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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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

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

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

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’

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

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

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)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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: