Juice

What is Juice?

​Juice Labs is a pioneering software platform that enables GPU-over-IP technology, allowing organizations to virtualize, share, and dynamically allocate GPU resources across networks without the need for additional hardware or complex orchestration tools like Kubernetes. By transforming GPUs into network-attached resources, Juice Labs facilitates efficient utilization of existing GPU infrastructure, catering to the growing demands of AI, graphics, and high-performance computing workloads.

Juice Features:

• Software-Only Deployment: Its installs on existing GPU systems and networks, both on-premises and in the cloud, without requiring additional hardware. ​
• Application Transparency: Applications remain unaware of the remote nature of the GPU, allowing for seamless integration without code changes. ​
• GPU Fractionalization: Its enables splitting and sharing of GPU resources on-the-fly, without the need for resets, unlike traditional vGPU or MIG solutions.
• Cross-Cloud GPU Routing: The platform can route GPU capacity from areas of abundance to areas of scarcity, even across different cloud providers. ​
• High Utilization Rates: By dynamically allocating GPU resources, Juice helps achieve near 100% GPU utilization, maximizing the return on investment.

Juice Benefits:

• Cost Efficiency: By optimizing GPU utilization and eliminating the need for additional hardware or complex orchestration tools, its reduces operational costs. ​
• Scalability: Organizations can scale their GPU resources dynamically to meet varying workload demands without significant infrastructure changes. ​
• Flexibility: Its supports a wide range of deployment scenarios, including on-premises, cloud, and hybrid environments, providing adaptability to different organizational needs.
• Simplified Management: The platform’s software-only approach and elimination of Kubernetes simplify the management and orchestration of GPU resources.

Use Cases:

• Enterprise AI Workloads: Organizations can efficiently run AI and machine learning workloads by dynamically allocating GPU resources where needed. ​
• High-Performance Computing (HPC): Research institutions and universities can leverage Juice for dynamic GPU scheduling and pooling in superclusters. ​
• Cloud Service Providers: Cloud providers can optimize their GPU infrastructure by routing capacity across data centers to balance supply and demand. ​
• Media and Entertainment: Studios can utilize Juice to provide artists and developers with access to powerful GPU resources without the need for local hardware.