Showing 3 open source projects for "network data speed"

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  • Atera all-in-one platform IT management software with AI agents Icon
    Atera all-in-one platform IT management software with AI agents

    Ideal for internal IT departments or managed service providers (MSPs)

    Atera’s AI agents don’t just assist, they act. From detection to resolution, they handle incidents and requests instantly, taking your IT management from automated to autonomous.
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  • Desktop and Mobile Device Management Software Icon
    Desktop and Mobile Device Management Software

    It's a modern take on desktop management that can be scaled as per organizational needs.

    Desktop Central is a unified endpoint management (UEM) solution that helps in managing servers, laptops, desktops, smartphones, and tablets from a central location.
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  • 1
    The Futhark Programming Language

    The Futhark Programming Language

    A data-parallel functional programming language

    ...The language supports regular nested data-parallelism, as well as a form of imperative-style in-place modification of arrays, while still preserving the purity of the language via the use of a uniqueness type system. While the Futhark language and compiler is an ongoing research project, it is quite usable for real programming and can compile nontrivial programs which then run on real machines at high speed.
    Downloads: 0 This Week
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  • 2
    Aeson

    Aeson

    A fast Haskell JSON library

    aeson is a high-performance Haskell library for JSON parsing and encoding, optimized for speed and ease of use. It serves as a foundational tool in the Haskell ecosystem for handling JSON data efficiently. High-performance optimized for real-world workloads. Widely used and well-maintained community library. Compatible with popular frameworks and the Haskell web ecosystem. Easy-to-use API (e.g., FromJSON, ToJSON typeclasses).
    Downloads: 0 This Week
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  • 3
    Hasktorch

    Hasktorch

    Tensors and neural networks in Haskell

    Hasktorch is a powerful Haskell library for tensor computation and neural network modeling, built on top of libtorch (the backend of PyTorch). It brings differentiable programming, automatic differentiation, and efficient tensor operations into Haskell’s strongly typed functional paradigm. This project is in active development, so expect changes to the library API as it evolves. We would like to invite new users to join our Hasktorch discord space for questions and discussions....
    Downloads: 0 This Week
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