PHILADELPHIA, PA — Server maker xFusion and networking company Cornelis Networks are expanding their partnership with an integrated high-performance computing platform aimed at helping engineering and research organizations manage growing artificial intelligence and simulation workloads.
The joint platform combines xFusion’s FusionServer infrastructure with Cornelis’ CN5000 networking technology to support compute-intensive applications such as computational fluid dynamics, crash simulations, structural analysis and digital twin modeling, the companies said.
The partnership comes as demand for high-performance computing infrastructure rises alongside the adoption of AI-assisted design and increasingly complex modeling applications, placing new pressure on organizations to process larger datasets and shorten development cycles.
“As HPC and AI workloads continue to grow in scale and complexity, organizations need infrastructure that can scale efficiently without introducing bottlenecks,” Cornelis Chief Executive Lisa Spelman said in a statement.
The companies said the combined platform is designed to allow customers to expand computing clusters while maintaining application performance across larger environments.
“Our FusionServer platforms are purpose-built for high-density HPC deployments,” xFusion Europe Chief Executive Frank Qin said. “Together with Cornelis, we are helping customers build infrastructure environments optimized for large-scale modeling, simulation, and other data-intensive workloads.”
The collaboration builds on several years of joint development work between the companies across multiple generations of computing and networking technologies.
The companies also said the platform addresses growing interest in reducing energy consumption in large-scale computing environments. xFusion’s liquid-cooled server designs and Cornelis’ liquid-cooled networking technology are intended to improve thermal efficiency and increase computing density in data center deployments.
The combined offering targets customers running large-scale analytics, engineering simulations and emerging AI-driven workflows, sectors expected to require increasingly powerful computing infrastructure as enterprises accelerate investment in artificial intelligence and digital engineering.
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