Juice

Juice Labs offers GPU-over-IP software that unlocks the untapped potential of GPUs within your infrastructure. By utilizing their dynamic sharing and pooling software, you can access any GPU capacity on any network, making all of this "Dark GPU" available for use. This software is easy to install and allows you to maximize the utilization of your GPUs, saving money and increasing productivity.

Key Features:

1. GPU Agility for Enterprises: Juice's enterprise software enables quick installation and makes all of your organization's GPUs network-attached, regardless of their location. With this feature, you can easily share, compose, and access GPUs in ways that were previously not possible.

2. Supercharge Your GPUs: Many organizations invest heavily in GPUs as part of their computing infrastructure; however, these powerful resources are often underutilized with an average deployment rate of only 15%. Juice helps boost GPU utilization so that more compute power is put to work instead of going to waste.

3. GPU Any Place, Any Time: With Juice's simple software installation process, any workload can utilize any GPU over standard network infrastructure without requiring additional hardware. This flexibility allows you to extend the reach of your GPUs beyond traditional boundaries.

Use Cases:

- Utilizing Workstation GPUs: In a hybrid work environment where many desks remain empty or workstations are underutilized even when occupied, Juice enables you to leverage the unused compute power from these machines just as easily as those in server racks.

Conclusion:

Juice Labs' GPU-over-IP software provides a solution for unlocking the full potential of your organization's GPUs by making them network-attached wherever they are located. By maximizing GPU utilization through dynamic sharing and pooling capabilities, organizations can save costs while increasing productivity. Whether it's freeing trapped capacity from workstations or leveraging existing servers more efficiently, Juice empowers businesses to make better use of their valuable computing resources.