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Juice LabsLive Preview

Juice Labs

This flexibility allows organizations to optimize their GPU utilization without the need for code modifications, making it particularly appealing for teams already using popular APIs like CUDA and Vulkan. The performance remains impressive, often matching that of local GPUs when operating within the same data center, which is crucial for demanding AI and graphics workloads. Additionally, the convenience of remote access supports distributed teams, enabling them to leverage powerful GPU resources without being tethered to specific hardware.

Features

  • Dynamic Sharing — Efficiently share a single GPU across multiple workstations or allocate it to CPU-only machines, optimizing resource utilization.
  • No Code Changes — Seamlessly offload GPU processing without modifying existing applications that use CUDA or Vulkan APIs.
  • Performance — Achieve performance levels within 5% of local GPUs when operating in the same data center, ensuring high efficiency for AI and graphics workloads.
  • Convenient Access — Enjoy remote access to GPUs, making it ideal for distributed teams and cloud-based projects.
  • Robust Security Features — Benefit from user authentication, data encryption, and isolation to ensure secure and private GPU access.
  • Comprehensive Audit Trails — Maintain detailed logs of GPU usage for effective monitoring and investigation of any security incidents.
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