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Julia High Performance

You're reading from   Julia High Performance Optimizations, distributed computing, multithreading, and GPU programming with Julia 1.0 and beyond

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Product type Paperback
Published in Jun 2019
Publisher Packt
ISBN-13 9781788298117
Length 218 pages
Edition 2nd Edition
Languages
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Author (1):
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Avik Sengupta Avik Sengupta
Author Profile Icon Avik Sengupta
Avik Sengupta
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Toc

Table of Contents (13) Chapters Close

Preface 1. Julia is Fast FREE CHAPTER 2. Analyzing Performance 3. Types, Type Inference, and Stability 4. Making Fast Function Calls 5. Fast Numbers 6. Using Arrays 7. Accelerating Code with the GPU 8. Concurrent Programming with Tasks 9. Threads 10. Distributed Computing with Julia 11. Licences
12. Other Books You May Enjoy

Subnormal numbers

Subnormal numbers (also sometimes called denormal numbers) are very small floating point values, near zero. Formally, they are numbers smaller than those that can be represented without leading zeros in the significand.

Typically, floating point numbers are represented without leading zeros in the significand. Leading zeros in the number are moved to the exponent (that is, 0.0123 is represented as 1.23×10-2). Subnormal numbers are, however numbers in which such a representation would cause the exponent to be lower than the minimum possible value. In such a situation, the significand is forced to have leading zeros.

Subnormal numbers in Julia can be identified by the issubnormal function, as follows:

julia> issubnormal(1.0)
false

julia> issubnormal(1.0e-308)
true

Subnormal numbers are useful for a gradual underflow. Without them, for example, subtraction...

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