Search Results for "source code wireshark" - Page 3

Showing 91 open source projects for "source code wireshark"

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  • 1
    Pkg Julia

    Pkg Julia

    Package manager for the Julia programming language

    Unlike traditional package managers, which install and manage a single global set of packages, Pkg is designed around “environments”: independent sets of packages that can be local to an individual project or shared and selected by name. The exact set of packages and versions in an environment is captured in a manifest file which can be checked into a project repository and tracked in version control, significantly improving reproducibility of projects. If you’ve ever tried to run code you...
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  • 2
    QuantumClifford.jl

    QuantumClifford.jl

    Clifford circuits, graph states, and other quantum Stabilizer tools

    A Julia package for working with quantum stabilizer states and Clifford circuits that act on them. Graphs states are also supported. The package is already very fast for the majority of common operations, but there are still many low-hanging fruits performance-wise. See the detailed suggested readings & references page for background on the various algorithms.
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  • 3
    JUDI.jl

    JUDI.jl

    Julia Devito inversion

    JUDI is a framework for large-scale seismic modeling and inversion and is designed to enable rapid translations of algorithms to fast and efficient code that scales to industry-size 3D problems. The focus of the package lies on seismic modeling as well as PDE-constrained optimization such as full-waveform inversion (FWI) and imaging (LS-RTM). Wave equations in JUDI are solved with Devito, a Python domain-specific language for automated finite-difference (FD) computations. JUDI's modeling...
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  • 4
    101-0250-00

    101-0250-00

    ETH course - Solving PDEs in parallel on GPUs

    This course aims to cover state-of-the-art methods in modern parallel Graphical Processing Unit (GPU) computing, supercomputing and code development with applications to natural sciences and engineering.
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  • 5
    LLVM.jl

    LLVM.jl

    Julia wrapper for the LLVM C API

    A Julia wrapper for the LLVM C API. The LLVM.jl package is a Julia wrapper for the LLVM C API, and can be used to work with the LLVM compiler framework from Julia. You can use the package to work with LLVM code generated by Julia, to interoperate with the Julia compiler, or to create your own compiler. It is heavily used by the different GPU compilers for the Julia programming language.
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  • 6
    JuliaWorkshop

    JuliaWorkshop

    Intensive Julia workshop that takes you from zero to hero

    This is an intensive workshop for the Julia language, composed out of three 2-hour segments. It targets people already familiar with programming, so that the established basics such as for-loops are skipped through quickly and efficiently. Nevertheless, it assumes only rudimentary programming familiarity and does explain concepts that go beyond the basics. The goal of the workshop is to take you from zero to hero (regarding Julia): even if you know nothing about Julia, by the end you should...
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  • 7
    NCDatasets.jl

    NCDatasets.jl

    Load and create NetCDF files in Julia

    NCDatasets allows one to read and create netCDF files. NetCDF data set and attribute list behave like Julia dictionaries and variables like Julia arrays. This package implements the CommonDataModel.jl interface, which means that the datasets can be accessed in the same way as GRIB files opened with GRIBDatasets.jl.
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  • 8
    DynamicHMC

    DynamicHMC

    Implementation of robust dynamic Hamiltonian Monte Carlo methods

    Implementation of robust dynamic Hamiltonian Monte Carlo methods in Julia. In contrast to frameworks that utilize a directed acyclic graph to build a posterior for a Bayesian model from small components, this package requires that you code a log-density function of the posterior in Julia. Derivatives can be provided manually, or using automatic differentiation. Consequently, this package requires that the user is comfortable with the basics of the theory of Bayesian inference, to the extent...
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  • 9
    PGFPlotsX.jl

    PGFPlotsX.jl

    Plots in Julia using the PGFPlots LaTeX package

    PGFPlotsX is a Julia package to generate publication quality figures using the LaTeX library PGFPlots. It is similar in spirit to the package PGFPlots.jl but it tries to have a very close mapping to the PGFPlots API as well as minimize the number of dependencies. The fact that the syntax is similar to the TeX version means that examples from Stack Overflow and the PGFPlots manual can easily be incorporated in the Julia code.
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  • 10
    Manifolds.jl

    Manifolds.jl

    Manifolds.jl provides a library of manifolds

    ... on that interface can be used within your code.
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  • 11
    Enzyme.jl

    Enzyme.jl

    Julia bindings for the Enzyme automatic differentiator

    This is a package containing the Julia bindings for Enzyme. This is very much a work in progress and bug reports/discussion is greatly appreciated. Enzyme is a plugin that performs automatic differentiation (AD) of statically analyzable LLVM. It is highly-efficient and its ability perform AD on optimized code allows Enzyme to meet or exceed the performance of state-of-the-art AD tools.
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  • 12
    SymbolicUtils.jl

    SymbolicUtils.jl

    Symbolic expressions, rewriting and simplification

    SymbolicUtils is a practical symbolic programming utility in Julia. It lets you create, rewrite and simplify symbolic expressions, and generate Julia code from them. SymbolicUtils.jl provides various utilities for symbolic computing. SymbolicUtils.jl is what one would use to build a Computer Algebra System (CAS). If you're looking for a complete CAS, similar to SymPy or Mathematica, see Symbolics.jl. If you want to build a crazy CAS for your weird Octonian algebras, you've come to the right...
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  • 13
    QuantumOptics.jl

    QuantumOptics.jl

    Library for the numerical simulation of closed as well as open quantum

    ..., not on the numerics. Every function in the framework has been severely tested with all tests and their code coverage presented on the framework's GitHub page.
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  • 14
    Bayesian Julia

    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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  • 15
    Wflow.jl

    Wflow.jl

    Hydrological modeling

    Wflow is Deltares’ solution for modeling hydrological processes, allowing users to account for precipitation, interception, snow accumulation and melt, evapotranspiration, soil water, surface water and groundwater recharge in a fully distributed environment. Successfully applied worldwide for analyzing flood hazards, drought, climate change impacts and land use changes, wflow is growing to be a leader in hydrology solutions. Wflow is conceived as a framework, within which multiple...
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  • 16
    Reduce.jl

    Reduce.jl

    Symbolic parser for Julia language term rewriting using REDUCE algebra

    ... including Run-REDUCE, TeXmacs and GNU Emacs. REDUCE (and its complete source code) is available free of charge for most common computing systems, in some cases in more than one version for the same machine. The manual and other support documents and tutorials are also included in the distributions.
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  • 17
    CliMA Land

    CliMA Land

    Everything within the Land model

    ... and examples for users, rather than a place to store the code for all sub-modules. This project is supposed to be a community effort, leveraging all the work that has been done in Land Surface Modeling from various groups around the world. The ultimate goal is to build a bio-physical model that represents the state of the art and can be coupled to the CliMA Earth System Model (ESM), i.e. Caltech's CliMA initiative.
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  • 18
    LossFunctions.jl

    LossFunctions.jl

    Julia package of loss functions for machine learning

    This package represents a community effort to centralize the definition and implementation of loss functions in Julia. As such, it is a part of the JuliaML ecosystem. The sole purpose of this package is to provide an efficient and extensible implementation of various loss functions used throughout Machine Learning (ML). It is thus intended to serve as a special purpose back-end for other ML libraries that require losses to accomplish their tasks. To that end we provide a considerable amount...
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  • 19
    LinearSolve.jl

    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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  • 20
    jlrs

    jlrs

    Julia bindings for Rust

    jlrs is a crate that provides access to most of the Julia C API, it can be used to embed Julia in Rust applications and to use functionality it provides when writing ccallable functions in Rust. Currently, this crate is only tested in combination with Julia 1.6 and 1.9, but also supports Julia 1.7, 1.8, and 1.10. Using the current stable version is highly recommended. The minimum supported Rust version is currently 1.65. Julia must be installed before jlrs can be used, jlrs is compatible...
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  • 21
    OrdinaryDiffEq.jl

    OrdinaryDiffEq.jl

    High performance ordinary differential equation (ODE)

    ... for high-precision and HPC applications. At the same time, it wraps the classic C/Fortran methods, making it easy to switch over to them whenever necessary. Solving differential equations with different methods from different languages and packages can be done by changing one line of code, allowing for easy benchmarking to ensure you are using the fastest method possible.
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  • 22
    Gridap.jl

    Gridap.jl

    Grid-based approximation of partial differential equations in Julia

    Gridap provides a set of tools for the grid-based approximation of partial differential equations (PDEs) written in the Julia programming language. The library currently supports linear and nonlinear PDE systems for scalar and vector fields, single and multi-field problems, conforming and nonconforming finite element (FE) discretizations, on structured and unstructured meshes of simplices and n-cubes. It also provides methods for time integration. Gridap is extensible and modular. One can...
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  • 23
    CUDA.jl

    CUDA.jl

    CUDA programming in Julia

    High-performance GPU programming in a high-level language. JuliaGPU is a GitHub organization created to unify the many packages for programming GPUs in Julia. With its high-level syntax and flexible compiler, Julia is well-positioned to productively program hardware accelerators like GPUs without sacrificing performance. The latest development version of CUDA.jl requires Julia 1.8 or higher. If you are using an older version of Julia, you need to use a previous version of CUDA.jl. This will...
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  • 24
    InteractiveCodeSearch.jl

    InteractiveCodeSearch.jl

    Interactively search Julia code from terminal

    Julia has @edit, @less, etc. which are very handy for reading the implementation of functions. However, you need to specify a "good enough" set of (type) parameters for them to find the location of the code.
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  • 25
    PDFIO.jl

    PDFIO.jl

    PDF Reader Library for Native Julia.

    ... a new PDF file there is a possibility that it may not work to the best interpretation of the specification. A script-based language makes it easier for the consumers to quickly modify the code and enhance to their specific needs.
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