How to Install and Uninstall libsimde-dev Package on Ubuntu 21.10 (Impish Indri)

Last updated: May 03,2024

1. Install "libsimde-dev" package

Please follow the steps below to install libsimde-dev on Ubuntu 21.10 (Impish Indri)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                libsimde-dev
            
                    
    
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2. Uninstall "libsimde-dev" package

This tutorial shows how to uninstall libsimde-dev on Ubuntu 21.10 (Impish Indri):


    
        
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                sudo apt remove
            
                        
                libsimde-dev
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the libsimde-dev package on Ubuntu 21.10 (Impish Indri)

Package: libsimde-dev
Architecture: all
Version: 0.7.2-4
Multi-Arch: foreign
Priority: optional
Section: universe/libdevel
Source: simde
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Med Packaging Team
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 4258
Filename: pool/universe/s/simde/libsimde-dev_0.7.2-4_all.deb
Size: 258452
MD5sum: 060fdcecf361f7156cc22af380c0f38f
SHA1: 6a7d8535aefb474b0f2a9e485f62538da63badff
SHA256: e6b5d8e772ad4390909fa8d1f4776aca524602d3ec6e14696f755abe4e73118f
SHA512: 0a9f61bd40aac882b3cab5b2375d793a0c273b4f4af8d6c514eb74d93745825a4b2d8164a9872e56a67c7f40aacf0d8e2de476dafd84341443bd303f861ea345
Homepage: https://github.com/simd-everywhere/simde
Description-en: Implementations of SIMD instructions for all systems
SIMDe provides fast, portable implementations of SIMD intrinsics on hardware
which doesn't natively support them, such as calling SSE functions on ARM.
There is no performance penalty if the hardware supports the native
implementation (e.g., SSE/AVX runs at full speed on x86, NEON on ARM, etc.).
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This makes porting code to other architectures much easier in a few key ways:
.
First, instead of forcing you to rewrite everything for each architecture,
SIMDe lets you get a port up and running almost effortlessly. You can then
start working on switching the most performance-critical sections to native
intrinsics, improving performance gradually. SIMDe lets (for example) SSE/AVX
and NEON code exist side-by-side, in the same implementation.
.
Second, SIMDe makes it easier to write code targeting ISA extensions you don't
have convenient access to. You can run NEON code on your x86 machine without an
emulator. Obviously you'll eventually want to test on the actual hardware
you're targeting, but for most development, SIMDe can provide a much easier
path.
.
SIMDe takes a very different approach from most other SIMD abstraction layers
in that it aims to expose the entire functionality of the underlying
instruction set. Instead of limiting functionality to the lowest common
denominator, SIMDe tries to minimize the amount of effort required to port
while still allowing you the space to optimize as needed.
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The current focus is on writing complete portable implementations, though a
large number of functions already have accelerated implementations using one
(or more) of the following:
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SIMD intrinsics from other ISA extensions (e.g., using NEON to implement
SSE).
Compiler-specific vector extensions and built-ins such as
__builtin_shufflevector and __builtin_convertvector
Compiler auto-vectorization hints, using:
OpenMP 4 SIMD
Cilk Plus
GCC loop-specific pragmas
clang pragma loop hint directives
Description-md5: 365b10d48a705f04d00cad192b9ea9f1