Educational guide School of Engineering |
english |
Biomedical Data Science (2022) |
Subjects |
HIGH-PERFORMANCE AND DISTRIBUTED COMPUTING FOR BIG DATA |
IDENTIFYING DATA | 2022_23 | |||||||||||||||||
Subject (*) | HIGH-PERFORMANCE AND DISTRIBUTED COMPUTING FOR BIG DATA | Code | 17705110 | |||||||||||||||
Study programme |
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Cycle | 2nd | |||||||||||||||
Descriptors | Credits | Type | Year | Period | ||||||||||||||
6 | Compulsory | First | 2Q |
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Teaching | Modality by working group | Teaching language, timetables and exam dates | ||||||||||||||||
Prerequisites | ||||||||||||||||||
Department | Electronic, Electric and Automatic Engineering Computer Engineering and Mathematics |
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Coordinator |
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miquelangel.senar@urv.cat jordi.vilaplanam@urv.cat santiago.marcos@urv.cat |
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Lecturers |
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Web | ||||||||||||||||||
General description and relevant information |
The course on High-Performance and Distributed Computing for Big Data sets the basics for understanding and using advanced computing infraestructures to solve biomedical problems that use large amounts of data. This course is about the basic tools, programming languages and algorithmic techniques that are needed to develop software solutions that are scalable in parallel and distributed environments. The techniques cover the main algorithm design and analysis ideas for three major classes of machines: multicore and manycore shared memory machines, distributed memory machines like clusters and supercomputers, and cloud environments. Techniques will be illustrated with representative problems from the biomedical field. |
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(*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation. |