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Weronika Filinger,
David Henty,
Emmanouil (Manos) Farsarakis,
Zheng Meyer-Zhao,
Jane Kennedy,
Bryan Johnston,
and
Ann B
Topics Covered
- Supercomputers: introducing supercomputing terminology and some of the largest machines in the world
- Parallel computers: how they are built from hundreds of thousands of CPUs, each similar to those in a desktop PC
- Parallel computing: using parallel processing to harness the power of all of those CPUs for a single calculation
- Computer simulation: how we can perform virtual experiments to make real-life predictions
- Case studies: how supercomputing is making scientific breakthroughs that were never possible before
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Reading list
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Provides a comprehensive introduction to high-performance computing (HPC) for scientists and engineers. It covers the basics of HPC, including parallel programming, load balancing, and performance optimization. The book also discusses the use of HPC in a variety of scientific and engineering applications.
Provides a comprehensive overview of high performance computing, from its architecture to its applications. It covers the basics of HPC, as well as the latest advances in the field. The book is written by three leading experts in the field.
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Provides a comprehensive introduction to parallel computing. It covers the basics of parallel programming, as well as the latest advances in the field. The book is written by a leading expert in the field.
Provides a comprehensive overview of algorithms and parallel computing. It covers the basics of algorithms and parallel computing, as well as the latest advances in the field.
Provides a comprehensive overview of high performance computing in science and engineering. It covers the basics of high performance computing, as well as the latest advances in the field.
Provides a comprehensive overview of parallel computing, covering topics such as parallel programming models, algorithms, and architectures. It is written by a team of experts in the field and is suitable for both undergraduate and graduate students.
Provides a comprehensive overview of parallel programming with MPI, covering topics such as parallel programming models, algorithms, and performance optimization. It is written by an expert in the field and is suitable for both programmers and researchers.
Provides an overview of parallel algorithms for machine learning, covering topics such as linear algebra, optimization, and deep learning. It is written by a team of experts in the field and is suitable for both researchers and practitioners.
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Provides a comprehensive overview of parallel computing, covering topics such as parallel architectures, algorithms, and applications. It is written by an expert in the field and is suitable for both undergraduate and graduate students.
Provides an introduction to high-performance computing for computational science, covering topics such as parallel programming, performance optimization, and scientific computing libraries. It is written by a team of experts in the field and is suitable for researchers and practitioners.
Provides a comprehensive overview of parallelism in OpenMP, covering topics such as parallel programming models, algorithms, and performance optimization. It is written by an expert in the field and is suitable for both programmers and researchers.
Provides a practical guide to parallel computing, covering topics such as parallel programming models, algorithms, and performance optimization. It is written by a team of experts in the field and is suitable for both programmers and researchers.
Provides a comprehensive overview of parallel computing for scientific and engineering applications, covering topics such as parallel programming models, algorithms, and performance optimization. It is written by a team of experts in the field and is suitable for both researchers and practitioners.
Provides a comprehensive overview of numerical simulation techniques used in molecular dynamics. It covers topics such as Monte Carlo methods, molecular dynamics simulations, and free energy calculations. It is suitable for both beginners and advanced users.
Provides a comprehensive overview of computer simulation in science and engineering. It covers topics such as numerical methods, optimization techniques, and simulation applications. It is suitable for both beginners and advanced users.
Provides a comprehensive overview of mathematical modeling and simulation. It covers topics such as differential equations, numerical methods, and simulation techniques. It is suitable for both beginners and advanced users.
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Provides a comprehensive overview of simulation modeling and analysis. It covers topics such as simulation languages, statistical analysis, and optimization. It is suitable for both beginners and advanced users.
Provides a comprehensive overview of simulation using Arena software. It covers topics such as model building, simulation techniques, and data analysis. It is suitable for both beginners and advanced users.
Provides a comprehensive overview of advanced computer simulation approaches for studying complex systems. It covers topics such as multi-scale modeling, agent-based modeling, and machine learning. It is suitable for both beginners and advanced users.
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Time
15 hours
Via
FutureLearn
Institutions
The University of Edinburgh
Partnership for Advanced Computing in Europe (PRACE)
SURFsara
Instructors
Weronika Filinger
David Henty
Emmanouil (Manos) Farsarakis
Zheng Meyer-Zhao
Jane Kennedy
Bryan Johnston
Ann B
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