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Fast Parallel Algorithms for Short-Range Molecular Dynamics

by Steve Plimpton - JOURNAL OF COMPUTATIONAL PHYSICS , 1995
"... Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dyn ..."
Abstract - Cited by 653 (7 self) - Add to MetaCart
Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently -- those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed--memory parallel machine which allows for message--passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers -- the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventi...
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NAMD2: Greater Scalability for Parallel Molecular Dynamics

by Laxmikant Kale , Robert Skeel, Milind Bhandarkar, Robert Brunner, Attila Gursoy, Neal Krawetz, James Phillips, Aritomo Shinozaki, Krishnan Varadarajan, Klaus Schulten - JOURNAL OF COMPUTATIONAL PHYSICS , 1998
"... Molecular dynamics programs simulate the behavior of biomolecular systems, leading to insights and understanding of their functions. However, the computational complexity of such simulations is enormous. Parallel machines provide the potential to meet this computational challenge. To harness this ..."
Abstract - Cited by 322 (45 self) - Add to MetaCart
Molecular dynamics programs simulate the behavior of biomolecular systems, leading to insights and understanding of their functions. However, the computational complexity of such simulations is enormous. Parallel machines provide the potential to meet this computational challenge. To harness this potential, it is necessary to develop a scalable program. It is also necessary that the program be easily modified by application-domain programmers. The

NAMD: biomolecular simulation on thousands of processors

by James C Phillips , Gengbin Zheng , Sameer Kumar , Laxmikant V Kalé - In Supercomputing , 2002
"... Abstract NAMD is a fully featured, production molecular dynamics program for high performance simulation of large biomolecular systems. We have previously, at SC2000, presented scaling results for simulations with cutoff electrostatics on up to 2048 processors of the ASCI Red machine, achieved with ..."
Abstract - Cited by 113 (33 self) - Add to MetaCart
Abstract NAMD is a fully featured, production molecular dynamics program for high performance simulation of large biomolecular systems. We have previously, at SC2000, presented scaling results for simulations with cutoff electrostatics on up to 2048 processors of the ASCI Red machine, achieved with an object-based hybrid force and spatial decomposition scheme and an aggressive measurement-based predictive load balancing framework. We extend this work by demonstrating similar scaling on the much faster processors of the PSC Lemieux Alpha cluster, and for simulations employing efficient (order N log N) particle mesh Ewald full electrostatics. This unprecedented scalability in a biomolecular simulation code has been attained through latency tolerance, adaptation to multiprocessor nodes, and the direct use of the Quadrics Elan library in place of MPI by the Charm++/Converse parallel runtime system.
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Scalable algorithms for molecular dynamics simulations on commodity clusters

by Kevin J. Bowers, Edmond Chow, Huafeng Xu, Ron O. Dror, Michael P. Eastwood, Brent A. Gregersen, John L. Klepeis, Istvan Kolossvary, Mark A. Moraes, Federico D. Sacerdoti, John K. Salmon, Yibing Shan, David E. Shaw - In SC ’06: Proceedings of the 2006 ACM/IEEE Conference on Supercomputing , 2006
"... Although molecular dynamics (MD) simulations of biomolecular systems often run for days to months, many events of great scientific interest and pharmaceutical relevance occur on long time scales that remain beyond reach. We present several new algorithms and implementation techniques that significan ..."
Abstract - Cited by 68 (5 self) - Add to MetaCart
Although molecular dynamics (MD) simulations of biomolecular systems often run for days to months, many events of great scientific interest and pharmaceutical relevance occur on long time scales that remain beyond reach. We present several new algorithms and implementation techniques that significantly accelerate parallel MD simulations compared with current stateof-the-art codes. These include a novel parallel decomposition method and message-passing techniques that reduce communication requirements, as well as novel communication primitives that further reduce communication time. We have also developed numerical techniques that maintain high accuracy while using single precision computation in order to exploit processor-level vector instructions. These methods are embodied in a newly developed MD code called Desmond that achieves unprecedented simulation throughput and parallel scalability on commodity clusters. Our results suggest that Desmond’s parallel performance substantially surpasses that of any previously described code. For example, on a standard benchmark, Desmond’s performance on a conventional Opteron cluster with 2K processors slightly exceeded the reported performance of IBM’s Blue Gene/L machine with 32K processors running its Blue Matter MD code. 1.
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Overcoming Scaling Challenges in Biomolecular Simulations across Multiple Platforms

by Abhinav Bhatele, Sameer Kumar, Chao Mei, James C. Phillips, Gengbin Zheng, Laxmikant V. Kalé
"... NAMD † is a portable parallel application for biomolecular simulations. NAMD pioneered the use of hybrid spatial and force decomposition, a technique used now by most scalable programs for biomolecular simulations, including Blue Matter and Desmond developed by IBM and D. E. Shaw respectively. NAMD ..."
Abstract - Cited by 48 (32 self) - Add to MetaCart
NAMD † is a portable parallel application for biomolecular simulations. NAMD pioneered the use of hybrid spatial and force decomposition, a technique used now by most scalable programs for biomolecular simulations, including Blue Matter and Desmond developed by IBM and D. E. Shaw respectively. NAMD is developed using CHARM++ and benefits from its adaptive communication-computation overlap and dynamic load balancing. This paper focuses on new scalability challenges in biomolecular simulations: using much larger machines and simulating molecular systems with millions of atoms. We describe new techniques we have developed to overcome these challenges. Since our approach involves automatic adaptive runtime optimizations, one interesting issue involves harmful interaction between multiple adaptive strategies, and how to deal with them. Unlike most other molecular dynamics programs, NAMD runs on a wide variety of platforms ranging from commodity clusters to supercomputers. It also scales to large machines: we present results for up to 65,536 processors on IBM’s Blue Gene/L and 8,192 processors on Cray XT3/XT4 in addition to results on NCSA’s Abe, SDSC’s DataStar and TACC’s LoneStar cluster, to demonstrate efficient portability. Since our IPDPS’06 paper two years ago, two new highly scalable programs named Desmond and Blue Matter have emerged, which we compare with NAMD in this paper. 1
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PROTOMOL, an Object-Oriented Framework for Prototyping Novel Algorithms for Molecular Dynamics

by Thierry Matthey, Trevor Cickovski, Scott Hampton, Alice Ko, Qun Ma - In Computational Science—ICCS 2003, International Conference , 2002
"... Factory [Gamma et al. 1995, pp. 87-95] and the Prototype [Gamma et al. 1995, pp. 117-126] patterns. The Abstract Factory pattern delegates the object creation, and the Prototype pattern allows dynamic configuration. The factory is in charge of converting the user-specified force into an object that ..."
Abstract - Cited by 34 (18 self) - Add to MetaCart
Factory [Gamma et al. 1995, pp. 87-95] and the Prototype [Gamma et al. 1995, pp. 117-126] patterns. The Abstract Factory pattern delegates the object creation, and the Prototype pattern allows dynamic configuration. The factory is in charge of converting the user-specified force into an object that has been properly setup to do computation. The factory creates replicas of "prototypes" that have been registered by the developer. This restricts the factory to create only supported objects, since not all combinations of R1-R5 make sense or are supported at a given stage of development.

Achieving Strong Scaling with NAMD on Blue Gene/L

by Sameer Kumar, Chao Huang, Gheorghe Almasi, Laxmikant V. Kalé - In Parallel and Distributed Processing Symposium, 2006. IPDPS 2006. 20th International , 2006
"... NAMD is a scalable molecular dynamics application, which has proven its performance on several parallel com-puter architectures. Strong scaling is necessary for molec-ular dynamics as problem size is fixed, and a large num-ber of iterations need to be executed to understand interest-ing biological p ..."
Abstract - Cited by 19 (5 self) - Add to MetaCart
NAMD is a scalable molecular dynamics application, which has proven its performance on several parallel com-puter architectures. Strong scaling is necessary for molec-ular dynamics as problem size is fixed, and a large num-ber of iterations need to be executed to understand interest-ing biological phenomenon. The Blue Gene/L machine is a massive source of compute power. It consists of tens of thou-sands of embedded Power PC 440 processors. In this paper, we present several techniques to scale NAMD to 8192 pro-cessors of Blue Gene/L. These include topology specific op-timizations, new messaging protocols, load-balancing, and overlap of computation and communication. We were able to achieve 1.2 TF of peak performance for cutoff simula-tions and 0.99 TF with PME. 1
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ProtoMol: A molecular dynamics framework with incremental parallelization

by T. Matthey, J. A. Izaguirre - In Proc. of the Tenth SIAM Conf. on Parallel Processing for Scientific Computing (PP01), Proceedings in Applied Mathematics , 2001
"... Molecular dynamics (MD) for a classical unconstrained simulation of bimolecular systems requires the solution of Newton’s equations of motion. At each step, one evaluates the contribution of interacting forces, and these are applied to the system using a numerical integrator. The most computationall ..."
Abstract - Cited by 18 (10 self) - Add to MetaCart
Molecular dynamics (MD) for a classical unconstrained simulation of bimolecular systems requires the solution of Newton’s equations of motion. At each step, one evaluates the contribution of interacting forces, and these are applied to the system using a numerical integrator. The most computationally expensive part is the force evaluation among atoms.
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MSA: Multiphase specifically shared arrays

by Jayant Desouza, Laxmikant V. Kalé - In Proceedings of the 17th International Workshop on Languages and Compilers for Parallel Computing , 2004
"... Abstract. Shared address space (SAS) parallel programming models have faced difficulty scaling to large number of processors. Further, although in some cases SAS programs are easier to develop, in other cases they face difficulties due to a large number of race conditions. We contend that a multi-pa ..."
Abstract - Cited by 16 (8 self) - Add to MetaCart
Abstract. Shared address space (SAS) parallel programming models have faced difficulty scaling to large number of processors. Further, although in some cases SAS programs are easier to develop, in other cases they face difficulties due to a large number of race conditions. We contend that a multi-paradigm programming model comprising a distributedmemory model with a disciplined form of shared-memory programming may constitute a “complete ” and powerful parallel programming system. Optimized coherence mechanisms based on the specific access pattern of a shared variable show significant performance benefits over general DSM coherence protocols. We present MSA, a system that supports such specifically shared arrays that can be shared in read-only, write-many, and accumulate modes. These simple modes scale well and are general enough to capture the majority of shared memory access patterns. MSA does not support a general read-write access mode, but a single array can be shared in read-only mode in one phase and write-many in another. MSA coexists with the message-passing paradigm (MPI) and the processor virtualization-based message-driven paradigm(Charm++). We present the model, its implementation, programming examples and preliminary performance results. 1 1
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Scalable Molecular Dynamics for Large Biomolecular Systems

by Robert K. Brunner, James C. Phillips, Laxmikant V. Kalé - In Proceedings of Supercomputing (SC) 2000 , 2000
"... We present an optimized parallelization scheme for molecular dynamics simulations of large biomolecular systems, implemented in the production-quality molecular dynamics program NAMD. With an object-based hybrid force and spatial decomposition scheme, and an aggressive measurement-based predictiv ..."
Abstract - Cited by 11 (1 self) - Add to MetaCart
We present an optimized parallelization scheme for molecular dynamics simulations of large biomolecular systems, implemented in the production-quality molecular dynamics program NAMD. With an object-based hybrid force and spatial decomposition scheme, and an aggressive measurement-based predictive load balancing framework, we have attained speeds and speedups that are much higher than any reported in literature so far. The paper first summarizes the broad methodology we are pursuing, and the basic parallelization scheme we used. It then describes the optimizations that were instrumental in increasing performance, and presents performance results on benchmark simulations. 1 Introduction Understanding the structure and function of biomolecules such as proteins and DNA is crucial to our ability to understand the mechanisms of diseases, drugs, and normal life processes. With the experimental determination of structures for an increasing set of proteins it has become possible to em...
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