Showing 3 open source projects for "runtime"

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  • Run applications fast and securely in a fully managed environment Icon
    Run applications fast and securely in a fully managed environment

    Cloud Run is a fully-managed compute platform that lets you run your code in a container directly on top of scalable infrastructure.

    Run frontend and backend services, batch jobs, deploy websites and applications, and queue processing workloads without the need to manage infrastructure.
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  • Cloud based software designed for labor unions Icon
    Cloud based software designed for labor unions

    Union Impact goes above and beyond in improving the way you manage your member information.

    We’re confident you’ll agree that our labor union software is truly the easiest, most efficient, and customizable way to organize all of your union workforce management needs.   In addition to making workflow easier, you’ll find that with our labor union software your organization will become more in tune with your members, contractors, and their surrounding communities.
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  • 1
    GEF

    GEF

    Modern experience for GDB with advanced debugging capabilities

    ...Application developers will also benefit from it, as GEF lifts a great part of regular GDB obscurity, avoiding repeating traditional commands or bringing out the relevant information from the debugging runtime.
    Downloads: 1 This Week
    Last Update:
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  • 2
    Tangent

    Tangent

    Source-to-source debuggable derivatives in pure Python

    Existing libraries implement automatic differentiation by tracing a program's execution (at runtime, like PyTorch) or by staging out a dynamic data-flow graph and then differentiating the graph (ahead-of-time, like TensorFlow). In contrast, Tangent performs ahead-of-time autodiff on the Python source code itself, and produces Python source code as its output. Tangent fills a unique location in the space of machine learning tools.
    Downloads: 1 This Week
    Last Update:
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  • 3
    z-utalm

    z-utalm

    Unified Test and Logging layer for multiple programming languages

    Modern software systems and application are commonly written in multiple languages, include scripting engines, and are frequently build on multiple specialized frameworks and middleware for a considerable diversity of runtime environments. The latest influencing update in development paradigm is the application of multicore processors. This projects is aimed to unify the required trace and logging output and integrate into debugging environments. The target is to provide general development, test, and production support of software environments based on multiple programming languages for distributed multicore environments.
    Downloads: 0 This Week
    Last Update:
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