Motivation Architecture Infrastructure Job Level: Hierarchical Scheduling

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Interactive Problem Solving: The Polder Meta Computing Inititiative


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    1. Interactive Problem Solving:The Polder Meta Computing Inititiative Peter Sloot Computational Science University of Amsterdam, The Netherlands

    2. Ariadne’s Red-Rope • From PSE to Virtual Laboratory and Motivation • Architecture • Infrastructure • Job Level: Hierarchical Scheduling • Resource management: Task-migration • Interaction && Case implementation • Interactive Algorithms

    3. Virtual Laboratory Environment Advanced Scientific Domains Computational Physics System Engineering Computational Bio-medicine Local User Local User Virtual Simulation & Exploration Environment (ViSE) Communication & collaboration (ComCol) Virtual-lab Information Management for Cooperation (VIMCO) Physical apparatus Distributed Computing & Gigabit Local Area Network ViSE Net Client App. User MRI/CT Internet 2 Wide Area Network

    4. Interactive Computing: Why? • Goal: From Data, via Information to Knowledge • Complexity: Huge data-sets, complex processes • Approach: Parametric exploration and sensitivity analyses: • Combine raw (sensory) data with simulation • Person in the loop: • Sensory interaction • Intelligent short-cuts

    5. Intro: Case study from biomedicine...

    6. In Vitro In Vivo In Silico Changing the Paradigm

    7. In Vitro In Vivo In Silico Changing the Paradigm

    8. In Vitro In Vivo In Silico Changing the Paradigm

    9. Diagnosis & Planning Treatment Observation Current Situation

    10. Fast, High-throughput Low Latency Internet High Performance Super Computing New Possibilities in the VL • Time and Space Independence • 3D Information • Simulation based planning • Surgeon ‘in the loop’

    11. Experimental set-up

    12. Architecture

    13. Cave Origine 2000 9 10 11 12 13 14 8 15 7 16 6 17 5 18 4 19 ATM 3 20 2 1 0 23 22 21 GRAPE1 GRAPE0 Architecture Continued: Hybrid system • Host: The DAS • 24 node parallel cluster in a 200 node wide area machine • 200 MHz Pentium Pro • Myrinet 150MB/s • ATM wide-area interconnect between clusters

    14. Immersive Environments

    15. 3D Information and Interaction

    16. Problem: Curse of dynamics: Static task load Dynamic task load Static task allocation Predictable reallocation Dynamical reallocation Static resource load Dynamic resource load

    17. Solution To Curse • Performance of a parallel program usuallydictated by slowest task • Task resource requirements and available resources both vary dynamically • Therefore, optimal task allocation changes • Gain must exceed cost of migration • Resources used by long-running programs may be reclaimed by owner

    18. Node A Node B PVMtask 1 PVMD A PVMD B Node C PVMtask 2 PVMD C Dynamite Initial State Two PVM tasks communicating through a network of daemons Migrate task 2 to node B

    19. Node A Node B Newcontext PVMtask 1 PVMD A PVMD B Node C Program PVM Ckpt PVMD C Prepare for Migration Create new context for task 2 Tell PVM daemon B to expect messages for task 2 Update routing tables in daemons (first B, then A, later C)

    20. Checkpointing Node A Node B Newcontext PVMtask 1 PVMD A PVMD B Node C Program PVM Ckpt PVMD C Send checkpoint signal to task 2 Flush connections Checkpoint task to disk

    21. Cross-cluster checkpointing(design) Node A Node B Helper task PVMtask 1 PVMD A PVMD B Node C Program PVM Ckpt PVMD C Send checkpoint signal to task 2 Flush connections, close files Checkpoint task to disk via helper task

    22. Restart Execution Node A Node B NewPVM task 2 PVMtask 1 PVMD A PVMD B Node C PVMD C Restart checkpointed task 2 on node B Resume communications Re-open & re-position files

    23. Special considerations • Preserve communication • PVM should continue to run as if nothing happened • Use location independent addressing • Open files • Preserve open file state

    24. Performance • Migration speed largely dependent on the speed of shared file system • and that depends mostly on the network • NFS over 100 Mbps Ethernet • 0.4 s < Tmig < 15 s for 2 MB < sizeimg < 64 MB • Communication speed reduced due to added overhead • 25% for 1 byte direct messages • 2% for 100 KB indirect messages

    25. Current status: Dynamite Part • Checkpointer operational under • Solaris 2.5.1 and higher (UltraSparc, 32 bit) • Linux/i386 2.0 and 2.2 (libc5 and glibc 2.0) • PVM 3.3.x applications supported and tested • Pam-Crash (ESI) - car crash simulations • CEM3D (ESI) - electro-magnetics code • Grail (UvA) - large, simple FEM code • NAS parallel benchmarks • BloodFlow • MPI and socket (Univ. of Krakow) libraries available • Scheduling not yet satisfactory

    26. Architecture: Revisited

    27. Design Considerations • High Quality presentation • High Frame rate • Intuitive interaction • Real-time response • Interactive Algorithms • High performance computing and networking...

    28. Problem: Time, time what has become of us?

    29. Solution: Asynchronicity

    30. A police officer to guide the asynchronous processes

    31. Runtime Support • Need generic framework to support modalities • Need interoperability • High Level Architecture (HLA): • data distribution across heterogeneous platforms • flexible attribute and ownership mechanisms • advanced time management

    32. Provoking a bit… Progress in natural sciences comes from taking things apart ... Progress in computer science comes from bringing things together...

    33. Proof is in the pudding... • Diagnostic Findings • Occluded right iliac artery • 75% stenosis in left iliac artery • Occluded left SFA • Diffuse disease in right SFA

    34. Problem: From Image to Simulation MR Scan of Abdomen MR Scan of Legs

    35. Solution: 3DManual initialization Place start point Place one or more end points Wave propagates from start- to end point Backtrack = first estimation of the centerline Wave propagates from ‘centerline’  vessel wall Distance Transform from vessel wall to center  centerline

    36. Wavefront Propagation Place start point Place one or more end points Wave propagates from start- to end point Backtrack = first estimation of the centerline Wave propagates from ‘centerline’  vessel wall Distance Transform from vessel wall to center  centerline

    37. MRA: Backtrack Place start point Place one or more end points Wave propagates from start- to end point Backtrack = first estimation of the centerline Wave propagates from ‘centerline’  vessel wall Distance Transform from vessel wall to center  centerline

    38. MRA: Wavefront Propagation Place start point Place one or more end points Wave propagates from start- to end point Backtrack = first estimation of the centerline Wave propagates from ‘centerline’  vessel wall Distance Transform from vessel wall to center  centerline

    39. MRA: Distance Transform Place start point Place one or more end points Wave propagates from start- to end point Backtrack = first estimation of the centerline Wave propagates from ‘centerline’  vessel wall Distance Transform from vessel wall to center  centerline

    40. 3-D selection of region of interest

    41. Tracking the vessels

    42. Building the Geometric Models

    43. VR-Interaction

    44. Alternate Treatments Preop AFB w/ E-S Prox.Anast. AFB w/ E-E Prox.Anast. Angio w/Fem-Fem Angio w/ Fem-Fem & Fem-Pop

    45. Problem: Flow through complex geometry • After determining the vascular structure simulate the blood-flow and pressure drop… • Conventional CFD methods might fail: • Complex geometry • Numerical instability wrt interaction • Inefficient shear-stress calculation

    46. Solution to interactive flow simulation • Use Cellular Automata as a mesoscopic model system: • Simple local interaction • Support for real physics and heuristics • Computational efficient

    47. Mesoscopic Fluid Model • Fluid model with Cellular Automata rules • Collision: particles reshuffle velocities • Imposed Constraints • Conservation of mass • Conservation of momentum • Isotropy Details...

    48. ...Equivalence with NS • For lattice with enough symmetry: equivalent to the continuous incompressible Navier-Stokes equations: Implicit parallel and complex geometry support.

    49. Efficient Calculation of Shear-Stress Perpendicular momentum transfer: AND the momentum stress tensor P thatis linearly related to the shear stresses sab From LBE scheme:

    50. 10 cm/sec 0 cm/sec Velocity Magnitude