LAPACK and ScaLAPACK Survey Results - ordered by question

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Question #5. Description of related activities?

Responses
programmer and maintainer of ACESII computational chemistry package
Compact storage for scalapack. Out of core extension for scalapack.
Computational condensed matter physics
Working on density matrix techniques as eigensolver replacements in quantum chemistry. This relies heavily on (sca)lapack.
Electron-impact excitation/ionization of atoms for modelling of fusion diagnostics and experiments. From a computational perspective, it involves the repeated diagonalisation (ie 40-70 times) of symmetric matrices in excess of 50,000 in which ALL eigenvectors and ALL eigenvalues are required. The physics of electron scattering of relativistic targets will drive the size of these matrices upward by at least a factor 5 in coming years. I need efficient I/O and stable diagonalistion. I hope that the next generation of ScaLapack will not be as demanding on memory requirements. Ie. a 40K matrix is the maximum i can diagonalise over 25 opteron processors each with 2 Gb of Ram.
Development of the computational chemistry software NWChem http://www.emsl.pnl.gov/docs/nwchem
I have been working on parallel sparse solvers such as incomplete factorization preconditioners for iterative methods. In such precondtioners I sometimes exploits dense matrix computation to achieve better performance, but the cost of communication is typically more imprtant for the method of interest.
We make limited use of LAPACK in the GYRO code. The dominant matrix structure is sparse, so for that we use UMFPACK.
electronic structure calculation
Reseach on Computational Condensed Matter Physics.
Numical optimization solvers that I develop and distribute target applications nonlinear and semidefinite programming. I use LAPACK to factor dense matrices that are usually the Schur complements of much larger indefinite matrices. Parallel versions of these solvers use ScaLAPACK. Users of our software must also link to these packages.
Computational nuclear theory (static Hartree-Fock, time-dependent Hartree-Fock, Hartree-Fock-Bogoliubov, Dirac equation, ...)
function parameter fitting principle component analysis structural superposition
Condensed matter theory; scientific code developments
quantum chemistry code development (q-chem program)
We are an Electronic Structure Physics group of Northwestern University engaging in the numerical calculations and simulations of materials.
Computational Electromagnetics
quadratic and nonlinear programming
statistical computations
Research on statistical machine learning.
Finite Element methods in CFD. http://www.cimec.org.ar/petscfem
Numerical methods for Atmospheric Dynamics
Time series data analysis; deconvolution
Numerical simulation of reactive flows (CFD and Bifurcation Theory)
Library routine development, User collaborations (consultant work)
Optimization, approximation and cubature, distribution of points on manifolds, mathematical finance
Application of Multiple Precision Numerical Computation
biostatistics bioinformatics
We write code for quantum mechanics, which does repeated generalised eigensolving. Eigenvectors from one iteration are generally good initial guesses to the next, but we can't make any use of this in ScaLAPACK. For large systems our matrices get sparse and so we are looking into using PARPACK or something along those lines for those. Our biggest problem with ScaLAPACK is memory, not speed.
Dense library development
Numerical simulation of fluid flow in oil reservoirs.
PhD-student in wavelet methods, I only use LAPACK for routines that I do not feel like implementing myself. Running time is not really an issue. The large-scale matrix operations are so sparse and specific that I implement them myself.
CAE consultancy shop, with emphasis on CFD.
BEM application developer
I am mostly talking about my experience working with applicaiton groups.
We use ScaLAPACK in a boundary element method application. We also have finite element method applications which use sparse solvers (both iterative and direct) which in turn use BLAS and LAPACK heavily.
Image processing, estimation theory
COndensed matter physics, high-temperature superconductivity
development of software for large-scale numerical optimization, semidefinite programming, sparse and dense
Not sure what you're asking - if you're asking about the nature of the application it's fluid dynamics in the interior of the Sun.
Finite element application
Finite element application
Our goal is to incorporate the lapack routines in our own multi precision environment MPL.
FEM/MOM formulation for electromagnetic code
I work on the development and implementation of multilevel iterative algortihms on various parallel machines. The underlying linear systems are large and sparse, and so LAPACK routines are typically used for various local (serial) computations in a distributed memory environment. Increasingly we are using shared memory nodes within large clusters, however, hybrid memory models have yet to pay off. This may change as OpenMP and other threading capabilities improve.
Use D H Bailey's MP and Yozo's QD - for extra precison.
PDE's in control, boundary control, conservation laws
Sparse linear algebra
CFD Applications
FEM, sparse generalized eigenvalue problems
optimization
Financial industry, statistics, data mining, machine learning.
Computing science in fluid dynamic and heat transfert. Cluster and grid computing. Great use of MPI-2, Atlas, Lapack, Scalapack and Spools from Fortran and C.
Atomic, Molecular and Optical Physics, Computational Chemistry.
I work on the numerical investigation of geophysical fluid instabilities and predictability. I am especially interested the relationship between ensemble forecasting and geophysical fluid instabilities.
Computational Fluid Dynamics, solution of ODEs/PDEs
I use lapack routines to develop aplatations from hte area of signal processing. Esp. I'm interested in recursive filters.
I use lapack routines to develop aplatations from hte area of signal processing. Esp. I'm interested in recursive filters.
Signal processing
Materials modelling ab-initio modelling (density functional theory)
Most of my current work is with sparse matrices coming from finite element discritizations.
Quantum-chemistry. Iterative eigenvalue solves.
Our main CFD code does not use LAPACK. A stand-alone applications of ours does, however.








Tue May 21 09:29:02 2013
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