RAID Inc. North American Gold Partner for Parallel File System BeeGFS

RAID Inc., a custom computing solutions company, announced it was selected as a North American Gold Partner for the parallel file system BeeGFS, by Fraunhofer HPC spin-off ThinkParQ GmbH.

The team behind BeeGFS (formerly FhGFS) looks to this strategic partnership as an opportunity for RAID Inc. to enlighten its portfolio of HPC and big data infrastructure solutions across diverse markets as genomics, drug discovery, research, semiconductors, and financial services. RAID Inc. will be exhibiting this parallel cluster file system’s storage performance prowess at Supercomputing Conference (SC16), the HPC community’s flagpole event, in Salt Lake City November 13-18, 2016.

BeeGFS, available as open source, was designed to address I/O intensive workloads with a focus on performance, ease of use, and simplified manageability for HPC without presenting a TCO burden. BeeGFS transparently spreads user data across multiple servers; therefore, by increasing the number of servers and disks in the system, IT admins can scale performance and capacity from small clusters up to enterprise systems with thousands of nodes.

“BeeGFS is a file system dedicated to delivering maximum I/O performance to customers,” said Sven Breuner, CEO, ThinkParQ. “Leveraging their twenty plus years of technical computing experience in solution design, RAID Inc. is positioned to impact the HPC market by deploying all-flash systems with BeeGFS.“

With performance-centric highly available data increasing in demand, a flexible architecture like BeeGFS eliminates data silos and storage complexity with a solution built for multi-tenancy and cloud. BeeGFS is based on a lightweight architecture and can be created on a per job basis with the BeeOND (BeeGFS On Demand) application. This BeeOND feature is designed to provide new instances on the fly across all compute nodes being assigned to a particular job. BeeOND aggregates the performance and capacity of internal SSDs or HDDs in compute nodes for the duration of a compute job to increase performance levels with a method of burst buffering, which can be useful in cloud environments and temporary scratch data scenarios.

“Partnering with ThinkParQ we are able to leverage one of the highest performing file systems for write-dominated workloads,” said Robert Picardi, CEO, RAID Inc. “At RAID Inc. we continue to build on our HPC heritage by introducing all flash technical computing solutions and innovative performance-tuned parallel file systems, BeeGFS allows us to achieve fierce storage performance metrics.“

Incorporating the performance-tuned BeeGFS parallel storage platform into its line of all-flash Fusion servers with dual NVMe drives per node, RAID Inc. can increase performance, IO/s, and data bandwidth efficiency. NVMe flash storage helps to accelerate the included scalable metadata architecture and facilitates increased response in environments with a shared single name space for capacity storage. The RAID Inc.’s Ability EBOD Series creates one of the most cost-effective and storage dense options with 84 drive bays enabling capacities up to 840TB per unit – 210TB pre rack U height.

RAID Inc. builds upon its HPC legacy with the introduction of the BeeGFS parallel cluster file system platform for distributed applications that need fast access to large amounts of data to achieve price/IO/s ratios. Its HPC and big data solutions bring a vendor agnostic approach to disaggregate scale-out platforms and hyperconverged appliances with an architecture that couples compute, networking, and storage designs in an effort to remove storage and data motion barriers.

Performance-centric entities that seek a holistic approach can leverage a RAID Inc.’s technical computing solution built on the BeeGFS platform empowering data center managers to manage a scale-out data center infrastructure.

This solution is available with engineer-driven guidance and 24×7 concierge support from RAID Inc. for organizations looking to maximize data center efficiency and deliver lower cost TCO in technical computing environments.