High performance scientific computing with C /
"In this course, you'll learn to develop scientific and numerical programs that solve problems. It's ideal for scientists, engineers, and programmers who need to model mathematical or physical systems. You'll get a core toolkit of algorithms that can be used in a wide variety of...
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Full text (MCPHS users only) |
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Other Authors: | |
Format: | Electronic Video |
Language: | English |
Published: |
[Place of publication not identified] :
Packt,
2018
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Subjects: |
Summary: | "In this course, you'll learn to develop scientific and numerical programs that solve problems. It's ideal for scientists, engineers, and programmers who need to model mathematical or physical systems. You'll get a core toolkit of algorithms that can be used in a wide variety of applications, using the low-level capabilities of the C programming language. The close-to-the-metal approach means you'll learn to optimize our programs to get the absolute best performance that our hardware can provide. You'll see how the design of algorithms affects their performance and accuracy, the tools that can be used to optimize your code and develop your intuition about numerical problems. Finally, you'll examine the growing array of parallel solutions that enable you to take advantage of multi-core CPUs, distributed compute clusters and GPU accelerators. By the end of this course, you'll know how to write fast, accurate code that can run on many different platforms and solve many different scientific problems."--Resource description page |
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Item Description: | Title from title screen (viewed September 20, 2018). Date of publication from resource description page. |
Physical Description: | 1 online resource (1 streaming video file (2 hr., 16 min., 19 sec.)) |
Participant or Performer: | Presenter, Benjamin Keller. |