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NAMD Development Goals. L.V. (Sanjay) Kale Professor Dept. of Computer Science http://www.ks.uiuc.edu/Research/namd/. NAMD Vision. Make NAMD a widely used MD program For large molecular systems, Scaling from PCs, clusters, to large parallel machines For interactive molecular dynamics - PowerPoint PPT Presentation
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NIH Resource for Biomolecular Modeling and Bioinformaticshttp://www.ks.uiuc.edu/
Beckman Institute, UIUC
NAMD Development Goals
L.V. (Sanjay) KaleProfessor
Dept. of Computer Sciencehttp://www.ks.uiuc.edu/Research/namd/
NIH Resource for Biomolecular Modeling and Bioinformaticshttp://www.ks.uiuc.edu/
Beckman Institute, UIUC
NAMD Vision
• Make NAMD a widely used MD program– For large molecular systems, – Scaling from PCs, clusters, to large parallel machines– For interactive molecular dynamics
• Goals:– High performance– Ease of use:
• configuration and run
– Ease of modification (for us and advanced users)• Maximize reuse of communication and control patterns• Push parallel complexity down into Charm++ runtime
– Incorporation of features needed by Scientists
NIH Resource for Biomolecular Modeling and Bioinformaticshttp://www.ks.uiuc.edu/
Beckman Institute, UIUC
NAMD 3 New Features
• Software Goal:– Modular architecture to permit reuse extensibility
• Scientific/Numeric Modules:– Implicit solvent models (e.g, generalized Born)– Replica exchange (e.g., 10 on 16 processors)– Self-consistent polarizability with a (sequential) CPU penalty of
less than 100%.– Hybrid quantum/classical mechanics– Fast nonperiodic (and periodic) electrostatics using multiple grid
methods.– A Langevin integrator that permits larger time steps (by being
exact for constant forces).– An integrator module that computes shadow energy.
NIH Resource for Biomolecular Modeling and Bioinformaticshttp://www.ks.uiuc.edu/
Beckman Institute, UIUC
Design
• NAMD 3 will be a major rewrite of NAMD– Incorporate lessons learned in the past years– Use modern features of Charm++– Refactor software for modularity– Restructure for supporting planned features– Algorithms that scale to even larger machines
NIH Resource for Biomolecular Modeling and Bioinformaticshttp://www.ks.uiuc.edu/
Beckman Institute, UIUC
Programmability
• NAMD3 Scientific Modules:– Forces, integration, steering, analysis– Keep code with a common goal together– Add new features without touching old code
• Parallel Decomposition Framework:– Support common scientific algorithm patterns– Avoid duplicating services for each algorithm– Start with NAMD 2 architecture (but not code)
NIH Resource for Biomolecular Modeling and Bioinformaticshttp://www.ks.uiuc.edu/
Beckman Institute, UIUC
Core CHARM++
Clusters Lemieux Teragrid
Collective communication Load balancer
FFT Fault Tolerance Grid Scheduling
Bonds related Force calculation
Integration Pair-wise Forces calculation
PME
Charm++ modules
NAMD Core
Replica exchange QM Implicit Solvents Polarizable Force Field
MDAPI
…
New Science modules
NIH Resource for Biomolecular Modeling and Bioinformaticshttp://www.ks.uiuc.edu/
Beckman Institute, UIUC
MDAPI Modular Interface
• Separate “front end” from modular “engine”• Same program or over a network or grid• Dynamic discovery of engine capabilities, no
limitations imposed by interface• Front ends: NAMD 2, NAMD 3, Amber,
CHARMM, VMD• Engines: NAMD 2, NAMD 3, MINDY
NIH Resource for Biomolecular Modeling and Bioinformaticshttp://www.ks.uiuc.edu/
Beckman Institute, UIUC
Terascale Biology and ResourcesPSC LeMieux
RikenMDGRAPE
NCSATungsten
TeraGrid
ASCI Purple
Red StormThor’s Hammer
CRAY X1
NIH Resource for Biomolecular Modeling and Bioinformaticshttp://www.ks.uiuc.edu/
Beckman Institute, UIUC
NAMD on Charm++• Active computer science collaboration (since 1992)• Object array - A collection of chares,
– with a single global name for the collection, and– each member addressed by an index– Mapping of element objects to processors handled by the system
A[0] A[1] A[2] A[3] A[..]
A[3]A[0]
User’s view
System view
NIH Resource for Biomolecular Modeling and Bioinformaticshttp://www.ks.uiuc.edu/
Beckman Institute, UIUC
NAMD3 Features Based on Charm++
• Adaptive load balancing• Optimized communication
– Persistent Communication, Optimized concurrent multicast/reduction• Flexible, tuned, parallel FFT libraries• Automatic Checkpointing• Ability to change the number of processors • Scheduling on the grid• Fault tolerance
– Fully automated restart– Survive loss of a node
• Scaling to large machines– fine-grained parallelism for PME: bonded and nonbonded force
evaluations
NIH Resource for Biomolecular Modeling and Bioinformaticshttp://www.ks.uiuc.edu/
Beckman Institute, UIUC
Efficient Parallelization for IMD
• Characteristics– Limited parallelism on small systems– Real time response needed
• Fine grained parallelization– Improve speedups on 4K-30K atom systems– Time/step goal
• Currently 0.2s/step for BrH on single processor (P4 1.7GHz)• Targeting on 0.003s/step on 64 processors of faster machine, that is
20picosecond/minute
• Flexible use of clusters– Migrating jobs (shrink/expand)– Better utilization when machine is idle
NIH Resource for Biomolecular Modeling and Bioinformaticshttp://www.ks.uiuc.edu/
Beckman Institute, UIUC
Integration with CHARMM/Amber?
• Goal: NAMD as parallel simulation engine for CHARMM/Amber
• Generate input files in CHARMM/Amber– NAMD must read native file formats
• Run with NAMD on parallel computer– Need to use equivalent algorithms
• Analyze simulation in CHARMM/Amber– NAMD must generate native file formats