Abhinav S Bhatele Department of Computer Science University of Illinois at UrbanaChampaign httpcharmcsuiucedu Email bhateleillinoisedu Feb 13th 2009 Abhinav S Bhatele 2 University of Illinois ID: 530887
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Slide1
The Charm++ Programming Model and NAMD
Abhinav S BhateleDepartment of Computer ScienceUniversity of Illinois at Urbana-Champaign
http://charm.cs.uiuc.edu
E-mail: bhatele@illinois.eduSlide2
Feb 13th, 2009
Abhinav S Bhatele
2
University of Illinois
Urbana-Champaign,
Illinois, USASlide3
Processor Virtualization
User View
System View
Programmer: Decomposes the computation into objects
Runtime: Maps the computation on to the processors
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Abhinav S BhateleSlide4
Benefits of the Charm++ Model
Software EngineeringNumber of VPs independent of physical processorsDifferent sets of VPs for different computationsDynamic MappingLoad balancing
Change the set of processors usedMessage-driven executionCompositionalityPredictability
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Abhinav S BhateleSlide5
Charm++ and CSE Applications
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Abhinav S Bhatele
Gordon Bell Award, SC 2002
Fine-grained CPAIMD
Cosmological SimulationsSlide6
Adaptive MPI (AMPI)
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MPI “Processes” - Implemented as virtual “processes” (light-weight user level
migratable
threads)Slide7
Load Balancing
Based on Principle of PersistenceRuntime instrumentationMeasures communication volume and computation time
Measurement based load balancersUse the instrumented data-base periodically to make new decisionsMany alternative strategies can use the database
Centralized
vs
distributed
Greedy improvements
vs
complete reassignments
Taking communication into account
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Abhinav S Bhatele
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NAMD
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NAnoscale
Molecular Dynamics
Simulates the life of bio-molecules
Simulation window broken
down into a large number of time steps (typically 1
fs
each)
Forces
on each atom calculated every step
Positions and velocities updated and atoms migrated to their new positionsSlide9
Parallelization of NAMD
Hybrid DecompositionFeb 13th, 2009
Abhinav S Bhatele
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Control Flow
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Non-bonded Work
Bonded Work
Integration
PME
CommunicationSlide12
Optimizations on MareNostrum
Fixes to the CVS versionCrash due to a xlc compiler bugPerformance analysisUsing Projections performance analysis tool
Performance tuningConfiguration parameters for NAMD to enable high parallelization
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Abhinav S Bhatele
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Performance Tuning
Increasing the number of objectstwoAway{X, Y, Z} optionsChoice of PME implementationSlab (1D) vs. Pencil (2D) decompositionOffloading processors doing PME
Use of spanning tree for communicationFeb 13th, 2009
Abhinav S Bhatele
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DD on MareNostrum
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Abhinav S BhateleSlide15
DD with Slab PME
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DD with Pencil PME
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Problem?
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1.2 msSlide18
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Abhinav S Bhatele
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Nucleosome on MareNostrum
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Abhinav S BhateleSlide20
Membrane on MareNostrum
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Abhinav S BhateleSlide21
Similar Problem?
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16 ms
Bandwidth on
Myrinet
: 250 MB/s
Expected Latency for 6-10 KB messages < 0.1 msSlide22
Optimizations on the Xe Cluster
Getting the CVS version running (over mpi)Trying a development version of charmRuns directly over
Infiniband (ibverbs)Currently unstable
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DD on Xeon Cluster
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Abhinav S BhateleSlide24
Thank You!