Search Results for "cluster management software"
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Showing 49 open source projects for "cluster management software"
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The ARCHModels Package for Julia
A Julia package for estimating ARMA-GARCH models
ARCH (Autoregressive Conditional Heteroskedasticity) models are a class of models designed to capture a feature of financial returns data known as volatility clustering, i.e., the fact that large (in absolute value) returns tend to cluster together, such as during periods of financial turmoil, which then alternate with relatively calmer periods. This package provides efficient routines for simulating, estimating, and testing a variety of GARCH models. ARCH (Autoregressive Conditional... -
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AlphaZero.jl
A generic, simple and fast implementation of Deepmind's AlphaZero
Beyond its much publicized success in attaining superhuman level at games such as Chess and Go, DeepMind's AlphaZero algorithm illustrates a more general methodology of combining learning and search to explore large combinatorial spaces effectively. We believe that this methodology can have exciting applications in many different research areas. Because AlphaZero is resource-hungry, successful open-source implementations (such as Leela Zero) are written in low-level languages (such as C++)... -
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Clapeyron
Framework for the development and use of fluid-thermodynamic models
Welcome to Clapeyron! This module provides both a large library of thermodynamic models and a framework for one to easily implement their own models. Clapeyron provides a framework for the development and use of fluid-thermodynamic models, including SAFT, cubic, activity, multi-parameter, and COSMO-SAC. -
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Oceananigans.jl
Julia software for fast, friendly, flexible fluid dynamics on CPUs
Oceananigans is a fast, friendly, flexible software package for finite volume simulations of the nonhydrostatic and hydrostatic Boussinesq equations on CPUs and GPUs. It runs on GPUs (wow, fast!), though we believe Oceananigans makes the biggest waves with its ultra-flexible user interface that makes simple simulations easy, and complex, creative simulations possible. -
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ModelingToolkitStandardLibrary.jl
A standard library of components to model the world and beyond
The ModelingToolkit Standard Library is a standard library of components to model the world and beyond. -
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InvertibleNetworks.jl
A Julia framework for invertible neural networks
Building blocks for invertible neural networks in the Julia programming language. -
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PETSc.jl
Julia wrappers for the PETSc library
This package provides a low level interface for PETSc and allows combining julia features (such as automatic differentiation) with the PETSc infrastructure and nonlinear solvers. -
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ConcurrentSim.jl
Discrete event process oriented simulation framework written in Julia
A discrete event process-oriented simulation framework written in Julia inspired by the Python library SimPy. One of the longest-lived Julia packages (originally under the name SimJulia). -
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DynamicalSystems.jl
Award winning software library for nonlinear dynamics timeseries
DynamicalSystems.jl is an award-winning Julia software library for nonlinear dynamics and nonlinear time series analysis. To install DynamicalSystems.jl, run import Pkg; Pkg.add("DynamicalSystems"). To learn how to use it and see its contents visit the documentation, which you can either find online or build locally by running the docs/make.jl file. DynamicalSystems.jl is part of JuliaDynamics, an organization dedicated to creating high-quality scientific software. All implemented algorithms... -
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The NLopt module for Julia
Package to call the NLopt nonlinear-optimization library from Julia
This module provides a Julia-language interface to the free/open-source NLopt library for nonlinear optimization. NLopt provides a common interface for many different optimization algorithms. -
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Rocket.jl
Functional reactive programming extensions library for Julia
Rocket.jl is a Julia package for reactive programming using Observables, to make it easier to work with asynchronous data. Rocket.jl has been designed with a focus on performance and modularity. -
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IntervalArithmetic.jl
Library for validated numerics using interval arithmetic
IntervalArithmetic.jl is a Julia package for validated numerics in Julia. All calculations are carried out using interval arithmetic where quantities are treated as intervals. The final result is a rigorous enclosure of the true value. We are working towards having the IntervalArithmetic library be conformant with the IEEE 1788-2015 Standard for Interval Arithmetic. To do so, we have incorporated tests from the ITF1788 test suite. -
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FFTW.jl
Julia bindings to the FFTW library for fast Fourier transforms
This package provides Julia bindings to the FFTW library for fast Fourier transforms (FFTs), as well as functionality useful for signal processing. These functions were formerly a part of Base Julia. Users with a build of Julia based on Intel's Math Kernel Library (MKL) can use MKL for FFTs by setting a preference in their top-level project by either using the FFTW.set_provider!() method, or by directly setting the preference using Preferences.jl. Note that this choice will be recorded for... -
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The Julia Programming Language
High-level, high-performance dynamic language for technical computing
Julia is a fast, open source high-performance dynamic language for technical computing. It can be used for data visualization and plotting, deep learning, machine learning, scientific computing, parallel computing and so much more. Having a high level syntax, Julia is easy to use for programmers of every level and background. Julia has more than 2,800 community-registered packages including various mathematical libraries, data manipulation tools, and packages for general purpose... -
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AppleAccelerate.jl
Julia interface to the macOS Accelerate framework
Julia interface to the macOS Accelerate framework. This provides a Julia interface to some of the macOS Accelerate frameworks. At the moment, this package provides access to Accelerate BLAS and LAPACK using the libblastrampoline framework, an interface to the array-oriented functions, which provide a vectorized form for many common mathematical functions. The performance is significantly better than using standard libm functions in some cases, though there does appear to be some reduced... -
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GDAL.jl
Thin Julia wrapper for GDAL - Geospatial Data Abstraction Library
Julia wrapper for GDAL - Geospatial Data Abstraction Library. This package is a binding to the C API of GDAL/OGR. It provides only a C style usage, where resources must be closed manually, and datasets are pointers. Other packages can build on top of this to provide a more Julian user experience. See for example ArchGDAL.jl. Most users will want to use ArchGDAL.jl instead of using GDAL.jl directly. -
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ReTest.jl
Testing framework for Julia
ReTest is a testing framework for Julia allowing defining tests in source files, whose execution is deferred and triggered on demand. This is useful when one likes to have definitions of methods and corresponding tests close to each other. This is also useful for code that is not (yet) organized as a package, and where one doesn't want to maintain a separate set of files for tests. Filtering run testsets with a Regex, which is matched against the descriptions of testsets. This is useful for... -
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Interpolations.jl
Fast, continuous interpolation of discrete datasets in Julia
This package implements a variety of interpolation schemes for the Julia language. It has the goals of ease of use, broad algorithmic support, and exceptional performance. Currently, this package supports B-splines and irregular grids. The API has been designed with the intent to support more options. Initial support for Lanczos interpolation was recently added. Pull requests are more than welcome! It should be noted that the API may continue to evolve over time. -
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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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MLJBase.jl
Core functionality for the MLJ machine learning framework
Repository for developers that provides core functionality for the MLJ machine learning framework. MLJ is a Julia framework for combining and tuning machine learning models. This repository provides core functionality for MLJ. -
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TerminalUserInterfaces.jl
Terminal User Interfaces in Julia
Create TerminalUserInterfaces in Julia. -
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HTTP.jl
HTTP for Julia
HTTP.jl is a pure Julia implementation of the HTTP protocol, providing tools for building HTTP clients and servers. It enables users to send requests, handle responses, and construct REST APIs or web services entirely in Julia. HTTP.jl supports TLS, cookies, headers, streaming, and middleware, making it suitable for both simple scripting and full-scale web service development. -
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ProbabilisticCircuits.jl
Probabilistic Circuits from the Juice library
This module provides a Julia implementation of Probabilistic Circuits (PCs), tools to learn structure and parameters of PCs from data, and tools to do tractable exact inference with them. Probabilistic Circuits provides a unifying framework for several family of tractable probabilistic models. PCs are represented as computational graphs that define a joint probability distribution as recursive mixtures (sum units) and factorizations (product units) of simpler distributions (input units).... -
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Measurements.jl
Error propagation calculator and library for physical measurements
Error propagation calculator and library for physical measurements. It supports real and complex numbers with uncertainty, arbitrary precision calculations, operations with arrays, and numerical integration. Physical measures are typically reported with an error, a quantification of the uncertainty of the accuracy of the measurement. Whenever you perform mathematical operations involving these quantities you have also to propagate the uncertainty, so that the resulting number will also have... -
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Plots
Powerful convenience for Julia visualizations and data analysis
Data visualization has a complicated history. Plotting software makes trade-offs between features and simplicity, speed and beauty, and a static and dynamic interface. Some packages make a display and never change it, while others make updates in real-time. Plots is a visualization interface and toolset. It sits above other backends, like GR, PythonPlot, PGFPlotsX, or Plotly, connecting commands with implementation. If one backend does not support your desired features or make the right...
