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Exxact Partners with Run:ai to Offer Maximal Utilization in GPU Clusters for AI Workloads

Exxact Corporation; a leading provider of high-performance computing (HPC), artificial intelligence (AI), and data center solutions; now offers Run:ai in their solutions. This groundbreaking Kubernetes-based orchestration tool incorporates an AI-dedicated, high-performant super-scheduler tailored for managing GPU resources in AI clusters.

Run:ai dynamically optimizes hardware utilization for AI workloads, enabling clusters to operate at peak efficiency. Hardware is disaggregated into a shared pool where Run:ai’s super-scheduler distributes GPU resources across the team’s jobs. Data scientists can easily leverage massive amounts of GPU computing with confidence. IT can view a centralized and highly transparent UI to monitor resource provisions, job queues, and utilization percentages. During low peak times, Run:ai automatically distributes unused resources to accelerate existing jobs and maximize resource utilization. Thus, AI models can be built faster and trained harder while minimizing wasted resources of idle GPUs.

Run:ai co-founder and CEO Omri Geller says the goal is to enable IT teams to maximize return of investments in expensive GPUs and democratize access to AI compute. By plugging Run:ai software into Kubernetes environments, IT can control and prioritize AI workloads and give AI practitioners simple and scalable ways to run workloads.

“Deep learning is creating whole new industries and transforming old ones,” said Geller. “Now it’s time for computing to adapt to deep learning. Run:ai gives both IT and data scientists what they need to get the most out of their GPUs, so they can innovate and iterate their models faster to produce the advanced AI of the future.”

“By partnering with Run:ai, Exxact can help customers unlock the full potential of their AI cluster performance. By leveraging dynamic GPU orchestration and resource allocation, Run:ai helps developers achieve significant performance efficiency in AI building, training, and inferencing workloads over traditional AI clusters,” said Andrew Nelson, Vice President of Technology at Exxact Corporation.

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