Acquire techniques in parallel and distributed programming, and the knowledge of modern hardware and software architectures for high-performance scientific computing. Learn distributed iterative methods for simulating numerical problems. Acquire the knowledge of the newly developed languages for dynamic programming in scientific computing, such as the Julia language.
Curriculum
teacher profile teaching materials
2. [Learning Julia](https://www.manning.com/books/julia-in-action)
3. Blaise N. Barney, [HPC Training Materials](https://computing.llnl.gov/tutorials/parallel_comp/), per gentile concessione del Lawrence Livermore National Laboratory's Computational Training Center
4. J. Dongarra, J. Kurzak, J. Demmel, M. Heroux, [Linear Algebra Libraries for High- Performance Computing: Scientific Computing with Multicore and Accelerators](http://www.netlib.org/utk/people/JackDongarra/SLIDES/sc2011-tutorial.pdf), SuperComputing 2011 (SC11)
Fruizione: 20810157 CALCOLO PARALLELO E DISTRIBUITO in Ingegneria informatica LM-32 PAOLUZZI ALBERTO
Programme
Short introduction to Julia for scientific programming. Introduction to parallel aechitectures. Designi principles of parallel algorithms. Prallel and distributed programming with Julia. Comunication and sincronization primitives: MPI paradigm. Directive-based languages: OpenMP. Performance metrics of parallel programs. Matrix operations and dense linear systems: mentions to BLAS, LAPACK, scaLAPACK. Sparse linear systems. Mentions to CombBLAS and GraphBLAS.Core Documentation
1. [Lecture slides and diary](https://github.com/cvdlab-courses/pdc/blob/master/schedule.md)2. [Learning Julia](https://www.manning.com/books/julia-in-action)
3. Blaise N. Barney, [HPC Training Materials](https://computing.llnl.gov/tutorials/parallel_comp/), per gentile concessione del Lawrence Livermore National Laboratory's Computational Training Center
4. J. Dongarra, J. Kurzak, J. Demmel, M. Heroux, [Linear Algebra Libraries for High- Performance Computing: Scientific Computing with Multicore and Accelerators](http://www.netlib.org/utk/people/JackDongarra/SLIDES/sc2011-tutorial.pdf), SuperComputing 2011 (SC11)
Type of delivery of the course
LecturesType of evaluation
Project evaluation teacher profile teaching materials
2. [Learning Julia](https://www.manning.com/books/julia-in-action)
3. Blaise N. Barney, [HPC Training Materials](https://computing.llnl.gov/tutorials/parallel_comp/), per gentile concessione del Lawrence Livermore National Laboratory's Computational Training Center
4. J. Dongarra, J. Kurzak, J. Demmel, M. Heroux, [Linear Algebra Libraries for High- Performance Computing: Scientific Computing with Multicore and Accelerators](http://www.netlib.org/utk/people/JackDongarra/SLIDES/sc2011-tutorial.pdf), SuperComputing 2011 (SC11)
Fruizione: 20810157 CALCOLO PARALLELO E DISTRIBUITO in Ingegneria informatica LM-32 PAOLUZZI ALBERTO
Programme
Short introduction to Julia for scientific programming. Introduction to parallel aechitectures. Designi principles of parallel algorithms. Prallel and distributed programming with Julia. Comunication and sincronization primitives: MPI paradigm. Directive-based languages: OpenMP. Performance metrics of parallel programs. Matrix operations and dense linear systems: mentions to BLAS, LAPACK, scaLAPACK. Sparse linear systems. Mentions to CombBLAS and GraphBLAS.Core Documentation
1. [Lecture slides and diary](https://github.com/cvdlab-courses/pdc/blob/master/schedule.md)2. [Learning Julia](https://www.manning.com/books/julia-in-action)
3. Blaise N. Barney, [HPC Training Materials](https://computing.llnl.gov/tutorials/parallel_comp/), per gentile concessione del Lawrence Livermore National Laboratory's Computational Training Center
4. J. Dongarra, J. Kurzak, J. Demmel, M. Heroux, [Linear Algebra Libraries for High- Performance Computing: Scientific Computing with Multicore and Accelerators](http://www.netlib.org/utk/people/JackDongarra/SLIDES/sc2011-tutorial.pdf), SuperComputing 2011 (SC11)
Type of delivery of the course
LecturesType of evaluation
Project evaluation teacher profile teaching materials
2. [Learning Julia](https://www.manning.com/books/julia-in-action)
3. Blaise N. Barney, [HPC Training Materials](https://computing.llnl.gov/tutorials/parallel_comp/), per gentile concessione del Lawrence Livermore National Laboratory's Computational Training Center
4. J. Dongarra, J. Kurzak, J. Demmel, M. Heroux, [Linear Algebra Libraries for High- Performance Computing: Scientific Computing with Multicore and Accelerators](http://www.netlib.org/utk/people/JackDongarra/SLIDES/sc2011-tutorial.pdf), SuperComputing 2011 (SC11)
Fruizione: 20810157 CALCOLO PARALLELO E DISTRIBUITO in Ingegneria informatica LM-32 PAOLUZZI ALBERTO
Programme
Short introduction to Julia for scientific programming. Introduction to parallel aechitectures. Designi principles of parallel algorithms. Prallel and distributed programming with Julia. Comunication and sincronization primitives: MPI paradigm. Directive-based languages: OpenMP. Performance metrics of parallel programs. Matrix operations and dense linear systems: mentions to BLAS, LAPACK, scaLAPACK. Sparse linear systems. Mentions to CombBLAS and GraphBLAS.Core Documentation
1. [Lecture slides and diary](https://github.com/cvdlab-courses/pdc/blob/master/schedule.md)2. [Learning Julia](https://www.manning.com/books/julia-in-action)
3. Blaise N. Barney, [HPC Training Materials](https://computing.llnl.gov/tutorials/parallel_comp/), per gentile concessione del Lawrence Livermore National Laboratory's Computational Training Center
4. J. Dongarra, J. Kurzak, J. Demmel, M. Heroux, [Linear Algebra Libraries for High- Performance Computing: Scientific Computing with Multicore and Accelerators](http://www.netlib.org/utk/people/JackDongarra/SLIDES/sc2011-tutorial.pdf), SuperComputing 2011 (SC11)
Type of delivery of the course
LecturesType of evaluation
Project evaluation