Rescale Teams with NVIDIA to Unite HPC and AI for Optimized Engineering in the Cloud

Companies to Bring NVIDIA AI Enterprise Software to Rescale HPC-as-a-Service Platform, Collaborate on World’s First Compute Recommendation Engine to Accelerate Innovation

Rescale, the leader in high performance computing built for the cloud to accelerate engineering innovation, announced it is teaming with NVIDIA to integrate the NVIDIA AI platform into Rescale’s HPC-as-a-Service offering.

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The integration is designed to advance computational engineering simulation with AI and machine learning, helping enterprises commercialize new product innovations faster, more efficiently and at less cost.

Additionally, Rescale announced the world’s first Compute Recommendation Engine (CRE) to power Intelligent Computing for HPC and AI workloads. Optimizing workload performance can be prohibitively complex as organizations seek to balance decisions among architectures, geographic regions, price points, scalability, service levels, compliance, and sustainability objectives. Developed using machine learning on NVIDIA architectures with infrastructure telemetry, industry benchmarks, and full-stack metadata spanning over 100 million production HPC workloads, Rescale CRE provides customers unprecedented insight to optimize overall performance.

Customers can choose to run workloads the fastest, at the lowest cost, or the right balance between the two alongside a broad set of policy-based enterprise controls.

“We are moving from an era of intuition-driven engineering to AI-assisted engineering, and Rescale Intelligent Computing simplifies the user experience while delivering the best possible performance as computational engineering and AI workloads converge,” said Joris Poort, Rescale founder and CEO. “Our unique built-for-the-cloud approach enables us to deliver optimal accelerated computational performance on-demand for any workload on any cloud worldwide, and our collaboration with NVIDIA will bring powerful new AI capabilities to our industrial HPC customers.”

“Fusing principled and data-driven methods, physics-ML AI models let us explore our design space at speeds and scales many orders of magnitude greater than ever before,” said Jensen Huang, NVIDIA founder and CEO. “Rescale is at the intersection of these major trends. NVIDIA’s accelerated and AI computing platform perfectly complements Rescale to advance industrial scientific computing.”

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Uniting NVIDIA AI and HPC to Accelerate Engineering Leadership

Rescale will be adding the NVIDIA AI Enterprise software suite to enable organizations to leverage the power of HPC and AI on its platform supported on all leading clouds.

Additionally, NVIDIA Modulus, a physics-ML framework, is now available on Rescale with just a few clicks. This allows users to run their entire AI-driven simulation workflow on the Rescale platform, from data preprocessing and model training to inference and model deployment.

Rescale’s software catalog now provides access to hundreds of NVIDIA containerized HPC applications and pretrained AI models on NVIDIA NGC. Rescale is also integrating NVIDIA Base Command Platform software to orchestrate workloads across clouds and on-prem NVIDIA DGX systems.

Compute Recommendation Engine Optimizes Workloads

Today, 78% of organizations have used cloud for computational science and engineering, and R&D organizations that have easy access to computing at scale are up to 60% more likely to achieve their goals on-budget than those that do not, according to the 2022 State of Computational Engineering Report.

Most companies in the aerospace and automotive verticals already use computational engineering to perform broad design space exploration to develop future product designs. Rescale’s Intelligent Computing fabric, powered by the Compute Recommendation Engine, automatically and optimally runs computational engineering and AI workloads anywhere in Rescale’s global multi-cloud infrastructure, accelerated by NVIDIA computing and software. This timely development facilitates the increasing use of AI-driven approaches in computational science and engineering methods.

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