#
avx
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C++ image processing and machine learning library with using of SIMD: SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2, AVX, AVX2, AVX-512, VMX(Altivec) and VSX(Power7), NEON for ARM.
c-plus-plus
machine-learning
arm
neural-network
neon
image-processing
avx
sse
simd
avx2
sse2
sse41
avx512
powerpc
altivec
vsx
ssse3
simd-library
haar-cascade
lbp
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Updated
Nov 26, 2020 - C++
SIMD Vector Classes for C++
c-plus-plus
cpp
portable
neon
cpp14
parallel
parallel-computing
avx
sse
cpp11
simd
cpp17
avx2
simd-programming
vectorization
avx512
simd-instructions
simd-vector
data-parallel
-
Updated
Aug 28, 2020 - C++
Fast, modern C++ DSP framework, FFT, Sample Rate Conversion, FIR/IIR/Biquad Filters (SSE, AVX, AVX-512, ARM NEON)
audio
cplusplus
dft
cxx
travis-ci
dsp
cpp14
intel
avx
clang
simd
header-only
fast-fourier-transform
cpp17
cplusplus-14
fft
digital-signal-processing
avx512
ser
audio-processing
cplusplus-17
discrete-fourier-transform
-
Updated
Oct 20, 2020 - C++
C++ wrappers for SIMD intrinsics and parallelized, optimized mathematical functions (SSE, AVX, NEON, AVX512)
cpp
neon
avx
sse
simd
c-plus-plus-14
vectorization
avx512
mathematical-functions
simd-instructions
simd-intrinsics
-
Updated
Nov 23, 2020 - C++
Performance-optimized wheels for TensorFlow (SSE, AVX, FMA, XLA, MPI)
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Updated
Jul 15, 2019
c
euler
opengl
math
postfix
neon
vector
matrix
bezier
avx
sse
simd
affine-transform-matrices
opengl-math
3d
bounding-boxes
matrix-decompositions
frustum
3d-math
marix-inverse
glm-for-c
-
Updated
Nov 21, 2020 - C
Accelerate SHA256 computations in pure Go using AVX512, SHA256 and AVX2 for Intel and ARM64 for ARM. On AVX512 it provides an up to 8x improvement (over 3 GB/s per core) in comparison to AVX2. On SHA256 speeds up observed at 4x in comparison to AVX2.
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Updated
Sep 18, 2019 - Go
SIMD Library for Evaluating Elementary Functions, vectorized libm and DFT
arm
math
neon
cuda
avx
simd
elementary-functions
sse2
fft
vectorization
math-library
aarch64
avx512
powerpc
vsx
libm
vector-math
s390x
quadruple-precision
sve
-
Updated
Dec 1, 2020 - C
BitMagic Library
c
c-plus-plus
information-retrieval
cmake
algorithm
avx
bit-manipulation
simd
integer-compression
sparse-vectors
sparse-matrix
bit-array
indexing-engine
bit-vector
adjacency-matrix
associative-array
sparse-vector
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Updated
Nov 30, 2020 - C++
Examples of C# code compiled to GPU by hybridizer
visual-studio
compiler
dotnet
gpu
optimization
parallel
cuda
avx
avx2
vectorization
avx512
hybridizer-essentials
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Updated
Sep 5, 2019 - C#
Open Source Architecture Code Analyzer
python
hpc
latency
assembly
avx
x86
throughput
avx2
performance-analysis
avx512
out-of-order
critical-path
port-mapping
performance-modeling
arm64v8
sve
in-core
loop-carried-dependency
-
Updated
Nov 23, 2020 - Assembly
Agenium Scale vectorization library for CPUs and GPUs
neon
cuda
avx
simd
avx2
sse2
simd-programming
aarch64
avx512
simd-instructions
sse42
rocm
sve
neon128
vectorization-library
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Updated
Nov 30, 2020 - Python
guillaumekln
commented
Jul 29, 2020
We should prefix CMake build options with "CT2_", e.g. CT2_WITH_MKL instead of WITH_MKL. This is a good practice to avoid possible conflicts with other projects.
The usage should then be updated in several places:
- README.md
- docker/Dockerfile.*
- python/tools/build_wheel.sh
- .travis.yml
- src/cpu/cpu_isa.h
- src/profiler.cc
python
c
openmp
avx
simd
cosmology
astrophysics
galaxies
large-scale-structure
pair-counting
intrinsics
avx2
avx512
sse42
correlation-functions
-
Updated
Nov 25, 2020 - C
An AVX Lifter for the Hex-Rays Decompiler
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Updated
Jul 22, 2020 - Python
Turbo Base64 - Fastest Base64 SIMD/Neon/Altivec
encoding
benchmark
arm
library
base64
neon
avx
sse
simd
avx2
base64-encoding
base64-decoding
encoding-library
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Updated
Aug 17, 2020 - C
ihhub
commented
Jan 22, 2020
We have Bitmap image saving function void Save( const std::string & path, const penguinV::Image & image, uint32_t startX, uint32_t startY, uint32_t width, uint32_t height ) which locates in src/file/bmp_image.h and src/file/bmp_image.cpp files.
During file saving we purposely copy a line of image to temporary array and then write the array into file. The reason behind this is that
UME::SIMD A library for explicit simd vectorization.
benchmark
cpp
neon
vector
cpp14
avx
cpp11
simd
performance-tuning
cpp17
code-generation
avx2
simd-programming
vectorization
avx512
simd-instructions
altivec
instruction-set-architecture
scalar-types
ume
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Updated
Jan 19, 2018 - C++
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