Main Purpose
The main purpose of the Run:ai website is to provide AI optimization and orchestration solutions for businesses and researchers.
Key Features
- Dev Environment Setup: Run:ai allows users to spin up their development environment with a single command and connect it remotely to their favorite IDE and experiment tracking tools.
- GPU Resource Management: Users can access multiple GPUs or a fraction of a single GPU while keeping their data and code private and secure.
- AI Workload Optimization: Run:ai's scheduler manages tasks in batches using multiple queues on top of Kubernetes, allowing for automated and optimized resource allocation based on business priorities.
- Over-Quota System: The platform's over-quota system enables users to automatically access idle resources based on configurable fairness policies, leading to improved resource utilization.
- Bridge Between HPC and AI: Run:ai's scheduler allows users to easily utilize integer GPUs, multiple-nodes of GPUs, and GPU MIG instances for distributed training on Kubernetes, bridging the efficiency of High-Performance Computing and the simplicity of Kubernetes.
Use Case
- AI Development and Research: Run:ai's solutions are suitable for businesses and researchers involved in AI development and research, providing optimized resource management and workload orchestration.
- Data Science and Machine Learning: The platform can be used by data scientists and machine learning practitioners to efficiently manage their AI workloads and access GPU resources.
- High-Performance Computing: Run:ai's bridge between HPC and AI makes it a valuable tool for industries that require high-performance computing capabilities for their AI workloads.
