dynamic topology aware load balancing algorithms for md applications
DESCRIPTION
Dynamic Topology Aware Load Balancing Algorithms for MD Applications. Abhinav Bhatele, Laxmikant V. Kale University of Illinois at Urbana-Champaign Sameer Kumar IBM T. J. Watson Research Center. Molecular Dynamics. A system of [charged] atoms with bonds - PowerPoint PPT PresentationTRANSCRIPT
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Abhinav Bhatele, Laxmikant V. KaleUniversity of Illinois at Urbana-Champaign
Sameer KumarIBM T. J. Watson Research Center
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Molecular DynamicsA system of [charged] atoms with bondsUse Newtonian Mechanics to find the positions and
velocities of atomsEach time-step is typically in femto-secondsAt each time step
calculate the forces on all atoms calculate the velocities and move atoms around
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NAMD: NAnoscale Molecular DynamicsNaïve force calculation is O(N2)Reduced to O(N logN) by calculating
Bonded forces Non-bonded: using a cutoff radius
Short-range: calculated every time step Long-range: calculated every fourth time-step (PME)
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Hybrid of spatial and force decomposition
NAMD’s Parallel Design
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Parallelization using Charm++
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Static Mapping
Load Balancing
Bhatele, A., Kumar, S., Mei, C., Phillips, J. C., Zheng, G. & Kale, L. V. 2008 Overcoming Scaling Challenges in Biomolecular Simulations across Multiple Platforms. In Proceedings of IEEE International Parallel and Distributed Processing Symposium, Miami, FL, USA, April 2008.
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Communication in NAMDEach patch multicasts its
information to many computes
Each compute is a target of two multicasts only
Use ‘Proxies’ to send data to different computes on the same processor
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Topology Aware TechniquesStatic Placement of Patches
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Topology Aware Techniques (contd.)Placement of computes
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Load Balancing in Charm++Principle of Persistence
Object communication patterns and computational loads tend to persist over time
Measurement-based Load Balancing Instrument computation time and communication volume
at runtime Use the database to make new load balancing decisions
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NAMD’s Load Balancing StrategyNAMD uses a dynamic centralized greedy strategyThere are two schemes in play:
A comprehensive strategy (called once) A refinement scheme (called several times during a run)
Algorithm:Pick a compute and find a “suitable” processor to place it
on
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Choice of a suitable processorAmong underloaded processors, try to:
Find a processor with the two patches or their proxiesFind a processor with one patch or a proxyPick any underloaded processor
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Highest Priority
Lowest Priority
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Load Balancing MetricsLoad Balance: Bring Max-to-Avg Ratio close to 1Communication Volume: Minimize the number of
proxiesCommunication Traffic: Minimize hop bytes
Hop-bytes = Message size X Distance traveled by message
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Agarwal, T., Sharma, A., Kale, L.V. 2008 Topology-aware task mapping for reducing communication contention on large parallel machines, In Proceedings of IEEE International Parallel and Distributed Processing Symposium, Rhodes Island, Greece, April 2006.
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Results: Hop-bytes
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Results: Performance
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Simulation of WW DomainWW: 30,591- atom simulation on NCSA’s Abe cluster
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Freddolino, P. L., Liu, F., Gruebele, M., & Schulten, K. 2008 Ten-microsecond MD simulation of a fast-folding WW domain Biophysical Journal 94 L75-L77.
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Future WorkA scalable distributed load balancing strategyGeneralized Scenario:
multicasts: each object is the target of multiple multicasts use topological information to minimize communication
Understanding the effect of various factors on load balancing in detail
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NAMD Development Team:Parallel Programming Lab, UIUC – Abhinav Bhatele, Sameer Kumar, David Kunzman, Chee Wai Lee, Chao Mei, Gengbin Zheng, Laxmikant V. KaleTheoretical and Computational Biophysics Group – Jim Phillips, Klaus Schulten
Acknowledgments:Argonne National Laboratory, Pittsburgh Supercomputing Center (Shawn Brown, Chad Vizino, Brian Johanson), TeraGrid