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## Introduction
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The GPU device plugin for Kubernetes supports acceleration using the following Intel GPU hardware families:
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- Intel Xe discrete GPUs, including Xe-LP, Xe-HPG, Xe-HP SDV and XG310
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- Integrated GPUs within Intel Core processors
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- Integrated GPUs within Intel Xeon processors
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- Intel Visual Compute Accelerator (Intel VCA)
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The GPU plugin facilitates offloading the processing of computation intensive workloads to GPU hardware.
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Use cases include:
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Intel GPU plugin facilitates Kubernetes workload offloading by providing access to
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Intel discrete (Xe) and integrated GPU HW device files.
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Use cases include, but are not limited to:
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- Media transcode
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- Media analytics
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- Cloud gaming
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- High performance computing
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- AI training and inference
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For example, Intel oneAPI Video Processing Linbrary can offload video transcoding operations, and OpenCL or oneAPI Level Zero libraries can provide computation acceleration for Intel GPUs.
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The device plugin can also be used with [GVT-d](https://github.com/intel/gvt-linux/wiki/GVTd_Setup_Guide) device
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passthrough and acceleration.
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For example containers with Intel media driver (and components using that), can offload
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video transcoding operations, and containers with the Intel OpenCL / oneAPI Level Zero
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backend libraries can offload compute operations to GPU.
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