Showing 4 open source projects for "gpu hardware"

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    Custom VMs From 1 to 96 vCPUs With 99.95% Uptime

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    Build Agents and Models on One Platform

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  • 1
    NumPy

    NumPy

    The fundamental package for scientific computing with Python

    ...NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries. The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code. NumPy’s high level syntax makes it accessible and productive for programmers from any background or experience level. Distributed under a liberal BSD license, NumPy is developed and maintained publicly on GitHub by a vibrant, responsive, and diverse community. ...
    Downloads: 99 This Week
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  • 2
    NVIDIA Isaac Sim

    NVIDIA Isaac Sim

    NVIDIA Isaac Sim is an open-source application on NVIDIA Omniverse

    NVIDIA Isaac Sim is a high-fidelity robotics simulation platform built on NVIDIA Omniverse to develop, test, and validate AI-driven robots in physically accurate virtual environments. It supports a wide array of robotics formats (URDF, MJCF, CAD), includes GPU-accelerated physics, and features immersive RTX rendering and multisensory simulation. Realistic physics via GPU-accelerated engines and RTX ray tracing. Multi-sensor simulation (RGB-D cameras, Lidar, Radar, IMU, contact sensors)....
    Downloads: 11 This Week
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  • 3
    Microduck RL

    Microduck RL

    RL training environments for Microduck (mjlab)

    ...Its sim-to-real setup models actuator physics, backlash, domain randomization, and reward design. Trained policies can be exported to ONNX and deployed through the separate Microduck runtime. Training normally uses CUDA hardware, while supported workflows can offload jobs to Hugging Face Jobs when a local GPU is unavailable.
    Downloads: 0 This Week
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  • 4

    KEMP

    A FDTD solver for electromagnetic wave simulations on a GPU cluster

    KEMP is a fast FDTD solver on a GPU-based cluster. The FDTD (Finite-Difference Time-Domain) method is a popular numerical method for electromagnetic field simulations. KEMP enables hardware accelerations suitable for multi-GPU, multi-core CPU and GPU cluster. KEMP also provide easy configuration by using Python scripting language.
    Downloads: 0 This Week
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    MongoDB Atlas runs apps anywhere

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