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tools to build dofs map used by inrae.mse
AeroSol library has been developed within CAGIRE and Cardamom (and formerly Bacchus) teams. The aim is to develop a library able to deal with continuous and discontinuous finite elements methods on hybrid and possibly curvilinear meshes, and able to run on heterogeneous architectures. Fitting with the first axis of the Bordeaux Sud-Ouest development strategy, which is to build a coherent software suite scalable and efficient on new architectures, AeroSol library relies on several tools developed in other Inria teams, especially for the management of the parallel aspects.
Record the energy consumption of programs.
HYPRE is a software library of high performance preconditioners and solvers for the solution of large, sparse linear systems of equations. It features multigrid solvers for both structured and unstructured grid problems.
HYPRE is a software library of high performance preconditioners and solvers for the solution of large, sparse linear systems of equations. It features multigrid solvers for both structured and unstructured grid problems.
SuiteSparse is a suite of sparse matrix algorithms, including: UMFPACK, multifrontal LU factorization; CHOLMOD, supernodal Cholesky; SPQR, multifrontal QR; KLU and BTF, sparse LU factorization, well-suited for circuit simulation; ordering methods (AMD, CAMD, COLAMD, and CCOLAMD); CSparse and CXSparse, a concise sparse Cholesky factorization package; and many other packages.
This package contains all of the above-mentioned parts.
HLIBpro is a C++ library implementing H-matrix arithmetic and other algorithms in the context of H-matrices, e.g. geometrical and algebraic clustering, visualisation, BEM discretisation. The focus of the implemention in HLIBpro is on robust algorithms on parallel computers. Here robustness is meant to apply to the algorithms itself as well as on the implementation.
A collection of libraries intended to be widely useful, and usable across a broad spectrum of applications.
HDF5 is a suite that makes possible the management of extremely large and complex data collections.
The GNU Scientific Library is a library for numerical analysis in C and C++. It includes a wide range of mathematical routines, with over 1000 functions in total. Subject areas covered by the library include: differential equations, linear algebra, Fast Fourier Transforms and random numbers.
This package provides Intel's non-free compilers, icc and ifort. You may need to set the INTEL_LICENSE_FILE environment variable to use it.
Consider using GCC or Clang instead.
This package provides Intel's non-free compilers, icc and ifort. You may need to set the INTEL_LICENSE_FILE environment variable to use it.
Consider using GCC or Clang instead.
This package provides Intel's non-free compilers, icc and ifort. You may need to set the INTEL_LICENSE_FILE environment variable to use it.
Consider using GCC or Clang instead.
Medit was developped to visualize numerical simulation results on unstructured meshes in two and three dimensions. Scalar, vector and tensor fields can be easily associated and displayed with meshes.
ParMETIS is an MPI-based parallel library that implements a variety of algorithms for partitioning unstructured graphs, meshes, and for computing fill-reducing orderings of sparse matrices. ParMETIS extends the functionality provided by METIS and includes routines that are especially suited for parallel AMR computations and large scale numerical simulations. The algorithms implemented in ParMETIS are based on the parallel multilevel k-way graph-partitioning, adaptive repartitioning, and parallel multi-constrained partitioning schemes developed in our lab.
ParMETIS is an MPI-based parallel library that implements a variety of algorithms for partitioning unstructured graphs, meshes, and for computing fill-reducing orderings of sparse matrices. ParMETIS extends the functionality provided by METIS and includes routines that are especially suited for parallel AMR computations and large scale numerical simulations. The algorithms implemented in ParMETIS are based on the parallel multilevel k-way graph-partitioning, adaptive repartitioning, and parallel multi-constrained partitioning schemes developed in our lab.
SuperLU_DIST is a parallel extension to the serial SuperLU library. It is targeted for distributed memory parallel machines. SuperLU_DIST is implemented in ANSI C, and MPI for communications.
ParMETIS is an MPI-based parallel library that implements a variety of algorithms for partitioning unstructured graphs, meshes, and for computing fill-reducing orderings of sparse matrices. ParMETIS extends the functionality provided by METIS and includes routines that are especially suited for parallel AMR computations and large scale numerical simulations. The algorithms implemented in ParMETIS are based on the parallel multilevel k-way graph-partitioning, adaptive repartitioning, and parallel multi-constrained partitioning schemes developed in our lab.
ParMETIS is an MPI-based parallel library that implements a variety of algorithms for partitioning unstructured graphs, meshes, and for computing fill-reducing orderings of sparse matrices. ParMETIS extends the functionality provided by METIS and includes routines that are especially suited for parallel AMR computations and large scale numerical simulations. The algorithms implemented in ParMETIS are based on the parallel multilevel k-way graph-partitioning, adaptive repartitioning, and parallel multi-constrained partitioning schemes developed in our lab.
ParMETIS is an MPI-based parallel library that implements a variety of algorithms for partitioning unstructured graphs, meshes, and for computing fill-reducing orderings of sparse matrices. ParMETIS extends the functionality provided by METIS and includes routines that are especially suited for parallel AMR computations and large scale numerical simulations. The algorithms implemented in ParMETIS are based on the parallel multilevel k-way graph-partitioning, adaptive repartitioning, and parallel multi-constrained partitioning schemes developed in our lab.
This CUDA C++ Core Libraries (CCCL) unifies three essential CUDA C++ libraries into a single, convenient repository: Thrust, CUB and libcudacxx. The goal of CCCL is to provide CUDA C++ developers with building blocks that make it easier to write safe and efficient code. Bringing these libraries together streamlines your development process and broadens your ability to leverage the power of CUDA C++.