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== HCL software for heterogeneous computing == | == HCL software for heterogeneous computing == | ||
* Extensions for [[MPI]]: [http://hcl.ucd.ie/project/mpC mpC] [http://hcl.ucd.ie/project/HeteroMPI HeteroMPI] [http://hcl.ucd.ie/project/libELC libELC] | * Extensions for [[MPI]]: [http://hcl.ucd.ie/project/mpC mpC] [http://hcl.ucd.ie/project/HeteroMPI HeteroMPI] [http://hcl.ucd.ie/project/libELC libELC] | ||
− | * Extensions for [ | + | * Extensions for [http://en.wikipedia.org/wiki/GridRPC GridRPC]: [http://hcl.ucd.ie/project/SmartGridSolve SmartGridSolve] [http://hcl.ucd.ie/project/NI-Connect NI-Connect] |
* Computation benchmarking, modeling, dynamic load balancing: [http://hcl.ucd.ie/project/fupermod FuPerMod] [http://hcl.ucd.ie/project/pmm PMM] | * Computation benchmarking, modeling, dynamic load balancing: [http://hcl.ucd.ie/project/fupermod FuPerMod] [http://hcl.ucd.ie/project/pmm PMM] | ||
* Communication benchmarking, modeling, optimization: [http://hcl.ucd.ie/project/cpm CPM] [http://hcl.ucd.ie/project/mpiblib MPIBlib] | * Communication benchmarking, modeling, optimization: [http://hcl.ucd.ie/project/cpm CPM] [http://hcl.ucd.ie/project/mpiblib MPIBlib] |
Revision as of 12:00, 15 November 2012
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Contents
HCL software for heterogeneous computing
- Extensions for MPI: mpC HeteroMPI libELC
- Extensions for GridRPC: SmartGridSolve NI-Connect
- Computation benchmarking, modeling, dynamic load balancing: FuPerMod PMM
- Communication benchmarking, modeling, optimization: CPM MPIBlib
Heterogeneous mathematical software
Operating systems
Development tools
- C/C++, Python, UML, FORTRAN
- Autotools
- GDB, OProfile, Valgrind
- Doxygen
- ChangeLog, Subversion
- Eclipse
- Bash Scripts
Libraries
- GNU C Library
- MPI
- STL, Boost
- GSL
- BLAS LAPACK ScaLAPACK
- NLOPT
- BitTorrent (B. Cohen's version)
- CUDA SDK
Data processing
Paper & Presentation Tools
Hardware
How to connect to cluster via SSH
How to find information about the hardware
Mathematics
- Confidence interval (Statistics), Student's t-distribution (implemented in GSL)
- Linear regression (implemented in GSL)
- Binomial tree (use Graphviz to visualize trees)
- Spline interpolation, Spline approximation (implemented in GSL)