December 17, 2007
HAYWARD, Calif., Dec. 11 -- StoneFly Inc., a leading supplier of integrated IP storage area network (SAN) systems and a wholly owned subsidiary of Dynamic Network Factory Inc. (DNF), today announced that the United States Patent and Trademark Office has granted the company U.S. patent 7,302,500, entitled "Packet-Based Storage Processing." The patent was awarded for the technology driving StoneFly's storage virtualization engine, which is a core component of all of the company's IP SANs.
The patent, the first issued to StoneFly, is for technology developed by engineers at the company's development center in San Diego. This invention decreases latency and eliminates I/O bottlenecks, allowing communications to be classified into data or command "packets" for more efficient internal routing. The StoneFly innovation also offers a scalable way to process communication requests, taking full advantage of the available system or network bandwidth.
StoneFly's storage virtualization engine resides at the core of StoneFly StoneFusion, an IP-based, block-level provisioning appliance that centralizes storage management, control and monitoring of logical storage volumes. StoneFusion 6.0 provides enhanced VMware and Xen support for fast integration of networked storage with virtual servers, and also includes StoneFly Reflection for local and campus mirroring, and StoneFly Snapshot for fast, efficient data recovery. StoneFusion is integrated into all StoneFly IP SANs.
The storage virtualization engine operates seamlessly behind the scenes, allowing for efficient, concurrent processing. It powers StoneFly services such as clustering, replication, mirroring (via StoneFly Reflection) and other iSCSI storage resources.
According to Mo Tahmasebi, CEO for StoneFly's parent company, DNF Corp., "This valuable invention has provided an important foundation for our IP SAN solutions since StoneFly pioneered the market for iSCSI storage," said Tahmasebi. "We will continue to leverage and build upon this technology as we further advance our product offerings."
About StoneFly Inc. and Dynamic Network Factory Inc.
StoneFly Inc., headquartered in San Diego, was founded in April 2000 to deliver upon the vision of simple and affordable storage optimization and disaster recovery protection through IP SAN solutions. StoneFly is a subsidiary of Dynamic Network Factory Inc. (DNF), a leading maker of high-performance network attached storage, storage area networks, RAID and iSCSI systems. For more information on StoneFly, visit www.stonefly.com or www.iscsi.com.
Founded in 1989, Dynamic Network Factory Inc. (DNF) is a privately held company based in the Silicon Valley (Hayward, Calif.). DNF carries a variety of products to assist companies in meeting their mission-critical storage needs with cost-effective, high performance solutions. DNF started as a U.S. subsidiary of the publicly traded Japanese IT conglomerate, CSK Electronics, in 1989. In 1998, the company refined its strategy and began to focus the hardware group on storage solutions. Within a year, DNF's rapid growth resulted in its emergence as an independent, privately held spin-off. DNF has thousands of customers ranging from consumers and small-to-medium businesses, to government agencies, universities, hospitals, financial institutions and Fortune 500 companies. In 2006, DNF completed its acquisition of StoneFly Networks, an iSCSI storage pioneer and developer of complete, turnkey IP SAN solutions. For more information, visit www.dnfstorage.com.
Frank Ding, engineering analysis & technical computing manager at Simpson Strong-Tie, discussed the advantages of utilizing the cloud for occasional scientific computing, identified the obstacles to doing so, and proposed workarounds to some of those obstacles.
The private industry least likely to adopt public cloud services for data storage are financial institutions. Holding the most sensitive and heavily-regulated of data types, personal financial information, banks and similar institutions are mostly moving towards private cloud services – and doing so at great cost.
In this week's hand-picked assortment, researchers explore the path to more energy-efficient cloud datacenters, investigate new frameworks and runtime environments that are compatible with Windows Azure, and design a uniﬁed programming model for diverse data-intensive cloud computing paradigms.
May 16, 2013 |
When it comes to cloud, long distances mean unacceptably high latencies. Researchers from the University of Bonn in Germany examined those latency issues of doing CFD modeling in the cloud by utilizing a common CFD and its utilization in HPC instance types including both CPU and GPU cores of Amazon EC2.
May 10, 2013 |
Australian visual effects company, Animal Logic, is considering a move to the public cloud.
May 10, 2013 |
Program provides cash awards up to $10,000 for the best open-source end-user applications deployed on 100G network.
May 08, 2013 |
For engineers looking to leverage high-performance computing, the accessibility of a cloud-based approach is a powerful draw, but there are costs that may not be readily apparent.
05/10/2013 | Cleversafe, Cray, DDN, NetApp, & Panasas | From Wall Street to Hollywood, drug discovery to homeland security, companies and organizations of all sizes and stripes are coming face to face with the challenges – and opportunities – afforded by Big Data. Before anyone can utilize these extraordinary data repositories, however, they must first harness and manage their data stores, and do so utilizing technologies that underscore affordability, security, and scalability.
04/02/2012 | AMD | Developers today are just beginning to explore the potential of heterogeneous computing, but the potential for this new paradigm is huge. This brief article reviews how the technology might impact a range of application development areas, including client experiences and cloud-based data management. As platforms like OpenCL continue to evolve, the benefits of heterogeneous computing will become even more accessible. Use this quick article to jump-start your own thinking on heterogeneous computing.