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Course: CS 596, Fall 2008
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(Scientific CSCI596 Computing and Visualization) Assignment 1Molecular Dynamics Due: September 15 (Mon), 2008, at the class The purpose of this assignment is to familiarize yourself with the simple molecular dynamics (MD) program, md.c (and its linked-list cell variant, lmd.c). Note that, later in this course, you will need to be able to modify the programs in various projects such as visualization and...

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(Scientific CSCI596 Computing and Visualization) Assignment 1Molecular Dynamics Due: September 15 (Mon), 2008, at the class The purpose of this assignment is to familiarize yourself with the simple molecular dynamics (MD) program, md.c (and its linked-list cell variant, lmd.c). Note that, later in this course, you will need to be able to modify the programs in various projects such as visualization and parallelization. You will also perform basic performance measurements of the programs. 1. (Scaling) Perform a series of runs of the original md.c, in which the number of atoms is changed systematically. Note that the number of atoms is nAtom = 4 InitUcell[0] InitUcell[1] InitUcell[2]. Try a sequence, InitUcell[] = {3,3,3}, {4,4,4}, {5,5,5}, ..., {10,10,10}, for which nAtom = 108, 256, 500, ..., 4000. (Set StepLimit = 10 and StepAvg = 11, and make sure the constant NMAX in md.h is set larger than nAtom.) Plot the elapsed time per MD step as a function of the number of atoms. Fit the measured elapsed time T to the formula, T = CnAtomp, find and the power p (C is the other fitting parameter). Is your measured scaling, T = O(nAtomp), close to O(nAtom2)? Also perform the same measurement for lmd.c. Is your measured scaling now close to O(nAtom)? 2. (Mflops Performance) Performance of a program is often measured in MFlops (million floating point operations per second). Lets choose InitUcell = {10,10,10} (or nAtom = 4000) and measure the elapsed time of lmd.c. Count the number of floating point operations (+, , *, /) executed (for simplicity, count sqrt() as 1 operation). Divide the resulting number by the elapsed time (in seconds) to obtain the ...

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USC - CS - 596
CSCI596 Assignment 2Message Passing Interface Due: September 24 (Wed), 2008, at the class In this assignment, you will write your own global summation program (equivalent to using MPI_Send and MPI_Recv. Your program should run on P = 2l processors (l
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CSCI596 Assignment 3Parallel Computation of Due: October 1 (Wed), 2008 Part I: Programming Write a message passing interface (MPI) program, global_pi.c, to compute the value of based on the lecture note on Parallel Computation of Pi and using the g
USC - CS - 596
CSCI596 Assignment 4Parallel Molecular Dynamics Due: October 8 (Wed), 2008 The purpose of this assignment is to get familiar with the message-passing scheme used in the parallel molecular dynamics (MD) program, pmd.c, and asynchronous messages in the
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CSCI596 Assignment 5: Molecular Dynamics Animation Due: October 22 (Wed), 2008 Combine md.c and atomv.c to write a C/OpenGL program that animates molecular dynamics (MD) simulation in real time. (Follow the lecture note on Visualizing Molecular Dynam
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CSCI596 Assignment 6: Parallel Quantum Dynamics Due: November 3 (Mon), 2008 (at the class) Parallelize the one-dimensional quantum dynamics (QD) simulation program qd1.c, using MPI. Use spatial decomposition, so that processor p [0, P-1] (P is the n
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CSCI596 (Scientific Computing and Visualization) Assignment 7 Hybrid MPI+OpenMP Parallel Molecular Dynamics Due: November 12 (Wed), 2008 (at the class) 1. Write a hybrid MPI+OpenMP parallel molecular dynamics (MD) program (name it hmd.c), starting fr
USC - CS - 596
CSCI596 (Scientific Computing and Visualization) Final Project Anything Related to What You Have Learned in the Class Due: December 17 (Wed), 2008 Submit the following project by Wednesday, December 17. In addition, at 3:30-4:50pm on Wednesday, Decem
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Guidelines for the Final Project I. II. Programming Critical review (&gt;2-3 pages) Dont repeat what the paper says. 1. 2. 3. 4. * III. Problem: Whats the problem? Method: How to solve it? Results: Bottom line? So what? Critique: Flaw? Improvement (how
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84Computer Physics Communications 63 (1991) 8494 North-HollandVisualizing quantum scattering on the CM-2 supercomputerJohn L. Richardson1Received 2 February 1990 Thinking Machines Corporation, 245 First Street, Cambridge, MA 02142-1214, USAWe
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CSCI653: High Performance Computing &amp; SimulationsAiichiro NakanoCollaboratory for Advanced Computing &amp; Simulations Department of Computer Science Department of Physics &amp; Astronomy Department of Chemical Engineering &amp; Materials Science University of
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Molecular Dynamics I: PrinciplesBasics of the molecular-dynamics (MD) method1-3 are described, along with corresponding data structures in program, md.c.Newtons Second Law of MotionTRAJECTORY, COORDINATE, AND ACCELERATION Physical system = a set
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Minimal Complex Analysis Complex function: A mapping from a complex variable z = x + iy (i = f(z) C.&quot;1) to a complex numberDifferentiation: A complex function f(z) at z is differentiable if the quantity ! f (z + &quot;z) # f (z)&quot;zconverges to a
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JOURNALOF COMPUTATIONALPHYSICS73, 315-348 (1987)A Fast Algorithmfor ParticleANDSimulations*L. GREENCARDV. ROKHLINDepartment of Computer Science, Yale Lnipersiry, New Haven, Connecticut 06520 Received June 10. 1986; revised February
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ELSEYIER2s -/.-I@Computer Physics Communications Computer Physics Communications ( 1997)59-69 104Parallel multilevel preconditioned conjugate-gradient approach to variable-charge molecular dynamicsAiichiro Nakano Depurtment of Computer Scienc
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Computer Physics Communications 153 (2003) 445461 www.elsevier.com/locate/cpcScalable and portable implementation of the fast multipole method on parallel computers Shuji Ogata a , Timothy J. Campbell b , Rajiv K. Kalia c,d , Aiichiro Nakano c,d,
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Reversiblemultipletime scale moleculardynamicsM. Tuckermar?) G. J. Martynaand B. J. BerneDepartment of Chemistry, Columbia University, New York, New York 10027 Department of Chemistry, University of Pennsylvania, Philadelphia, Pennsylvani
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Computer Physics CommunicationsELSEVIERComputer Physics Communications 83 (1994) 197214Multiresolution molecular dynamics algorithm for realistic materials modeling on parallel computersAiichiro Nakano, Rajiv K. Kalia, Priya VashishtaConcurrent
USC - CS - 653
Message Passing Interface (MPI) ProgrammingMPI (Message Passing Interface) is a standard message passing system that enables us to write and run applications on parallel computers. In 1992, MPI Forum was formed to develop a portable message passing
USC - CS - 653
OpenMP ProgrammingAiichiro NakanoCollaboratory for Advanced Computing &amp; Simulations Department of Computer Science Department of Physics &amp; Astronomy Department of Chemical Engineering &amp; Materials Science University of Southern California Email: ana
USC - CS - 653
Hybrid MPI+OpenMP Parallel MDAiichiro NakanoCollaboratory for Advanced Computing &amp; Simulations Department of Computer Science Department of Physics &amp; Astronomy Department of Chemical Engineering &amp; Materials Science University of Southern California
USC - CS - 653
Parallel Molecular DynamicsThis chapter explains the example parallel MD program, pmd.c, in detail.Spatial Decomposition Spatial decomposition: The physical system to be simulated is partitioned into subsystems of equal volume. Processors in a pa
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Parallel Molecular DynamicsAiichiro NakanoCollaboratory for Advanced Computing &amp; Simulations Department of Computer Science Department of Physics &amp; Astronomy Department of Chemical Engineering &amp; Materials Science University of Southern California E
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Scalability Metrics for Parallel Molecular DynamicsParallel EfficiencyWe define the efficiency of a parallel program running on P processors to solve a problem of size W. Let T(W, P) be the execution time of this parallel program. Speed of the prog
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Anton, a Special-Purpose Machine for Molecular Dynamics SimulationDavid E. Shaw, Martin M. Deneroff, Ron O. Dror, Jeffrey S. Kuskin, Richard H. Larson, John K. Salmon, Cliff Young, Brannon Batson, Kevin J. Bowers, Jack C. Chao, Michael P. Eastwood,
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Divide-and-Conquer Parallelization ParadigmDivide-and-Conquer Simulation Algorithms Divide-and-conquer (DC) algorithms: Recursively partition a problem into subprogram of roughly equal size. If subprogram can be solved independently, there is a pos
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Divide-&amp;-Conquer ParallelismAiichiro NakanoCollaboratory for Advanced Computing &amp; Simulations Department of Computer Science Department of Physics &amp; Astronomy Department of Chemical Engineering &amp; Materials Science University of Southern California
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Computational Materials Science 38 (2007) 642652 www.elsevier.com/locate/commatsciA divide-and-conquer/cellular-decomposition framework for million-to-billion atom simulations of chemical reactionsAiichiro Nakano a,*, Rajiv K. Kalia a, Ken-ichi No
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DE NOVO ULTRASCALE ATOMISTIC SIMULATIONS ON HIGH-END PARALLEL SUPERCOMPUTERSAiichiro Nakano Rajiv K. Kalia1 Ken-ichi Nomura1 Ashish Sharma1, 2 Priya Vashishta1 Fuyuki Shimojo1,3 4 Adri C. T. van Duin 4 William A. Goddard, III 5 Rupak Biswas Deepak S
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Load BalancingAiichiro NakanoCollaboratory for Advanced Computing &amp; Simulations Department of Computer Science Department of Physics &amp; Astronomy Department of Chemical Engineering &amp; Materials Science University of Southern California Email: anakano
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Lanczos Method for EigensystemsAiichiro NakanoCollaboratory for Advanced Computing &amp; Simulations Department of Computer Science Department of Physics &amp; Astronomy Department of Chemical Engineering &amp; Materials Science University of Southern Californ
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Supplementary Derivations for the Lanczos-Algorithm LectureSpectral representation The eigenvalues and eigenvectors satisfyn n\$ Aij q (&quot; ) = #&quot; qi(&quot; ) = \$ qi(&quot; ) #%&amp;%&quot; , jj=1%=1()(1)where &quot;#\$ = 1 (\$ = #); 0 (\$ % #). Define an orthogona
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Hypergraph-based Dynamic Load Balancing for Adaptive Scientic ComputationsUmit V. Catalyurek, Erik G. Boman, Karen D. Devine, Doruk Bozda , Robert Heaphy, g and Lee Ann Riesen Ohio State University Sandia National Laboratories Dept. of Biomedical
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Improving Memory Hierarchy Performance for Irregular Applications*John Mellor-Crummeyt, T Department of Computer Science, MS 132 Rice University 6100 Main Houston, TX 77005 David Whalleyz, Ken Kennedy?Cjohnmc,ken}@cs.rice.edu AbstractThe gap betw
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SIAM REVIEW Vol. 46, No. 1, pp. 345c 2004 Society for Industrial and Applied MathematicsRecursive Blocked Algorithms and Hybrid Data Structures for Dense Matrix Library SoftwareErik Elmroth Fred Gustavson Isak Jonsson Bo K gstrom aAbstract. Ma
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1 Quantum Dynamics BasicsIn this chapter, we will simulate the dynamics of a particle, such as an electron, which follows the law of quantum mechanics [1]. Basics of the quantum-dynamics (QD) method [2-5] are described, along with corresponding data
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Quantum Dynamics BasicsSpectral MethodIn this chapter, we will solve the time-dependent Schrdinger equation using another numerical technique, i.e., the spectral method, which is based on Fourier transformation.1.Discrete Fourier TransformCons
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13.10 Wavelet Transforms591The splitting point b must be chosen large enough that the remaining integral over (b, ) is small. Successive terms in its asymptotic expansion are found by integrating by parts. The integral over (a, b) can be done usi
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19.6 Multigrid Methods for Boundary Value Problems871standard tridiagonal algorithm. Given u n , one solves (19.5.36) for un+1/2 , substitutes on the right-hand side of (19.5.37), and then solves for u n+1 . The key question is how to choose the
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Computer Physics CommunicationsELSEVIER Computer Physics Communications 83 (1994) 181196Massively parallel algorithms for computational nanoelectronics based on quantum molecular dynamicsAiichiro Nakano, Priya Vashishta, Rajiv K. KaliaConcurrent
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Computer Physics Communications 167 (2005) 151164 www.elsevier.com/locate/cpcEmbedded divide-and-conquer algorithm on hierarchical real-space grids: parallel molecular dynamics simulation based on linear-scaling density functional theoryFuyuki Shi
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Hybrid Particle-Continuum SimulationAiichiro NakanoCollaboratory for Advanced Computing &amp; Simulations Department of Computer Science Department of Physics &amp; Astronomy Department of Chemical Engineering &amp; Materials Science University of Southern Cal