Search Results for "fast" - Page 2
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Showing 42 open source projects for "fast"
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Finch.jl
Sparse tensors in Julia and more
Finch is a cutting-edge Julia-to-Julia compiler specially designed for optimizing loop nests over sparse or structured multidimensional arrays. Finch empowers users to write conventional for loops which are transformed behind-the-scenes into fast sparse code. -
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LinearSolve.jl
High-Performance Unified Interface for Linear Solvers in Julia
LinearSolve.jl is a unified interface for the linear solving packages of Julia. It interfaces with other packages of the Julia ecosystem to make it easy to test alternative solver packages and pass small types to control algorithm swapping. It also interfaces with the ModelingToolkit.jl world of symbolic modeling to allow for automatically generating high-performance code. Performance is key: the current methods are made to be highly performant on scalar and statically sized small problems,... -
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FileTrees.jl
Parallel file processing made easy
Easy everyday parallelism with a file tree abstraction. Read a directory structure as a Julia data structure, (lazy-)load the files, apply map and reduce operations on the data while not exceeding available memory if possible. Make up a file tree in memory, create some data to go with each file (in parallel), write the tree to disk (in parallel). FileTrees is a set of tools to lazy-load, process and save file trees. Built-in parallelism allows you to max out all threads and processes that... -
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Tokenize.jl
Tokenization for Julia source code
Tokenize is a Julia package that serves a similar purpose and API as the tokenize module in Python but for Julia. This is to take a string or buffer containing Julia code, perform lexical analysis and return a stream of tokens. -
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LabPlot
Data Visualization and Analysis
LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone. -
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Bayesian Julia
Bayesian Statistics using Julia and Turing
Bayesian statistics is an approach to inferential statistics based on Bayes' theorem, where available knowledge about parameters in a statistical model is updated with the information in observed data. The background knowledge is expressed as a prior distribution and combined with observational data in the form of a likelihood function to determine the posterior distribution. The posterior can also be used for making predictions about future events. Bayesian statistics is a departure from... -
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AbstractFFTs.jl
A Julia framework for implementing FFTs
A general framework for fast Fourier transforms (FFTs) in Julia. This package is mainly not intended to be used directly. Instead, developers of packages that implement FFTs (such as FFTW.jl or FastTransforms.jl) extend the types/functions defined in AbstractFFTs. This allows multiple FFT packages to co-exist with the same underlying fft(x) and plan_fft(x) interface. -
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InteractiveDynamics.jl
Fast, general-purpose interactive applications for complex systems
Fast, general-purpose interactive applications for dynamical systems of all kinds, including ODEs, maps, billiards, and agent-based-models. -
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FLoops.jl
Fast sequential, threaded, and distributed for-loops for Julia
Fast sequential, threaded, and distributed for-loops for Julia, fold for humans.FLoops.jl provides a macro @floop. It can be used to generate a fast generic sequential and parallel iteration over complex collections. Furthermore, the loop written in @floop can be executed with any compatible executors. See FoldsThreads.jl for various thread-based executors that are optimized for different kinds of loops. -
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Augmentor.jl
A fast image augmentation library in Julia for machine learning
A fast library for increasing the number of training images by applying various transformations. Augmentor is a real-time image augmentation library designed to render the process of artificial dataset enlargement more convenient, less error prone, and easier to reproduce. It offers the user the ability to build a stochastic image-processing pipeline (or simply augmentation pipeline) using image operations as building blocks. -
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AugmentedGaussianProcesses.jl
Gaussian Process package based on data augmentation, and sparsity
...It contains a collection of models for different gaussian and non-gaussian likelihoods, which are transformed via data augmentation into conditionally conjugate likelihood allowing for extremely fast inference via block coordinate updates. There are also more options to use more traditional variational inference via quadrature or Monte Carlo integration. -
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NFFT
The official NFFT library repository
NFFT is a software library, written in C, for computing non-equispaced fast Fourier transforms and related variations. -
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RigidBodyDynamics.jl
Julia implementation of various rigid body dynamics
...It aims to be user friendly and performant, but also generic in the sense that the algorithms can be called with inputs of any (suitable) scalar types. This means that if fast numeric dynamics evaluations are required, a user can supply Float64 or Float32 inputs. However, if symbolic quantities are desired for analysis purposes, they can be obtained by calling the algorithms with e.g. SymPy.Sym inputs. If gradients are required, e.g. the ForwardDiff.Dual type, which implements forward-mode automatic differentiation, can be used. -
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ArgCheck.jl
Package for checking function arguments
Package for checking function arguments. @argcheck code is as fast as @assert or a hand written if. That being said it is possible to erase argchecks, much like one can erase bounds checking using @inbounds. This feature is currently experimental. It may be silently changed or removed without increasing the major ArgCheck version number. -
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HMMBase.jl
Hidden Markov Models for Julia
...It will keep being available as a Julia package but we encourage existing and new users to migrate to HiddenMarkovModels.jl which offers a similar interface. For more information see HiddenMarkovModels.jl: when did HMMs get so fast?. HMMBase provides a lightweight and efficient abstraction for hidden Markov models in Julia. Most HMMs libraries only support discrete (e.g. categorical) or Normal distributions. In contrast HMMBase builds upon Distributions.jl to support arbitrary univariate and multivariate distributions. -
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Merlin.jl
Deep Learning for Julia
Merlin is a deep learning framework written in Julia. It aims to provide a fast, flexible and compact deep learning library for machine learning. Merlin is tested against Julia 1.0 on Linux, OS X, and Windows (x64). -
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ParallelAccelerator.jl
ParallelAccelerator package, part of the High Performance Scripting
...With the @acc macro that ParallelAccelerator provides, users may specify parts of a program to accelerate. ParallelAccelerator compiles these parts of the program to fast native code. It automatically eliminates overheads such as array bounds checking when it is safe to do so. It also parallelizes and vectorizes many data-parallel operations. ParallelAccelerator is part of the High Performance Scripting (HPS) project at Intel Labs.
