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Rescale, a high-performance computing cloud vendor, has unveiled new features aimed at improving support for containers across cloud services and specialized architectures. The new offerings should simplify developments of advanced scientific and engineering applications for digital twins and cutting-edge scientific research.
Containers are one of the fastest-growing sectors in the IT sector. Containers help lower the barriers in moving applications from on-premises to cloud infrastructure or between clouds. Gartner predicts that this year, more than 75% of global organizations will be running containerized applications in production, up from less than 30% in 2020.
However, enterprises tend to face more challenges in moving high-performance computing (HPC) workloads to containerized infrastructure. HPC use cases bring additional requirements on security and parallel processing. Rescale’s special sauce includes bundles of HPC-specific apps and the dependencies required to execute on the best possible architecture.
Simplifying the engineer experience
Rescale provides a user-intuitive interface for engineers and scientists to securely deploy and scale containerized workloads on any architecture from a multi-cloud infrastructure catalog. The company is now expanding support for HPC use cases around artificial intelligence (AI) and machine learning (ML) workloads. With containers, engineers and scientists can pull published containers from their registry of choice and move forward with their research without thinking too much about the infrastructure.
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Containers come in handy for deploying specialized tools, such as an Nvidia solver specialized for their architecture or home-grown engineering applications. With Rescale, users can pull published containers from their registry of choice and move forward with their research without overthinking the infrastructure. Rescale automates the entire workflow to run these applications and provides easy collaboration for users to share jobs or data while providing IT/HPC organizations security and financial and architectural controls.
This helps simplify the architectural decisions required to build the proper infrastructure around each application the user wants to run. The company also has unique intelligence on the full set of cloud provider architectures. This includes how each architecture performs against different applications at various scales, the maturity and available capacity of these architectures across geographies and cloud provider regions. This could range from a workload for AI/ML, computational fluid dynamics and computational chemistry. This has helped enterprises such as nuclear fusion reactors (Commonwealth Fusion Systems) and commercial spacecraft (Firefly Aerospace).
Refactoring for cloud services
Adam McKenzie, CTO and founder of Rescale, told VentureBeat Rescale has focused on two significant factors for refactoring existing HPC workloads and tools to run on microservices in cloud infrastructure.
First, a lift and shift approach does not work for many HPC applications owing to challenges with data gravity, network bandwidth and complex infrastructure setup. Rescale refactors these components into a software-as-a-service offering. Rescale maintains any software an engineer runs from the catalog. Companies can also bring their software and publish it to the catalog and Rescale optimizes the architecture for various platforms.
Second, Rescale keeps track of cloud offerings, pricing and performance changes across cloud providers. This helps ensure each application uses the best architecture, runs in the best regions and pays for the right service level.
McKenzie said, “This built-for-the-cloud approach is reminiscent of how Snowflake reimagined what a user’s data warehouse experience should be in the cloud. What Snowflake did with the data warehouse, Rescale is doing with the accelerated computing stack.”
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