Juice Remote GPU

Juice Remote GPU

Enabling AI and Graphics workloads on remote GPUs

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Juice Remote GPU is a software that enables AI and Graphics workloads on remote GPUs. It allows users to offload GPU processing for any CUDA or Vulkan application to a remote host running the Juice agent. The software injects CUDA and Vulkan implementations during runtime, eliminating the need for code changes in the application. Juice supports multiple clients connecting to multiple GPUs and multiple clients sharing a single GPU. It is useful for sharing a single GPU across multiple workstations, allocating GPUs dynamically to CPU-only machines, and simplifying development workflows and deployments. Juice Remote GPU performs within 5% of a local GPU when running in the same datacenter. It supports various APIs, including CUDA, Vulkan, DirectX, and OpenGL, and is compatible with PyTorch and TensorFlow. The team behind Juice Remote GPU consists of engineers from Meta, Intel, and the gaming industry.

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Features

Advantages

  • Share a single GPU across multiple workstations
  • Allocate GPUs dynamically to CPU-only machines
  • Simplify development workflows and deployments
  • Support for various APIs, including CUDA, Vulkan, DirectX, and OpenGL
  • Compatibility with PyTorch and TensorFlow

Disadvantages

  • May require a stable and fast network connection for optimal performance
  • Limited to CUDA and Vulkan applications
  • May not be suitable for applications that require real-time GPU processing

Frequently Asked Questions

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