vectorized-computation
There are 4 repositories under vectorized-computation topic.
google-research / batch-ppo
Efficient Batched Reinforcement Learning in TensorFlow
Language:Python 967piotte13 / SIMD-Visualiser
A tool to graphically visualize SIMD code
Language:JavaScript 647- Language:Rust 314
awesome-simd / awesome-simd
A curated list of awesome SIMD frameworks, libraries and software
- fastNLfeaLanguage:MATLAB 18
bedbad / justpyplot
Plot in NumPy arrays directly, overlay NumPy plots straight over video real-time, plot in Jupyter without a single loop
Language:Python 8- Language:C++ 6
anilsathyan7 / ConvAcc
Accelerating convolution using numba, cupy and xnor in python
Language:Jupyter Notebook 5kmario23 / PyTorch-Padawan
Exercises, Descriptions, and Visualizations to build intuitions and confidence in working with PyTorch for accelerated Scientific Computing
Language:Jupyter Notebook 5Samxx97 / Fuzzy-Clustering
An Implementation of fuzzy clustering algorithms in Numpy
Language:Python 5codefortheplanet / CSTATplus
Two-point connectivity statistics computation for hydrological patterns
Language:Python 4- Language:C++ 4
mhaseebtariq / doppel-speller
An ML+NLP solution for linking misspelled titles with the true titles
Language:Python 3- Language:Python 3
sugatagh / Implementing-Logistic-Regression-from-Scratch
While it is convenient to use advanced libraries for day-to-day modeling, it does not give insight into the details of what really happens underneath, when we run the codes. In this work, we implement a logistic regression model manually from scratch, without using any advanced library, to understand how it works.
Language:Jupyter Notebook 3ciusji / sql_vectorization_compilation
Collection of experiments to carve out the differences between two types of relational query processing engines: Vectorizing (interpretation based) engines and compiling engines.
Language:C++ 2nopperl / vectorized-image-binarization
Vectorized implementation of the image binarization algorithm of Su et al. (2010)
Language:Python 2prabhupavitra / NumPy-Guide-for-Data-Science
A Hands-On NumPy Tutorial for Data Scientists
Language:Jupyter Notebook 2rashidch / Machine-Learning-with-Andrew-Ng-on-Coursera
This repository shows code of programming tasks which I completed during Machine Learning course on Coursera.
Language:Matlab 2geoye / fast_boltzmann
Fast computation of the Boltzmann Entropy of a numerical or nominal 2-D data array.
Language:Python 1OEmiliatanO / matrix_multiplication_comparison
Matrix multiplication speed comparison
Language:C++ 1ayushsharma-crypto / Bias-Variance-Tradeoff
A python code for demonstration of Bias-Variance TradeOff concept in Machine Learning
Language:Jupyter Notebook 0- mpi-primer
evarga / mpi-primer
This is a teaching material aimed to demonstrate the powerfulness of the SPMD paradigm with MPI.
Language:Python 0 - Language:MATLAB 0
Victor-Martinez-Pozos / Display-Controler-LIBtft144
In this repo I improve the performance of the LIBtft144 controller using numpy and vector operations, and use it to show in real-time the image stream from my raspberry-pi camera on a SPI 144 display
Language:Python 0xkrejc70 / mit-AVS-project1
AVS - Computation Systems Architectures - Project: Sequence code optimization (vectorization)
Language:C++ 0xstupi00 / Artificial-neural-network
Computation Systems Architectures - Project - Sequence code optimization
Language:C++ 0a-poliakov / discords_discovery
Поиск диссонансов временного ряда
Language:C++harmim / vut-avs-labs
Architektury výpočetních systémů - Cvičení
Language:C++Architektury výpočetních systémů - Projekt - Optimalizace sekvenčního kódu
Language:C++Jeffresh / Gradient-descent-feature-scaling
A way to speed up gradient descent is having each feature in the same range.
Language:MATLABpeferragut / image-processing-mc920
For the UNICAMP's discipline of Introduction to Digital Image Processing
Language:Pythontanmayv25 / Machine-Learning-Coursera
This repository includes my solutions to the Machine Learning Assignments offered on coursera.
Language:MATLAB- Language:Jupyter Notebook
tugrul512bit / oofrng
Thomas Wang's random number generation function implicitly parallelized & pipelined at speed of 0.6 cycles per 32bit integer.
Language:C++
