TensorDock Reviews

NVIDIA virtual graphics (vGPU), software that enables powerful GPU performance, is available for a wide range of workloads from graphics-rich virtual desktops to data science or AI. This allows IT to take advantage of the management and security advantages of virtualization and the performance of NVIDIA's GPUs for modern workloads. NVIDIA's vGPU software, installed on a physical GPU within a cloud server or enterprise data center, creates virtual GPUs which can be shared between multiple virtual machines and accessed from anywhere. Deliver performance that is virtually indistinguishable to a bare-metal environment. Use common data center management software, such as live migration. GPU resources can be allocated with fractional or multiple GPU virtual machine (VMs) instances. Responsiveness to remote teams and changing business requirements.

Launch GPU-accelerated instances that are highly configurable for your AI workload and budget. Reserve thousands of GPUs for training and inference in a next generation AI data center. The AI world is moving to GPU clouds in order to build and launch groundbreaking models without having the hassle of managing infrastructure or scarcity of resources. AI-centric cloud providers are outperforming traditional hyperscalers in terms of availability, compute costs, and scaling GPU utilization for complex AI workloads. Ori has a large pool with different GPU types that are tailored to meet different processing needs. This ensures that a greater concentration of powerful GPUs are readily available to be allocated compared to general purpose clouds. Ori offers more competitive pricing, whether it's for dedicated servers or on-demand instances. Our GPU compute costs are significantly lower than the per-hour and per-use pricing of legacy cloud services.