 Rescale, the leader in high-performance computing built for the cloud, announces High-Throughput Computing (HTC), a new capability on Rescale’s platform for running massively parallel computational jobs such as those used in semiconductor verification analysis, bioinformatics pipelines, and design space exploration.
High-throughput computing (HTC) can process millions of modeling, simulation, or data analysis tasks at the same time, helping analysts, engineers, and scientists accelerate research and product development.
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Cloud computing creates new possibilities for R&D organizations to use HTC at unprecedented scale. To fully capture these benefits, organizations need sophisticated and robust management capabilities to securely manage HTC tasks across multiple cloud services and computing architectures. The Rescale HTC platform makes this possible.
Rescale’s HTC solution enables organizations to get optimized full-stack workload performance, with improved throughput, cost efficiency, and reliability beyond what’s possible from a single cloud provider. Rescale’s global multi-cloud coverage, combined with its performance intelligence, delivers best-in-class performance for any workload, anywhere, while offering visibility and control to help ensure HTC operations are efficient and secure.
To address the complexities of running HTC across a mix of cloud infrastructures, processor types and hardware architectures, Rescale’s HTC capability offers multi-cloud automation, unified data management, and full-stack security to help organizations more efficiently execute their HTC projects. Organizations can use Rescale HTC’s cloud-native container-based architecture to get the best hardware architectures for their compute jobs across any of the leading cloud computing service providers including AWS, Google Cloud, Microsoft Azure, and NVIDIA DGX Cloud.
“Rescale is helping Arm usher in a new era for chip design,” says Mark Galbraith, Arm’s vice president of Productivity Engineering. “Arm-powered cloud computing combined with the intelligent automation of the Rescale platform brings many benefits to our design and verification processes by not only helping Arm engineers create the world’s most advanced IP, but also enabling our ecosystem to take full advantage of multi-cloud resources for accelerating R&D. With Rescale, our engineering teams can access the best computing resources they need – including the price/performance and sustainability benefits of running on Arm architecture – whenever they need them.”
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Rescale is demonstrating industry-defining scale and reliability for multi-cloud HTC operations. For example, Rescale HTC has demonstrated the ability to successfully run workloads with nearly half a million instantaneous vCPUs across two cloud providers and 12 regions, in just a few minutes. Over an eight week period Rescale HTC demonstrated successful runs of over 50 million core hours on Arm Architecture instances demonstrating 99.99 percent job reliability.
Rescale’s platform also enables the seamless adoption of the latest computing architectures, such as new Arm-based processors, from the most innovative and fast-moving cloud providers including AWS Graviton3, Google Cloud Tau T2A, Microsoft Azure Dpsv5, and NVIDIA GH200Â Grace Hopper. Through Rescale’s AI-based Compute Recommendation Engine, workloads can automatically and seamlessly adopt the best hardware architectures commercially available individually tuned to the specific workload.
“Across industries we are seeing rapid adoption of high-performance computing and high-throughput computing, upon which customers are running simulation, applied AI, and machine learning for engineering and scientific workloads.” says Joris Poort, CEO of Rescale, “Arm is a great example of how Rescale is working with leading companies to accelerate innovation with the power of intelligent computing across clouds.
Beyond semiconductor verification and testing, Rescale’s HTC solution is ideal for a wide-range of use cases including drug discovery, computer-aided engineering, deep learning networks, image processing, molecular dynamics, computational chemistry, computer vision applications, synthetic data generation, AI data processing, and signal processing systems.
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