Panasas and Penguin Computing Partner
To improve manageability of Linux-based cluster solutions
This is a Press Release edited by StorageNewsletter.com on July 4, 2008 at 3:42 pmPanasas, Inc., in parallel storage solutions, and Penguin Computing, a provider of Linux cluster solutions, announced their plans to bring to market a comprehensive compute and storage solution that will deliver unprecedented productivity and ease of use to the fastest growing segments of the technical computing market. The solution tightly integrates Panasas ActiveStor parallel storage with Penguin’s Scyld ClusterWare Linux clustering software and Penguin server platforms. The result is a powerful compute and storage solution designed to yield the fastest time to results with the greatest ease of use available on the market today, providing organizations of all sizes and expertise levels increased productivity and lower total cost of ownership (TCO).
"Penguin Computing’s Scyld ClusterWare is industry-proven cluster management software that today is accelerating the pace of product development at Fortune 500 firms," said Matt Jacobs, vice president of HPC at Penguin Computing. "Complexities in clustered environments are very real inhibitors to productivity. It is our sole focus at Penguin to liberate our customers from those complexities and enable them to focus on the research and development goals at hand. The marriage of Panasas parallel storage with the Penguin offering ensures that benefit for our customers and is a natural extension of the ease of use and performance features of both solutions."
High performance computing and parallel storage are quickly becoming the standard building blocks for research and development in highly competitive markets such as oil and gas, life sciences, finance, defense, aerospace and automotive industries. As organizations in these markets increasingly rely on large-scale clusters of multicore servers for simulation, analysis and modeling applications, the importance of tightly integrated, comprehensive and simple-to-use systems becomes critical to empowering researchers and engineers at all levels of the R&D effort.
One customer of the joint Panasas/Penguin Computing solution is AWS Truewind, a leading weather forecasting services firm. "We were in the market for a fully integrated, commercial grade, production-ready compute resource to run our weather simulations models. Time to productivity was critical for us as was the overall ease of use of the system. The Penguin compute solution with Scyld ClusterWare and Panasas ActiveStor parallel storage proved to be exactly what we needed," commented Nicki Armsby, director of operations at AWS Truewind. "This powerful combined solution has already had a positive impact in our transition to a clustered environment."
The ActiveStor parallel storage solution accelerates the performance of data-intensive applications by providing better random access for small files and maximum I/O throughput for large sequential files. This is achieved with the object-based PanFS parallel file system that is the foundation of the pNFS (parallel NFS) standard, which will be released later this year as NFS version 4.1. In addition, the storage system’s appliance-like expansion capability, ease of installation and single global namespace attributes increase user and IT administrative productivity, maximizing ROI from clustered computing environments.
"Our partnership with Penguin Computing provides an attractive choice for enterprise users seeking quick deployment of clusters with superior application performance," said Victor Perez, CEO at Panasas. "Penguin’s advanced servers and easy-to-use Scyld ClusterWare compute infrastructure software are a natural complement to Panasas parallel storage which together contribute to customers’ competitive advantage with improved manageability, increased IT efficiency and heightened end-user productivity."
The combined Panasas/Penguin Computing solution is available today and is already installed in multiple government and commercial enterprise sites.