1. NIH Resource for Biomolecular Modeling and Bioinformatics http://www.ks.uiuc.edu/ Beckman Institute, UIUC NAMD Development Goals L.V. (Sanjay) Kale Professor Dept. of Computer Science http://www.ks.uiuc.edu/Research/namd/

2. NIH Resource for Biomolecular Modeling and Bioinformatics http://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 Specific Goals for NAMD 3: –High performance –Ease of use: Easy to configure, set-up, and run –Ease of modification (for us and advanced users) –Incorporation of features needed by Scientists

3. NIH Resource for Biomolecular Modeling and Bioinformatics http://www.ks.uiuc.edu/ Beckman Institute, UIUC NAMD 3 New Features Scientific/Numeric Modules: –Implicit solvent models (e.g, generalized Born) –Replica exchange (e.g., 10 on 16 processors) –Hybrid quantum/classical mechanics –Self-consistent polarizability with a (sequential) CPU penalty of less than 100%. –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.

4. NIH Resource for Biomolecular Modeling and Bioinformatics http://www.ks.uiuc.edu/ Beckman Institute, UIUC Terascale Biology and Resources PSC LeMieux Riken MDGRAPE NCSA Tungsten TeraGrid ASCI Purple Red Storm Thor’s Hammer CRAY X1

5. NIH Resource for Biomolecular Modeling and Bioinformatics http://www.ks.uiuc.edu/ Beckman Institute, UIUC NAMD on Charm++ NAMD uses these diverse resources using Charm++ Active computer science collaboration (since 1992) Object array - A collection of objects, –Mapping of 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

6. NIH Resource for Biomolecular Modeling and Bioinformatics http://www.ks.uiuc.edu/ Beckman Institute, UIUC Namd 3 Features Based on Charm++ Adaptive load balancing Optimized communication Flexible, tuned, parallel FFT libraries Ability to change the number of processors Automatic Checkpointing Scheduling on the grid Fault tolerance –Fully automated restart –Surviving loss of a node Scaling to large machines –fine-grained parallelism ATPase synthase 1.02 TeraFLOPs

7. NIH Resource for Biomolecular Modeling and Bioinformatics http://www.ks.uiuc.edu/ Beckman Institute, UIUC Design for Programmability Software Goal: –Modular architecture to permit reuse and extensibility NAMD 3 will be a major rewrite of NAMD –Incorporate lessons learned in the past years –Use modern features of Charm++ –Re-factor software for modularity Separate physics modules from parallel framework –Restructure for supporting planned features –Algorithms that scale to even larger machines

8. NIH Resource for Biomolecular Modeling and Bioinformatics http://www.ks.uiuc.edu/ Beckman Institute, UIUC Core CHARM++ ClustersLemieuxTeragrid Collective communicationLoad balancer FFTFault ToleranceGrid Scheduling Bonds related Force calculation IntegrationPair-wise Forces calculation PME Charm++ modules NAMD Core Replica exchangeQMImplicit SolventsPolarizable Force Field MDAPI … New Science modules

9. NIH Resource for Biomolecular Modeling and Bioinformatics http://www.ks.uiuc.edu/ Beckman Institute, UIUC MDAPI Modular Interface Linked Executable LAN Grid Front End : Input/Output User Interface Engine Force Computation Integration,.. VMD Namd 3 Namd Amber Namd 2 MINDY Charm Dynamic discovery of engine capabilities

10. NIH Resource for Biomolecular Modeling and Bioinformatics http://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 3ms/step on 64 processors (20 ps/min) Flexible use of clusters: –Timeshare background and interactive jobs

11. NIH Resource for Biomolecular Modeling and Bioinformatics http://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

12. NIH Resource for Biomolecular Modeling and Bioinformatics http://www.ks.uiuc.edu/ Beckman Institute, UIUC Proud to be Programmers!