High Performance Computing for Scientists and Engineers

High Performance Computing for Scientists and Engineers

@VTU COE

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What you will learn

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Large-scale simulations of engineering and basic science problems require efficient use of modern high performance computing (HPC) infrastructure. This course is primarily aimed to introduce the concepts of high performance computing (HPC) to science and engineering students. Different parallel computing tools like MPI, OpenMP and CUDA will be discussed in connection with domain specific problems. This course will briefly introduce parallel architecture and discuss the performance metrics of HPC programs. Multi-CPU computing using both distributed and shared memory architecture will be discussed and OpenMP and MPI based parallelization of iterative matrix solvers will be discussed. Graphics processing unit (GPU) architecture and concepts of CUDA will be discussed. Matrix calculations using CUDA will be demonstrated.

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Lecture 07: Parallel Algorithms
Preview 48:01
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Lecture 08: Parallel Algorithms (continued)
Preview 31:28
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Lecture 08: Parallel Algorithms (continued)
Preview 31:28
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Lecture 09: Parallel Algorithms (continued)

38:16
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Lecture 10: Performance Metrics of Parallel Systems
Preview 27:25
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Lecture 10: Performance Metrics of Parallel Systems
Preview 27:25
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Lecture 11: Performance Metrics of Parallel Systems (continued)
Preview 38:49
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Lecture 11: Performance Metrics of Parallel Systems (continued)
Preview 38:49

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Lecture 12: Introduction to OpenMP
Preview 34:24
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Lecture 13: Introduction to OpenMP (continued)
Preview 39:06
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Lecture 13: Introduction to OpenMP (continued)
Preview 39:06
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Lecture 14: Introduction to OpenMP (continued
Preview 38:08
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Lecture 15: Essentials of OpenMP Programming
Preview 38:08
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ecture 16: Essentials of OpenMP Programming (continued)
Preview 45:07

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Lecture 17: Data sharing and synchronization
Preview 45:07
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Lecture 18: Efficient OpenMP programming for matrix computing
Preview 52:08
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Lecture 18: Efficient OpenMP programming for matrix computing
Preview 52:08
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Lecture 19: Introduction to MPI and Distributed Memory Parallel Programming
Preview 52:08
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Lecture 20: Introduction to MPI and Distributed Memory Parallel Programming (continued)
Preview 40:58

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Lecture 22: Communication using MPI (continued)
Preview 35:53
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Lecture 22: Communication using MPI (continued)
Preview 35:53
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Lecture 23: Communication using MPI (continued)
Preview 40:02
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Lecture 24: Matrix Representation of Physical Systems - Matrix Solvers
Preview 44:05
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Lecture 25: Domain Decomposition Technique
Preview 33:45

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Lecture 26: Domain decomposition based parallelization of matrix solvers
Preview 42:13
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Lecture 27: Domain decomposition based parallelization of matrix solvers (continued)
Preview 29:24
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Lecture 28: Domain decomposition based parallelization of matrix solvers (continued)
Preview 40:45
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Lecture 29: MPI routines for parallel matrix solvers
Preview 46:15

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Lecture 30: Introduction to GPGPU and CUDA
Preview 32:58
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Lecture 31: Introduction to GPGPU and CUDA (continued)
Preview 34:34
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Lecture 32: Introduction to GPGPU and CUDA (continued)
Preview 24:52
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Lecture 33: Introduction to GPGPU and CUDA (continued)
Preview 29:41
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Lecture 34: Introduction to CUDA programming
Preview 38:17
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Lecture 35: Introduction to CUDA programming (continued)
Preview 40:54

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Lecture 36: Thread execution in CUDA program - scheduling and memory access
Preview 37:31
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Lecture 37: Thread execution in CUDA program (continued)
Preview 40:46
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Lecture 38: Matrix multiplications in CUDA
Preview 33:16
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Lecture 39: OpenACC programming for GPU-s
Preview 40:52
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Lecture 40: Hybrid parallelization and exascale computing
Preview 48:09
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Meet Your Instructor
@VTU COE
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Instructor
3.2 Rating
5446 Students
800 Courses
About Instructor

VTU is one of the largest Technological Universities in India with 24 years of Tradition of excellence in Engineering & Technical Education, Research and Innovations. It came into existence in the year 1998 to cater the needs of Indian industries for trained technical manpower with practical experience and sound theoretical knowledge.

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Free

  • Course Duration
    29 h 45 m 3 s
  • Course Level
    Intermediate
  • Student Enrolled
    0
  • Language
    English
This Course Includes
  • 29 h 45 m 3 s Video Lectures
  • 0 Quizzes
  • 0 Assignments
  • 0 Downloadable Resources
  • Full Lifetime Access
  • Certificate of Completion