DENVER, CO / ACCESSWIRE / November 12, 2023 / Alces Flight, a leader in high-performance computing solutions, is pleased to unveil their new High Performance Computing (HPC) cloud delivery platform, Concertim, at the 2023 Supercomputing Conference series (SC23). Concertim is designed for building private and public cloud environments that can be tailored to user's unique requirements, while offering tools that help to drive down the cost and carbon footprint of research computing. Delivered via an intuitive web portal, Concertim provides users with the capabilities to configure the compute resources they need and then monitor cost, power and carbon footprint within a familiar HPC cluster layout.

Concertim
Green Computing utilising renewable energy and product-backed services.

Alces's new product allows enterprise IT teams, solution providers and data-centres to provide state-of-the-art HPC services to customers without the cost and risk of investing in a specialist in-house team. Alces has already partnered with a number of data-centres that use cheap, renewable energy and recycle waste heat in order to offer low-cost, low-carbon cloud HPC solutions.

"Our new product aims to address a common issue with HPC," says Wil Mayers of Alces Flight, "The complexity of using an HPC cluster is a big enough task for our partners and end-users, without the added complication of figuring out how to set-up and optimise the platform for best cost and power efficiency. Concertim massively simplifies the process of getting access to an appropriate compute resource for a typical HPC, AI or machine learning (ML) workload. Users are presented with a simple dashboard that allows them to launch a cluster that suits their particular needs - while clearly showing them the efficiency, cost and carbon impact of their computations."

Concertim offers a range of typical compute environments: including a traditional HPC batch cluster powered by the OpenFlightHPC project, a containerized environment suitable for AI and ML workloads; and interactive developer workstations with server-side 3D rendering. Users can configure their environment via the web interface before launching their cluster and get immediate access - no more waiting around for hardware resources to be provisioned over days and weeks.

"The Concertim platform essentially serves two communities," commented Michael Rudgyard from Alces. "Firstly, it enables our data centre partners to deliver HPC cloud services that would not be possible without a significant long-term investment in their own IT and support teams. But it also serves the end-users of HPC and AI directly, as this community can get access to cheaper and greener compute capabilities, while building virtual and bare-metal resources that are targeted for their own applications. Our aim is to reduce both the time-to-science and the cost-of-service delivery, both of which are of significant importance to our own customers and the broader HPC community."

On-demand services based on Concertim are designed for users consuming hours, days or weeks of resource at a time. For customers who are ready to commit to months or years of resource, Alces and its partners can also provide an option to onboard dedicated equipment that will benefit from centralised, low cost, low carbon infrastructure. Alces currently manages more than 500,000 compute cores, 100PB of data and some of the Top50 HPC clusters worldwide for customers throughout Europe - a scale that brings significant cost reductions for our partners and end-users with cross-platform consistency to simplify the user experience.

For a live demonstration of Concertim visit Alces Flight at booth 224 at the SC23 Conference or contact us at info@alces-flight.com for immediate HPC requirements.

Contact Information

Cristin Merritt
CMO
cristin.merritt@alces-flight.com
01869 249065

SOURCE: Alces Flight Limited

View source version on accesswire.com:
https://www.accesswire.com/796510/alces-flight-launches-concertim-delivering-sustainable-computing-for-researchers-engineers-and-scientists

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