vScaler’s SLURM integration with FabreX enables end users to dynamically compose their own infrastructure
LONDON, United Kingdom. – Aug 13th, 2020 – vScaler, an opensource Private Cloud offering, built and designed by HPC experts for HPC workloads, today announced the integration of SLURM with GigaIO’s FabreX offering within its Cloud platform, enabling elastic scaling of PCI devices and true HPC disaggregation.
As the industry’s first in-memory network, FabreX supports vScaler’s private cloud appliances for workloads such as deep learning, biotechnology and big data analytics.
vScaler’s Disaggregated (also known as ‘Composable’) HPC solution is enabled by FabreX’s Cloud-class infrastructure platform, a PCIe network that allows users to create rack-scale servers to drastically improve the utilisation rate of expensive resources like GPUs and FPGAs as they can be reconfigured on the fly as workflows change and evolve.
vScaler Chief Technology Officer, David Power comments “We’ve integrated GigaIO’s FabreX hardware into our private cloud product to allow our customer dynamically reconfigure hardware in line with evolving user demands and workloads. As people start to employ more AI tools and techniques, the underlying requirements for hardware to accelerate those tools also evolves. FabreX allows us provision resources to workloads so that we can run much more diverse workloads on top of a core hardware platform”.
“FabreX is based on an open architecture offering industry standard Redfish APIs that make it easy to setup, and because we partner with top tier providers like vScaler for seamless integration, we’re delivering true cloud-class orchestration and composition capabilities,” said Alan Benjamin, CEO of GigaIO. “vScaler’s SLURM integration with FabreX enables end users to dynamically compose their own infrastructure by reaching inside the rack to create servers and resources in seconds, complete with leading security, access control and provisioning features, to match the needs of today’s workflows used in cloud deployments while optimizing TCO.”
The additional integration of the SLURM workload manager, an open-source job scheduler for Linux and Unix-like kernels, means that vScaler Cloud users can request traditional resources like memory and compute cores to be available for jobs. Now, coupled with FabreX, users can now also specify PCI devices such as NVMe or GPUs to be attached to cluster nodes when running and executing specific workloads.
We recognise that traditionally when working with hardware suppliers it can mean that users are left with a static configuration for their HPC infrastructure, and that means that end users need to guess or estimate where their hardware needs to be over the next 1-3 years as their use cases evolve. With GigaIO and vScaler’s elastic Cloud approach, users can add a pool of movable resources into their overall architecture and then map those to the devices as and when they are required.
vScaler is a private Cloud platform built on Open Source technology that enables you to create a secure, scalable, cost-effective, flexible IT infrastructure. Driving out licencing costs, vScaler has been developed to reduce complexity, reduce risk & significantly reduce cost by creating a platform to deliver ‘Anything as a Service’. Competitively priced, secure, fully supported and available immediately, vScaler is poised and ready to simplify your infrastructure and support your digital transformation. For more information, contact the vScaler team at email@example.com
GigaIO has invented the first truly composable enterprise-class software-defined infrastructure network, empowering users to accelerate workloads on-demand, using industry-standard PCI Express technology. The company’s patented network technology optimizes cluster and rack system performance, and greatly reduces total cost of ownership. With the innovative GigaIO FabreX™ open architecture, data centers can scale up or scale out the performance of their systems, enabling their existing investment to flex as workloads and business change over time. For more information, contact the GigaIO team at firstname.lastname@example.org or visit www.gigaio.com.
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