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Parallel and Cloud Computing

Major: Information management systems and technologies
Code of Subject: 7.122.01.M.14
Credits: 5
Department: Automated Control Systems
Lecturer: Associate Professor , PhD Tsymbal Yu.V.
Semester: 2 семестр
Mode of Study: денна
Learning outcomes:
- know actual technologies for parallel and cloud computations, methods and means for their development;
- be able to develop algorithms and programs for parallel computations on graphics processing units, to use opportunities of cloud services.
Required prior and related subjects:
- prerequisite: Algorithmization and Programming
- co-requisites:
Summary of the subject:
Parallel computing on graphics processing units (GPU). Architecture of a modern GPU. CUDA technology. CUDA C program structure. CUDA thread organization. CUDA memories. Performance of computations. Floating-point considerations. Parallel patterns. OpenCL technology. Opportunities for cloud computing. IaaS, PaaS, SaaS models. Migration to a cloud. Virtual machines for cloud infrastructure. Monitoring and management. Cloud applications.
Recommended Books:
- David B. Kirk, Wen-mei W. Hwu. Programming Massively Parallel Processors: A Hands-on Approach, Second Edition. - Morgan Kaufmann, 2012. – 518 p.
- Jason Sanders, Edward Kandrot. CUDA by Example: An Introduction to General-Purpose GPU Programming. - Addison-Wesley, 2010. – 310 p.
- Shane Cook. CUDA Programming: A Developer's Guide to Parallel Computing with GPUs. - Morgan Kaufmann, 2012. – 590 p.
- Rajkumar Buyya, James Broberg, Andrzej M. Goscinski (eds.) Cloud Computing: Principles and Paradigms. – Wiley, 2011. – 675 p.
Assessment methods and criteria:
- Current control (30%): written reports on laboratory works.
- Final control (70%) credit.