How to Install and Uninstall libsimde-dev Package on Kali Linux
Last updated: December 23,2024
1. Install "libsimde-dev" package
Please follow the instructions below to install libsimde-dev on Kali Linux
$
sudo apt update
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$
sudo apt install
libsimde-dev
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2. Uninstall "libsimde-dev" package
This guide covers the steps necessary to uninstall libsimde-dev on Kali Linux:
$
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 Kali Linux
Package: libsimde-dev
Source: simde
Version: 0.7.6-1
Installed-Size: 6648
Maintainer: Debian Med Packaging Team
Architecture: all
Size: 384452
SHA256: 14006273220613866a4a8a6cc703a2473fa4bde6a576a9b9868c7dcb09c8e9f9
SHA1: 62735dff041537ccfe75f1b0e7a7b18a8a756961
MD5sum: 8d436b8ba640f46a46dbcf7e01cc0606
Description: 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.).
.
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.
.
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:
.
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:
Multi-Arch: foreign
Homepage: https://github.com/simd-everywhere/simde
Tag: devel::library, role::devel-lib
Section: libdevel
Priority: optional
Filename: pool/main/s/simde/libsimde-dev_0.7.6-1_all.deb
Source: simde
Version: 0.7.6-1
Installed-Size: 6648
Maintainer: Debian Med Packaging Team
Architecture: all
Size: 384452
SHA256: 14006273220613866a4a8a6cc703a2473fa4bde6a576a9b9868c7dcb09c8e9f9
SHA1: 62735dff041537ccfe75f1b0e7a7b18a8a756961
MD5sum: 8d436b8ba640f46a46dbcf7e01cc0606
Description: 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.).
.
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.
.
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:
.
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:
Multi-Arch: foreign
Homepage: https://github.com/simd-everywhere/simde
Tag: devel::library, role::devel-lib
Section: libdevel
Priority: optional
Filename: pool/main/s/simde/libsimde-dev_0.7.6-1_all.deb