Резултати от работата на Националния център за суперкомпютърни приложения за 2009г

суперкомпютърни приложения за 2009г

1. 
   Проекти
   

В изпълнение на договора, подписан между Националния център за суперкомпютърни приложения и бившата Държавна агенция за информационни технологии и съобщения, на 18.06.2009г бе обявен конкурса „ Създаване софтуерни среди за българския суперкомпютърен комплекс и свързаните с него мултипроцесорни клъстери”. Бяха класирани и сключени договори със следните колективи:

1. 
   Колектив с ръководител доц.д-р. Леандър Литов. Предмет на договора е
   

Задълженията на колектива са :

2. Колектив с ръководител проф.д-р. Ваньо Митев, д.б.н. Предмет на договор е изпълнението на проекта “Виртуален скрининг и моделиране на взаимодействието на кандидати за лекарства с биомолекули”. Проектът бе финансиран с 30 хил. лева

Задълженията на колектива са :

-да избере подходящи молекули и лиганди, да създаде библиотека от потенциални инхибитори, да моделира свързването на инхибиторорите с биомолекулите като използва Autodock4.2 и Dock6.3;

-да оптимизира параметрите на модела и да направи оценка на надеждността на моделиране на реални комплекси инхибитори-биомолекули

-да подготви ръководство по използването на всеки пакет биохимичните изследвания, в молекулярната медицина и фармацията и да организиране курсове за студенти и докторанти от Медицински университет - София .

Задълженията на колектива са :

- проектиране, разработване, инсталиране, верифициране и тестване на софтуер за определяне на местоположението и оценка на щетите от пожари, наводнения, обезлесяване и други природни бедствия;

- изготвяне на документация към всеки пакет, ръководства за потребители и организиране на периодични курсове обучение на потребителите.

Задълженията на колектива са :

-разработване и инсталация на програмни пакети за оптимално разполагане на сензори, определяне координати на събитията и автоматична ориентация на сензорите и идентификация на човешки лица по изображения от видео камери.

-изготвяне на документация към всеки пакет, ръководства за потребители и организиране на периодични курсове за обучение на потребителите.

Задълженията на колектива са :

-разработване и инсталация на програмни пакети EDF Saturne, EDF Syrthis, EDF Aster и EDF Salome. Центърът предостави тези пакети.

-разработване на документация към всеки пакет, ръководства за потребители и организиране на периодични курсове обучение на потребителите.

Задълженията на колектива са :

-да инсталира и тества на програмния пакет, да настрои параметрите и да провери модела с реални метеорологични и емисионни данни, да изследва скалируемостта, да анализира резултатите и да подготви описание на формата на използваните входни данни и получаваните изходни данни.

– да изготви на документация към всеки пакет, ръководства за потребители и организиране на периодични курсове за обучение на потребителите.

Задълженията на колектива са :

- да инсталира пакетите от библиотеки Trilinos, Hypre и ParFE

- да подготви документация към всеки пакет, ръководства за потребители и да организира периодични курсове за обучение на потребителите.

2. 
   Пакети приложни програми и програмни библиотеки
   

Националният център за суперкомпютърни приложения вече разполага с приложен софтуер и програмни библиотеки с общ обем повече от 6,379 мегабайта (около 6.4 гигабайта). Със суперкомпютърния комплекс не бе закупен нито един пакет приложен софтуер.

Над 70% от описаните по-долу пакети програми и библиотеки вече са модифицирани така, че да могат да се инсталират на Blue Gene/P или на свързаните с него клъстери . За да се постигне максималната възможна производителност са използвани оптимизационните опции на транслаторите от езиците Fortran и C++ и е отчетена спецификата на комуникациите между процесорите при изпълнението на всяка конкретна програма. Транслираният софтуер е тестван с контролни примери. Пакетите програми са модифицирани и пригодени за работа и инсталирани на суперкомпютърния комплекс от д-р. Валентин Павлов, д-р. Пейчо Петков и ст.н.с.Iст. д.т.н.Стоян Марков.

До края на март 2010 техните устойчиви версии ( така наречените индустриални среди) ще бъдат включени в библиотеката “Приложно програмно осигуряване” заедно с User’s Manuel.

Към средата на юни ще бъдат добавени подробни ръководства за тяхното използване от потребители, които не са фамилиарни с разделите от физиката, квантовата химия, методите за решаване на задачи с много големи размери, био информатиката, молекулярната динамика, динамиката на флуидите, теорията на микро флуидните течения, аеродинамиката, геофизиката и други научни области, както и с числените методи , които са в основата на тези пакети програми.В ръководствата за потребителите за всеки пакет ще се предложат специфични форми за неговото използване (tips and tricks) и за организиране на комуникациите между процесорите, с цел да се постигне почти тяхното равномерно натоварване ( load balancing), ако използваните алгоритми позволяват това.

Ако искате да използвате работните версии на пакетите приложни програми GROMACS , NAMD , LAMMPS, CP2K, DOCK6, CPMD обърнете се към д-р. Пейчо Петков , E-mail peicho@phys.uni-sofia.bg

Характеристиките са на английски език, за да се избегнат двусмислия и неточности при превода.

1. 
   Молекулярна динамика и квантова механика
   

53.5Mb

GROMACS is an engine to perform molecular dynamics simulations and energy minimization. These are two of the many techniques that belong to the realm of computational chemistry and molecular modeling. Computational Chemistry is just a name to indicate the use of computational techniques in chemistry, ranging from quantum mechanics of molecules to dynamics of large complex molecular aggregates. Molecular modeling indicates the general process of describing complex chemical systems in terms of a realistic atomic model, with the aim to understand and predict macroscopic properties based on detailed knowledge on an atomic scale. Often molecular modeling is used to design new materials, for which the accurate prediction of physical properties of realistic systems is required

Macroscopic physical properties can be distinguished in (a) static equilibrium properties, such as the binding constant of an inhibitor to an enzyme, the average potential energy of a system, or the radial distribution function in a liquid, and (b) dynamic or non-equilibrium properties, such as the viscosity of a liquid, diffusion processes in membranes, the dynamics of phase changes, reaction kinetics, or the dynamics of defects in crystals. The choice of technique depends on the question asked and on the feasibility of the method to yield reliable results at the present state of the art. Ideally, the (relativistic) time-dependent Schrödinger equation describes the properties of molecular systems with high accuracy, but anything more complex than the equilibrium state of a few atoms cannot be handled at this ab initio level. Thus approximations are necessary; the higher the complexity of a system and the longer the time span of the processes of interest is, the more severe the required approximations are. At a certain point (reached very much earlier than one would wish) the ab initio approach must be augmented or replaced by empirical parameterization of the model used. Where simulations based on physical principles of atomic interactions still fail due to the complexity of the system molecular modeling is based entirely on a similarity analysis of known structural and chemical data. The QSAR methods (Quantitative Structure-Activity Relations) and many homology-based protein structure predictions belong to the latter category.

NAMD 2.7b2

The Theoretical and Computational Biophysics Group at Illinois' Beckman Institute, University of Illinois

32.9 MB

NAMD is a parallel, object-oriented molecular dynamics code designed for high-performance simulation of large biomolecular systems. Simulation preparation and analysis is integrated into the visualization package VMD.

NAMD is developed using Charm++ and benefits from its adaptive communication-computation overlap and dynamic load balancing. We describe some recent optimizations including: pencil decomposition of the Particle Mesh Ewald method, reduction of memory footprint, and topology sensitive load balancing. Unlike most other MD programs, NAMD not only runs on a wide variety of platforms ranging from commodity clusters to supercomputers, but also scales to thousands of processors. NAMD was tested up to 64,000 processors and has several important features:

• Force Field Compatibility

The force field used by NAMD is the same as that used by the programs CHARMM and X-PLOR . This force field includes local interaction terms consisting of bonded interactions between 2, 3, and 4 atoms and pairwise interactions including electrostatic and van der Waals forces. This commonality allows simulations to migrate between these three programs.

• Efficient Full Electrostatics Algorithms

NAMD incorporates the Particle Mesh Ewald (PME) algorithm, which takes the full electrostatic interactions into account. This algorithm reduces the computational complexity of electrostatic force evaluation from O(N²) to O(N logN).

• Multiple Time Stepping

The velocity Verlet integration method is used to advance the positions and velocities of the atoms in time. To further reduce the cost of the evaluation of long-range electrostatic forces, a multiple time step scheme is employed. The local interactions (bonded, van der Waals and electrostatic interactions within a specified distance) are calculated at each time step. The longer range interactions (electrostatic interactions beyond the specified distance) are only computed less often. This amortizes the cost of computing the electrostatic forces over several timesteps. A smooth splitting function is used to separate a quickly varying short-range portion of the electrostatic interaction from a more slowly varying long-range component. It is also possible to employ an intermediate time step for the short-range nonbonded interactions, performing only bonded interactions every time step.

• Dynamics Simulation Options

MD simulations may be carried out using several options, including

– Constant energy dynamics,

– Constant temperature dynamics via

_ Velocity rescaling,

_ Velocity reassignment,

_ Langevin dynamics,

– Periodic boundary conditions,

– Constant pressure dynamics via

_ Berendsen pressure coupling,

_ Nos´e-Hoover Langevin piston,

– Energy minimization,

– Fixed atoms,

– Rigid waters,

– Rigid bonds to hydrogen,

– Harmonic restraints,

– Spherical or cylindrical boundary restraints.

• Load Balancing

An important factor in parallel applications is the equal distribution of computational load among the processors. In parallel molecular simulation, a spatial decomposition that evenly distributes the computational load causes the region of space mapped to each processor to become very irregular, hard to compute and difficult to generalize to the evaluation of many different types of forces. NAMD addresses this problem by using a simple uniform spatial decomposition where the entire model is split into uniform cubes of space called patches.

LAMMPS 05012010(Large scale Atomic/Molecular Massively Parallel Simulator)

Sandia National Laboratories

66.6 MB

LAMMPS is a classical molecular dynamics simulation code designed to run efficiently on parallel computers. It was developed at Sandia National Laboratories, a US Department of Energy facility, with funding from the DOE. In the most general sense, LAMMPS integrates Newton's equations of motion for collections of atoms, molecules, or macroscopic particles that interact via short − or long − range forces with a variety of initial and/or boundary conditions. For computational efficiency LAMMPS uses neighbor lists to keep track of nearby particles. The lists are optimized for systems with particles that are repulsive at short distances, so that the local density of particles never becomes too large. On parallel machines, LAMMPS uses spatial decomposition techniques to partition the simulation domain into small 3d sub domains, one of which is assigned to each processor. Processors communicate and store "ghost" atom information for atoms that border their sub−domain. LAMMPS is most efficient (in a parallel sense) for systems whose particles fill a 3d rectangular box with roughly uniform density.

-bead−spring polymers

-united−atom polymers or organic molecules

-all−atom polymers, organic molecules, proteins, DNA

-metals

-granular materials

-ellipsoidal particles

-point dipolar particles

-hybrid systems

-pairwise potentials: Lennard−Jones, Buckingham, Morse, Yukawa, soft, class 2 (COMPASS), tabulated

-charged pairwise potentials: Coulombic, point − dipole

-many body potentials: EAM, Finnis/Sinclair EAM, modified EAM (MEAM), Stillinger − Weber, Tersoff, AI−REBO

-coarse−grain potentials: granular, DPD, GayBerne, REsquared, colloidal

-bond potentials: harmonic, FENE, Morse, nonlinear, class 2, quadratic (breakable)

-angle potentials: harmonic, CHARMM, cosine, cosine/squared, class 2 (COMPASS)

-dihedral potentials: harmonic, CHARMM, multi − harmonic, helix, class 2 (COMPASS), OPLS

-improper potentials: harmonic, cvff, class 2 (COMPASS)

-hybrid potentials: multiple pair, bond, angle, dihedral, improper potentials can be used in one simulation

-overlaid potentials: superposition of multiple pair potentials

-polymer potentials: all atom, united atom, bead spring, breakable

-water potentials: TIP3P, TIP4P, SPC

-implicit solvent potentials: hydrodynamic lubrication, Debye

-long−range Coulombic’s and dispersion: Ewald, PPPM (similar to particle−mesh Ewald), Ewald/N -for long−range Lennard Jones

-CHARMM, AMBER, OPLS, GROMACS, force field compatibility

-read in atom coordinates from files

-create atoms on one or more lattices (e.g. grain boundaries)

-delete geometric or logical groups of atoms (e.g. voids)

-displace atoms
Ensembles, constraints, and boundary conditions:

-orthogonal or non−orthogonal (triclinic symmetry) simulation domains

-constant NVE, NVT, NPT, NPH integrators

-thermos tatting options for groups and geometric regions of atoms

-pressure control via Nose/Hoover or Berenson barostatting in 1 to 3 dimensions

-simulation box deformation (tensile and shear)

-harmonic (umbrella) constraint forces

-independent or coupled rigid body integration

-SHAKE bond and angle constraints

-walls of various kinds

-targeted molecular dynamics (TMD) and steered molecule dynamics (SMD) constraints

-non−equilibrium molecular dynamics (NEMD)

-variety of additional boundary conditions and constraints
Integrators:

-velocity Verlet integrator

-Brownian dynamics

-energy minimization via conjugate gradient relaxation

-rRESPA hierarchical timestepping

-parallel tempering (replica exchange)

-run multiple independent simulations simultaneously
CPMD 3.13.2 (Car-Parrinello Molecular Dynamics).

Physical Chemistry Institute of the University, Zurich,

Max Planck Institute, Stuttgart and

IBM Research Laboratory, Zurich

14.1 MB
CPMD is ab initio Electronic Structure and Molecular Dynamics Program. The main characteristics of the CPMD code include:

• 
  works with norm conserving or ultrasoft pseudopotentials
  
• 
  LDA, LSD and the most popular gradient correction schemes; free energy density functional implementation
  
• 
  isolated systems and system with periodic boundary conditions; k-points
  
• 
  molecular and crystal symmetry
  
• 
  wavefunction optimization: direct minimization and diagonalization
  
• 
  geometry optimization: local optimization and simulated annealing
  
• 
  molecular dynamics: constant energy, constant temperature and constant pressure
  
• 
  path integral MD
  
• 
  response functions
  
• 
  excited states
  
• 
  many electronic properties
  
• 
  time-dependent DFT (excitations, molecular dynamics in excited states)
  
• 
  coarse-grained non - Markovian metadynamics
  
• 
  - molecular dynamics: NVE, NVT, NPT ensembles.
  
• 
  path integral MD, free-energy path-sampling methods
  
• 
  response functions and many electronic structure properties
  
• 
  time -dependent Density Functional Theory (excitations, molecular dynamics in excited states)
  
• 
  LDA, LSD and many popular gradient correction schemes
  
• 
  isolated systems and system with periodic boundary conditions; k-points
  
• 
  Hybrid quantum mechanical / molecular mechanics calculations (QM/MM)
  

Cp2k BERLIOS Collaboration,

Jülich Forschung Centrum

102 MB
CP2K is a suite of modules, collecting a variety of molecular simulation methods at different levels of accuracy, from ab-initio DFT to classical Hamiltonians, passing through semi-empirical NDDO approximation. It is used routinely for predicting energies, molecular structures, vibrational frequencies of molecular systems, reaction mechanisms, and ideally suited for performing molecular dynamics studies.

CP2K is written in Fortran 95, to perform atomistic and molecular simulations of solid state, liquid, molecular and biological systems.

NWChem

NWChem Version 5.1, as developed and distributed by Pacific Northwest National Laboratory, P. O. Box 999, Richland, Washington 99352 USA

U. S. Department of Energy

1.5 million lines

7. 
   MB
   

WChem is a computational chemistry package that was developed by the High Performance Computational Chemistry Group from the Environmental Molecular Science Laboratory (EMSL) at Pacific Northwest National Laboratory. The program is designed for parallel computer systems including parallel supercomputers and large distributed clusters. It takes advantage of available parallel computing resources and high networking bandwidth. It can perform many molecular calculations including density functional, Hartree-Fock, Müller-Plesset, coupled-cluster, configuration interaction, molecular dynamics including the computation of free energies using a variety of force fields (AMBER, CHARMM) , mixed quantum mechanics, geometry optimizations, vibrational frequencies, static one-electron properties, relativistic corrections (Douglas-Kroll, Dyall-Dirac, spin-orbit), ab-initio molecular dynamics (Carr-Parinello), extended (solid-state) systems DFT and periodic system modeling.

NWChem is scalable, both in its ability to treat large problems efficiently, and in its utilization of available parallel computing resources.

The code uses the parallel programming tools TCGMSG and the Global Array (GA) library developed at PNNL for the High Performance Computing and Communication (HPCC) grand-challenge software program and the Environmental Molecular Sciences Laboratory (EMSL) Project. NWChem has been optimized to perform calculations on large molecules using large parallel computers, and it is unique in this regard. This document is intended as an aid to chemists using the code for their own applications. Users are not expected to have a detailed understanding of the code internals, but some familiarity with the overall structure of the code, how it handles information, and the nature of the algorithms it contains will generally be helpful.

Merck and Co., Inc.

38 MB

Merck Molecular Force Field (MMFF) is a family of force fields developed by Merck Research Laboratories. They are based on the MM3 force field. MMFF is not optimized for a single use (like simulating proteins or small molecules), but tries to perform well for a wide range of organic chemistry calculations. The parameters in the force field have been derived from computational data.

Class I force fields have limited transferability, therefore are only parameterized for a limited number of chemical types and are of limited value for screening large numbers of compounds.

Class II force fields, with their greater transferability, allow for a large number of compounds to be treated, as required for database screening. Inclusion of MMFF in CHARMM greatly facilitates the application of CHARMM in drug design. A Class II force field designed to be a transferable force field for pharmaceutical compounds that accurately treats conformational energetics and nonbonded interactions. This would, ideally, produce a force field that was adequate for both gas phase and condensed phase calculations.

Transferability: Application of empirical force field parameters to molecules not

explicitly included during the parameter optimization.
Application of MMFF in CHARMM

1) Open and read “topology” and parameter files (15 total)

2) Structure input

-Merck format files (*.mrk)

-Mol2 format (Tripos Inc.)

-Single molecules (from SYBYL, see mmff_mol2.inp)

-MOL2 databases (output from DOCK, see mmff_database.inp)

-CHARMM format (see mmff_charmm_input.inp)

-Create “dummy” residue and generate guess coordinates

-RTF mass list must include atom types

-Explicit identification of double and triple bonds

-See top_all22_prot_mmff.inp

-Create solvated system (mmff_solvate.inp)

-Create small molecule-protein interactions(See mmff_prot.inp and mmff_complex.inp)

-MSHIFT

-E14FAC 0.75

DEMOCRITOS National Simulation Center of CNR-INFM (Italian Institute for Condensed Matter Physics)

CINECA National Supercomputing Center in Bologna

43.1 MB

• ground-state energy and one-electron (Kohn-Sham) orbital’s

• atomic forces, stresses, and structural optimization

• molecular dynamics on the ground-state Born-Oppenheimer surface,

also with variable cell

• Nudged Elastic Band (NEB) and Fourier String Method Dynamics

(SMD) for energy barriers and reaction paths

• macroscopic polarization and finite electric fields via the modern theory

of polarization (Berry Phases)
All of the above works for both insulators and metals, in any crystal structure,

for many exchange-correlation functionals (including spin polarization,

DFT+U, exact exchange), for norm-conserving (Hamann-Schluter-Chiang)

pseudopotentials in separable form or Ultrasoft (Vanderbilt) pseudopotentials

or Projector Augmented Waves (PAW) method. Non-collinear magnetism

and spin-orbit interactions are also implemented. Finite electric fields

are implemented also using a supercell approach.
PHonon can perform the following types of calculations:

• phonon frequencies and eigenvectors at a generic wave vector, using

Density-Functional Perturbation Theory

• effective charges and dielectric tensors

• electron -phonon interaction coefficients for metals

• interatomic force constants in real space

• third-order anharmonic phonon lifetimes

• Infrared and Raman (nonresonant) cross section

DFT+U and exact exchange. PAW is not implemented for higher-order

response calculations. Furtrher calculations, in the Quasi-harmonic approximations,

of the vibrational free energy can be performed using the QHA

package.

PostProc can perform the following types of calculations:

• Scanning Tunneling Microscopy (STM) images;

• plots of Electron Localization Functions (ELF);

• Density of States (DOS) and Projected DOS (PDOS);

• Lȍwdin charges;

• planar and spherical averages;

plus interfacing with a number of graphical utilities and with external codes.

Всички пакети за молекулярна динамика и квантова механика плюс

DOCK 6.3

University of California, San Francisco

Pharmaceutical Chemistry Department

68.5 MB
In general, "docking" is the identification of the low-energy binding modes of a small molecule, or ligand, within the active site of a macromolecule, or receptor, whose structure is known. A compound that interacts strongly with, or binds, a receptor associated with a disease may inhibit its function and thus act as a drug. Solving the docking problem computationally requires an accurate representation of the molecular energetics as well as an efficient algorithm to search the potential binding modes.

Historically, the DOCK algorithm addressed rigid body docking using a geometric matching algorithm to superimpose the ligand onto a negative image of the binding pocket. Important features that improved the algorithm's ability to find the lowest-energy binding mode, including force-field based scoring, on-the-fly optimization, an improved matching algorithm for rigid body docking and an algorithm for flexible ligand docking, have been added over the years.
DOCK 6.3 is written in C++ and is functionally separated into independent components, allowing a high degree of program flexibility. Accessory programs are written in Fortran 77.
The new features of DOCK 6.3 include: additional scoring options during minimization; DOCK 3.5 scoring-including Delphi electrostatics, ligand conformational entropy corrections, ligand desolvation, receptor desolvation; Hawkins-Cramer-Truhlar GB/SA solvation scoring with optional salt screening; PB/SA solvation scoring; and AMBER scoring-including receptor flexibility, the full AMBER molecular mechanics scoring function with implicit solvent, conjugate gradient minimization, and molecular dynamics simulation capabilities. Because DOCK 6 is an extension of DOCK 5, it also includes all previous features.

We and others have used DOCK for the following applications:

-predict binding modes of small molecule-protein complexes

-search databases of ligands for compounds that inhibit enzyme activity

-search databases of ligands for compounds that bind a particular protein

-search databases of ligands for compounds that bind nucleic acid targets

-examine possible binding orientations of protein-protein and protein-DNA complexes

-help guide synthetic efforts by examining small molecules that are computationally derivatized and many more...

Hughes Institute, University of Washington.

Общ обем на библиотеките програми, масивите със структури на протеини, базите от данни за конструиране на лиганди и други помощни средства е над 1.9 GB

One of the key challenges in computational biology is prediction of three-dimensional protein structures from amino-acid sequences. It has been known for more than 40 years that the 3D structures of proteins under normal physiological conditions are uniquely determined by the composition of their amino acids, which form a sequence called the primary structure of a protein. However, despite considerable technical advances, the experimental determination of protein structures by nuclear magnetic resonance (NMR) and x-ray diffraction techniques remains slow, expensive, and arduous.

In particular, the rate at which protein structures are being experimentally solved is lagging far behind the explosive rate at which protein sequence information is being gathered by high throughput genome sequencing efforts. Thus, given an amino-acid sequence, a high-throughput methodology to computationally predict protein structures at atomic-level accuracy is one of the long-standing challenges in computational biology.

For most proteins,the ‘‘native state’’ lies at the bottom of a free energy landscape. Protein structure prediction involves varying the degrees of freedom of the protein in a constrained manner until it approaches its native state. In the Rosetta protein structure prediction protocols, a large number of independent folding trajectories are simulated, and several lowest-energy results are likely to be close to the native state. The availability of hundred-teraflop, and shortly, petaflops, computing resources is revolutionizing the approaches available for protein structure prediction.

Rosetta 3 is a library based object-oriented software suite which provides a robust system for predicting and designing protein structures, protein folding mechanisms, and protein-protein interactions. The Rosetta3 codes have been successful in the Critical Assessment of Techniques for Protein Structure Prediction (CASP7) competitions.

The Roseta3 method uses a two-phase Monte Carlo algorithm to sample the extremely large space of possible structures in order to find the most favorable one. The first phase generates a low-resolution model of the protein backbone atoms while approximating the side chains with a single dummy atom. The high-resolution phase then uses a more realistic model of the full protein, along with the corresponding interactions, to find the best candidate for the native structure.

The library contains the various tools that Rosetta uses, such as Atom, ResidueType, Residue, Conformation, Pose, ScoreFunction, ScoreType, and so forth. These components provide the data and services Rosetta uses to carry out its computations.

The major library is named "core", which contains conformational representations of polymer structures, their constituents, the capability to alter the conformations of those structures, and the ability to score those structures with the Rosetta scoring algorithms. It also contains the command-line options system.

The next most important library is "protocol". It contains higher-level classes and unctions needed by Rosetta subprotocols. All the protocols are wrapped by Mover objects, which unifies their interface and integrates them with the job distributor for use on clusters. This Mover interface also allows you to use pre-developed protocols by just calling the corresponding mover, making it easier to create new protocols.

Rosetta Functionality Summary

RosettaAbinitio	Performs de novo protein structure prediction
RosettaDesign	Dentifies low free energy sequences for target protein backbones.
RosettaDesign pymol plugin	A user-friendly interface for submitting Protein Design simulations using Rosetta Design.
RosettaDock	Predicts the structure of a protein-protein complex from the individual structures of the monomer components.
RosettaAntibody	Predicts antibody Fv region structures and performs antibody-antigen docking.
RosettaFragments	Generates fragment libraries for use by Rosetta ab initio in building protein structures.
RosettaNMR	Incorporates NMR data into the basic Rosetta protocol to accelerate the process of NMR structure prediction
RosettaDNA	For the design of proteins that interact with specified DNA sequences.
RosettaRNA	Fragment assembly of RNA.
RosettaLigand	For small molecule - protein docking

C. Сеизмичен анализ

SPECFEM3D - seismic wave propagation

Computational Infrastructure for Geodynamics

California Institute of Technology

University of Pau ( France )

SPECFEM3D Globe 4.0.1 420 MB

SPECFEM3D BASIN V1.4.1 102 MB
Unstructured hexahedral mesh generation is a critical part of the modeling

process in the Spectral-Element Method (SEM). We present some examples

of seismic wave propagation in complex geological models, automatically

meshed on a parallel machine based upon CUBIT (Sandia Laboratory), an advanced 3D unstructured hexahedral mesh generator that offers new opportunities for seismologist to design, assess, and improve the quality of a mesh in terms of both geometrical and numerical accuracy.

The main goal is to provide useful tools for understanding seismic phenomena

dueto surface topography and subsurface structures such as low wave-speed

sedimentary basins.

Spectral-Element Method

-Developed in Computational Fluid

Dynamics (Patera 1984)

- Accuracy of a pseudospectral method, flexibility of a finite-element method

-Extended by Komatitsch and Tromp, Capdeville et al.

-Large curved “spectral” finiteelements with high-degree polynomial interpolation

-Mesh honors the main discontinuities (velocity, density) and topography

-Very efficient on parallel computers, no linear system to invert (diagonal mass matrix)
Collaboration with the oil industry

Dynamic geophysical technique of imaging subsurface geologic structures by generating sound waves at a source and recording the reflected components of this energy at receivers. The Seismic Method is the industry standard for locating subsurface oil and gas accumulations.

• Geometrically flexible

• It is necessary to refine the mesh where the velocity contrast is high

• The mesh has to honor the major interfaces

Technology

Co-located finite volume, arbitrary unstructured meshes, predictor-corrector method.

500 000 lines of code, 49% FORTRAN, 41% C, 10% Python

42.1 MB

Code Saturne is a system designed to solve the Navier-Stokes equations in the cases of 2D, 2D axis symmetric or 3D flows. Its main module is designed for the simulation of flows which may be steady or unsteady, laminar or turbulent, incompressible or potentially dilatable, isothermal or not. Scalars and turbulent fluctuations of scalars can be taken into account. The code includes specific modules, referred to as “specific physics”, for the treatment of lagrangian particle tracking, semi-transparent radioactive transfer, gas, pulverized coal and heavy fuel oil combustion, electricity effects (Joule effect and electric arcs) and compressible flows. The code also includes an engineering module, Matisse, for the simulation of nuclear waste surface storage. Code Saturne relies on a finite volume discretization and allows the use of various mesh types which may be hybrid (containing several kinds of elements) and may have structural non-conformities (hanging nodes).

• Best practice guidelines in specific and critical domain

• Usual real life industrial studies (500 000 to 3 000 000 cells)
Physical modelling

• Laminar and turbulent flows: k-ε, k-ω SST, v2f, RSM, LES

• Radioactive heat transfer (DOM, P-1)

• Combustion coal, fuel, gas (EBU, pdf, LWP)

• Electric arc and Joule effect

• Lagrangian module for dispersed particle tracking

• Compressible flow

• ALE method for deformable meshes

• Conjugate heat transfer (Syrthes & 1D)

• Specific engineering modules for nuclear waste surface storage and cooling towers

• Derived version for atmospheric flows (Mercure_Saturne)

• Derived version for eulerian multiphase flows

• Portability (UNIX and Linux)

• GUI (Python TkTix, Xml format)

• Parallel on distributed memory machines

• Periodic boundaries (parallel, arbitrary interfaces)

• Wide range of unstructured meshes with arbitrary interfaces

• Code coupling capabilities (Code_Saturne/Code_Saturne, Code_Saturne/Code_Aster, ...)

Specific physics capabilities

Stochastic modeling with 2-way coupling (momentum, heat, mass)

Transport & deposit of droplets, ashes, coal, corrosion products, radioactive particles, chemical forces, ...
Gas combustion

EBU, pdf modeling (LWP: mean, variance and covariance of mixing rate & fuel mass fraction).

Combustion turbines (optimization, pollutants…)
Coal combustion

Homogeneous Eulerian approach (granulometric classes, Kobayashi for devolatilisation)

Pulverized coal furnaces (optimization, slagging, pollutants)
Semi-transparent radiative heat transfer

Discrete Ordinate Method and P-1 (L0,qi) model for optically thick media

Coal furnaces, electric arc

Joule effect and electric arc

Electromagnetism and coupling (momentum and heat transfer)

Glass furnace, plasma, electric transformers
Compressible flow

Density, momentum, total energy ⇒electric transformers, turbines

Independent FE solver with tetrahedral mesh and arbitrary fluid-solid interface

Thermal shock, striping, fatigue Fuel combustion, ionic mobility under development.
Structural mechanics code Aster

1.5 million lines

283 MB
Code Aster is a general code directed at the study of the mechanical behaviour of structures. It is widely used at EDF for the expertise and the maintenance of power plants and electrical networks
The main range of application is deformable solids: this explains the great number of functionalities related to mechanical phenomena. However, the study of the behaviour of industrial components requires a prior modelling of the conditions to which they are subjected, or of the physical phenomena which modify their behaviour (internal or external fluids, temperature, metallurgic phase changes, electro-magnetic stresses ...). For these reasons, Code Aster can « link » mechanical phenomena and thermal and acoustic phenomena together. Code Aster also provides a link to external software, and includes a coupled thermo-hydro-mechanics kit.
Even though Code Aster can be used for a number of different structural calculation problems (general purpose code), it has been developed to study the specific problems of components, materials and machines used in the energy production and supply industry. Thus, preference has been given to the modelling of: metallic isotropic structures, geo-materials, reinforced concrete structure components and composite material components
Thermal and mechanical non linear analysis are the main features of Code Aster : simple but effective algorithms have been developed to enable quick processing. Code Aster is mainly a solver for mechanics, based on the theory of the Finite elements. This tool covers a large range of applications : 3D thermal analyses and mechanical analyses in linear and non-linear statics and dynamics, for machines, pressure vessels and civil engineering structures ... Beyond the standard functionalities of a FEM software for solid mechanics, Code_Aster compiles specific research in various fields : fatigue, damage, fracture, contact, geomaterials, porous media, multi-physics couplingNote the creators did not want for the algorithms to function merely as independent “black boxes”. For complex projects, it is necessary to understand the operations conducted by the code so that they can be controlled in the most efficient manner: users should refer to the theoretical manuals of the Reference Manual for information about models and methods.
Code Salome

278 MB

Salome is a generic platform for pre and post processing and code coupling for numerical simulation with the following aims:

• 
  Supports interoperability between CAD modeling and computation software (CAD-CAE link).
  
• 
  Facilitate implementation of coupling between computing codes in a distributed environment Supports interoperability between CAD modeling and computation software (CAD-CAE link).
  
• 
  Makes easier the integration of new components into heterogeneous systems for numerical computation.
  
• 
  Sets the priority to multi-physics coupling between computation software.
  
• 
  Provides a generic user-friendly and efficient user interface, which helps to reduce the costs and delays of carrying out the studies.
  
• 
  Reduces training time to the specific time for learning the software solution based on this platform
  
• 
  Provides access to all functionalities via the integrated Python console.
  
• 
  Pool production of developments (pre and post processors, calculation distribution and supervision) in the field of numerical simulation
  

1.712 GB

Data setting

Code_Aster® computation

Post processing

Geometry +Meshing

Data setting

Code_Saturne® computation

Post processing
PLANETICS platform (Neutronics)

Data setting

Critical boron search procedure

Post processing

The SALOME base platform is composed of the following standard modules:

• 
  Lower layer: embeds core functionalities of the kernel (communication between distributed modules), graphical user interface and management of the studies. These services are handled by the following components:
  

Attached to the lower layer of the architecture, the core functionalities of SALOME are fully defined by the KERNEL module that implements a number of basic services, like:

• 
  Components manager: handles the general services (communication & life cycle) to manage SALOME components. These services correspond to the encapsulation of the CORBA layer in use in SALOME
  
• 
  Study: provides a generic process to manage data shared by the components (creation & persistence)
  

GUI component in SALOME platform provides:

• 
  Common desktop environment (SALOME desktop) for all components
  
• 
  Component integration and management: uploading, switching, component menus/toolbars handling
  
• 
  Study management (creation, saving, loading, editing studies)
  
• 
  Multi-window management in the framework of one study
  
• 
  Management of objects created or imported into the SALOME application (Object Browser)
  
• 
  Integrated Python interpreter
  
• 
  Output messages window
  
• 
  Additional tools : Catalogue Generator, Registry tool
  
• 
  Standard viewers for data visualization:
  
• 
  VTK 3d viewer
  
• 
  OCC 3d viewer
  
• 
  Plot 2d viewer
  
• 
  Supervision viewer
  

This component provides versatile functionalities for creation, visualization and modification of geometric CAD models. 

 Visualization of models in 3D viewers:

• 
  Shading, Wireframe modes
  
• 
  Pre-highlighting (detection)
  
• 
  Selection
  
• 
  Changing the color of a model
  
• 
  Display/Erase a model
  

Import/Export CAD models in the following formats 

Import/Export CAD models in the following formats:

• 
  IGES 5.3
  
• 
  STEP AP203/214 schemas
  
• 
  BREP (Open CASCADE internal format)
  

Creation of basic geometrical objects

• 
  Point
  
• 
  Line
  
• 
  Circle
  
• 
  Ellipse
  
• 
  Arc
  
• 
  Curve
  
• 
  Vector
  
• 
  Plane
  
• 
  Working Plane
  
• 
  Local Coordinate System
  

Modeling operations:

• 
  Extrusion
  
• 
  Revolution
  
• 
  Filling Surface With Edges
  
• 
  Pipe creation
  

• 
  Offset
  
• 
  Basic Sketcher
  

• 
  Creation of topological objects:
  
  • 
    Vertex
    
  • 
    Edge
    
  • 
    Wire
    
  • 
    Face
    
  • 
    Shell
    
  • 
    Solid/CompSolid
    
  • 
    Compound
    
• 
  Explode topological objects
  
• 
  Boolean operations:
  
  • 
    Fuse
    
  • 
    Common
    
  • 
    Cut
    
  • 
    Section
    
• 
  Transformation operations with objects:
  
  • 
    Translation
    
  • 
    Rotation
    
  • 
    Modify the Location
    
  • 
    Mirror Image
    
  • 
    Scaling
    
  • 
    Multi-translation
    
  • 
    Multi-rotation
    
  • 
    Multi-rotation
    
• 
  Advanced partition/gluing algorithm with support of material assignment
  
• 
  Creation of planes using the Archimedean law
  
• 
  Local operations:
  
  • 
    Fillet
    
  • 
    Chamfer
    
• 
  Shape healing functions:
  
  • 
    Sewing
    
  • 
    Change face orientation
    
  • 
    Suppress a hole
    
  • 
    Suppress a face
    
• 
  Topological information and dimensions:
  
  • 
    Basic properties (length, surface area, volume)
    
  • 
    Center of gravity
    
  • 
    Axis of inertia
    
  • 
    Bounding box
    
  • 
    Minimal distance
    
  • 
    Tolerance of the shape
    
  • 
    Validity of the shape
    
  • 
    Topological information
    

The purpose of the MED module is to provide a standard for storing and recovering computer data associated to numerical meshes and fields, and to facilitate the exchange between codes and solvers.

MED also provides structures to hold data on meshes and fields. These structures are exchanged between solvers, hide the communication level (CORBA or MPI), and offer persistence (read/write in .med files).

The main benefit of a common exchange format is reduced complexity of code coupling. It also allows sharing such high level functionalities as computation of nodal connectivity of sub-elements (faces and edges), arithmetic operations on fields, entity location functionalities, and interpolation toolkit.

Mesh Module (SMESH)

The goal of this module is to create meshes on the basis of geometrical models created or imported into GEOM. It uses a set of meshing algorithms and their corresponding conditions (hypotheses) to compute meshes. In addition, a new mesher can be easily connected to this module by using the existing plugin mechanism. The main functionalities of SMESH are:

• 
  Visualization of meshes in 3D viewers:
  
  • 
    Shading, Wireframe
    
  • 
    Shrink
    
  • 
    Nodes
    
  • 
    Special options for mesh (color, lines width, shrink coefficient, transparency)
    
  • 
    Show quadratic elements as lines or arcs of circle
    
  • 
    Display/Erase nodes/elements numbers
    
  • 
    Displaying/Erasing of mesh and submeshes
    
  • 
    Show/hide faces orientation vectors
    
  • 
    Use clipping planes to analyze mesh internal structure
    
• 
  Computation of meshes and submeshes on the basis of the following hypotheses:
  
  • 
    Average length of edges
    
  • 
    Arithmetic 1D
    
  • 
    Automatic Length
    
  • 
    Deflection 1D
    
  • 
    Maximal size of edge
    
  • 
    Number of segments
    
  • 
    Start and End Length
    
  • 
    Maximal triangle area
    
  • 
    Quadrangle parameters
    
  • 
    Maximal tetrahedron volume
    
• 
  Computation of meshes and submeshes using the following algorithms:
  
  • 
    Internal
    
    • 
      Segment around vertex
      
    • 
      Wire discretization
      
    • 
      Projection 1D
      
    • 
      Composite side discretization
      
    • 
      Use existing edges
      
    • 
      Triangulation (Mefisto 2D)
      
    • 
      Quadrangle (mapping)
      
    • 
      Projection 2D
      
    • 
      Use existing faces
      
    • 
      Hexahedron (I,j,k)
      
    • 
      Projection 3D
      
    • 
      3D Extrusion
      
  • 
    External
    
    • 
      BLSURF (with support of Size Map feature)
      
    • 
      Tetrahedron NETGEN 1D-2D / 2D / 1D-2D-3D
      
    • 
      Tetrahedron GHS3D
      
    • 
      Hexotic
      
    • 
      GHS3D Parallel
      
• 
  Group management:
  
  • 
    Creation of groups of elements
    
  • 
    Editing groups
    
  • 
    Deleting groups
    
  • 
    Add/Remove elements from a group
    
  • 
    Boolean operations on groups: Union, Intersect, Cut
    
  • 
    Remove a group
    
  • 
    Display/Erase a group
    
  • 
    Selection of groups
    
  • 
    Selection filter library
    
  • 
    Highlighting of groups
    
• 
  Information about computed meshes
  
• 
  Import meshes:MED, UNV, DAT
  

• 
  Quality controls of meshes:
  
  • 
    Length of edges
    
  • 
    Free boundaries
    
  • 
    Boundaries of multi-connections
    
  • 
    Area
    
  • 
    Taper
    
  • 
    Aspect Ratio 2D & 3D
    
  • 
    Minimum angle
    
  • 
    Warping angle 
    
  • 
    Skew
    
  • 
    Free nodes, free edges, free faces
    
  • 
    Volume
    
• 
  Mesh modifications:
  
  • 
    Add/Remove (node; 0D element, 1D elements: edge, triangle, quadrangle, polygon; 3D elements: tetrahedron, hexahedron, polyhedron; quadratic 1D/2D/3D elements: edge, triangle, quadrangle, tetrahedron, pyramid, pentahedron, hexahedron)
    
  • 
    Diagonal inversion
    
  • 
    Changing orientation
    
  • 
    Conversion of a group of triangles into quadrangles
    
  • 
    Conversion of a group of quadrangles into triangles
    
  • 
    Moving of node
    
  • 
    Union of Triangles
    
  • 
    Smothing
    
  • 
    Revolution
    
  • 
    Extrusion
    
  • 
    Extrusion along Path
    
  • 
    Transformation (Translation, Rotation, Symmetry, Sewing, Merging nodes/elements)
    
  • 
    Pattern Mapping
    
  • 
    Force mesh to pass through predefined point
    
  • 
    Build mesh compoundPost-Pro Module (VISU)
    

Among main functionalities, there are:

• 
  Visualization of presentations in different modes in a 3D viewer:
  
  • 
    Shading
    
  • 
    Wireframe
    
  • 
    Shrink
    
  • 
    Nodes
    
  • 
    Insidewireframe
    
  • 
    Special options for presentation (color, lines width, shrink coefficient)
    
  • 
    Displaying/Erasing of presentations
    
• 
  Visualization of 2D presentations (curves) in 2D viewer:
  
  • 
    Different style of curves
    
  • 
    Different style of curves
    
  • 
    Different scaling modes
    
  • 
    Auto or user defined legend
    
• 
  Import MED files
  
• 
  Import/Export ASCII files of special format for curve representation
  

• 
  Creation of 3D representations of results:
  
  • 
    Scalar map
    
  • 
    Deformed shape
    
  • 
    Deformed Shape and Scalar Map
    
  • 
    Vectors presentation
    
  • 
    Iso surfaces presentation
    
  • 
    Cut planes presentation
    
  • 
    Cut lines presentation
    
  • 
    Stream lines presentation
    
  • 
    Plot 3D Presentation
    
  • 
    Gauss Points presentation
    
  • 
    Different options for presentations listed above
    
• 
  Parallel and successive animation of the presentation along a time scale
  
• 
  Display information about values on cells
  
• 
  Creating/storing special view parameters (angle, zoom factor, etc.)
  

• 
  Creation of 2D data from 3D presentations
  
• 
  Visualization of tables
  
• 
  Creation of curves from tables
  
• 
  Creation of containers of the curves
  

The aim of this module is to graphically define, instantiate and execute a computation process which corresponds to a directed and cycle-free graph (dataflow).

This module is not supported since SALOME version 5.0. In SALOME series 5x it has been replaced by YACS module.

The Supervisor a tool that allows to describe and to control different coupling capabilities between the distributed components, and especially solver modules. A component can be either an existing SALOME module running on its own machine and on its own Operating System (i.e.: distributed component), or a Python component running locally and designed by the user.

Main functionalities of the module are:

• 
  Creation of a dataflow
  
• 
  Import/export of a dataflow into an xml file
  
• 
  Edit a dataflow:
  
  • 
    Add a node into a dataflow
    
  • 
    Remove a node from a dataflow
    
  • 
    Connect nodes in a dataflow
    
  • 
    Change node information
    
• 
  Rename a node Different presentation views of a dataflow
  
  • 
    Control view
    
  • 
    Full view
    
  • 
    Table view
    
• 
  Control the execution of a dataflow:
  
  • 
    Run execution
    
  • 
    Suspend execution
    
  • 
    Kill dataflow execution
    
  • 
    Step-by-step execution