Showing 5 open source projects for "intel gpu"

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    BoldTrail Real Estate CRM

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  • 1
    Intel Extension for PyTorch

    Intel Extension for PyTorch

    A Python package for extending the official PyTorch

    ...Moreover, Intel® Extension for PyTorch* provides easy GPU acceleration for Intel discrete GPUs through the PyTorch* xpu device.
    Downloads: 0 This Week
    Last Update:
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  • 2
    AWS Deep Learning Containers

    AWS Deep Learning Containers

    A set of Docker images for training and serving models in TensorFlow

    AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR). The AWS DLCs are used in Amazon SageMaker as the default vehicles for your SageMaker jobs such as training, inference, transforms etc. They've been tested for machine learning workloads on Amazon EC2, Amazon ECS and Amazon EKS services as well. ...
    Downloads: 3 This Week
    Last Update:
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  • 3
    PC_Workman_HCK

    PC_Workman_HCK

    AI-powered PC monitoring that explains. Not shows numbers/spikes.

    ...Features: - Time travel monitoring - debug issues from hours ago - AI diagnostics with HCK_GPT - Custom fan curves with profiles - Floating always-on-top widget - 2D system map - Cross-GPU support (NVIDIA/AMD/Intel) Four complete rebuilds. 29 features killed. 24,000 lines of optimized code. No team. Solo Dev. BUILD-IN-PUBLIC Free because good tools should be. Alpha v1.6.3—real tools built on real constraints.
    Downloads: 26 This Week
    Last Update:
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  • 4
    SageMaker MXNet Inference Toolkit

    SageMaker MXNet Inference Toolkit

    Toolkit for allowing inference and serving with MXNet in SageMaker

    ...AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR). The AWS DLCs are used in Amazon SageMaker as the default vehicles for your SageMaker jobs such as training, inference, transforms etc. They've been tested for machine learning workloads on Amazon EC2, Amazon ECS and Amazon EKS services as well.
    Downloads: 0 This Week
    Last Update:
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    eProcurement Software

    Enterprises and companies seeking a solution to manage all their procurement operations and processes

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  • 5
    Intel neon

    Intel neon

    Intel® Nervana™ reference deep learning framework

    ...Designed for ease of use and extensibility. See the new features in our latest release. We want to highlight that neon v2.0.0+ has been optimized for much better performance on CPUs by enabling Intel Math Kernel Library (MKL). The DNN (Deep Neural Networks) component of MKL that is used by neon is provided free of charge and downloaded automatically as part of the neon installation. The gpu backend is selected by default, so the above command is equivalent to if a compatible GPU resource is found on the system. The Intel Math Kernel Library takes advantages of the parallelization and vectorization capabilities of Intel Xeon and Xeon Phi systems. ...
    Downloads: 0 This Week
    Last Update:
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