November 05, 2007
BEAVERTON, Ore., Oct. 30 -- GemStone
Systems, the leading provider of distributed data management and
virtualization solutions, today announced GemFire Enterprise 5.1, a
core component of its high-performance, enterprise data fabric (EDF).
The new GemFire Enterprise 5.1 release serves as a distributed
operational data management infrastructure that sits between clustered
application processes and back-end data sources to provide very
low-latency, predictable, high-throughput data sharing and event
distribution. By managing data in-memory, GemFire Enterprise 5.1
enables extremely high-speed data sharing that turns a network of
machines into a single, logical data management unit or a data fabric.
GemFire
Enterprise 5.1 introduces an advanced set of technical features to
deliver powerful, end-to-end scalability and performance improvements.
By augmenting native C++/C# caching capabilities, GemFire Enterprise
5.1 provides highly available asynchronous cache update notifications
to ensure clients are protected against server failures.
“As
enterprises seek to move from a typical disaster recovery scenario to a
resilient architecture, companies need a dynamic distributed cache to
support next-generation enterprise utilities, especially for
compute-intensive, fault-tolerant applications,” said Chris Wolf,
senior analyst with Burton Group.
“There are a large number of
variables in a distributed system which significantly increase the
possibility of an error, such as loss of data consistency, missed event
notifications, or failure conditions arising from applications,
resource limitations or machine failures,” said Jags Ramnarayan, chief
architect at GemStone Systems. “With this release, GemFire Enterprise
5.1 minimizes the application risk under such conditions and specifies
any level of redundancy when partitioning the data across the cluster.
GemFire Enterprise 5.1 will control how the concurrent load is handled
on any server by a configurable set of workers and be assured that
events enqueued for delivery to clients can survive server failures.”
The
combination of distributed data caching with reliable message delivery
provides customers with the tools to build next generation
high-performance, real-time applications. For grid users, GemFire
Enterprise 5.1 offers scalability and the predictability that it
becomes near linear when additional resources become available to the
data fabric.
“As more and more organizations turn to
distributed data grids to improve application performance, minimize
latency and reduce operating expenses, they must address the growing
reliability and scalability challenges,” continues Ramnarayan. “GemFire
Enterprise 5.1 will allow users to leverage native client cache
enhancements, configure more than one level of redundancy and optimize
for high concurrency to guarantee data availability and integrity. This
release reinforces our commitment to delivering reliable solutions to
improve and simplify our client’s most critical IT processes and
deliver best-in-class scalability for distributed data grids with sub
millisecond latency.”
New features of GemFire Enterprise 5.1 include:
About GemStone Systems Inc.
GemStone
Systems is a privately held infrastructure software company that
provides data services solutions for enterprise business architects and
data infrastructure managers that are building, enhancing or
simplifying access, distribution, integration and management of
information within and across the enterprise. Founded in 1982, and with
over 200 installed customers, GemStone is recognized worldwide for its
unique competency and patented technology in object management, virtual
memory architectures, high-performance caching and data distribution
technologies.
The ever-growing complexity of scientific and engineering problems continues to pose new computational challenges. Thus, we present a novel federation model that enables end-users with the ability to aggregate heterogeneous resource scale problems. The feasibility of this federation model has been proven, in the context of the UberCloud HPC Experiment, by gathering the most comprehensive information to date on the effects of pillars on microfluid channel flow.
Read more...
Large-scale, worldwide scientific initiatives rely on some cloud-based system to both coordinate efforts and manage computational efforts at peak times that cannot be contained within the combined in-house HPC resources. Last week at Google I/O, Brookhaven National Lab’s Sergey Panitkin discussed the role of the Google Compute Engine in providing computational support to ATLAS, a detector of high-energy particles at the Large Hadron Collider (LHC).
Read more...
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.
Read more...
May 23, 2013 |
The study of climate change is one of those scientific problems where it is almost essential to model the entire Earth to attain accurate results and make worthwhile predictions. In an attempt to make climate science more accessible to smaller research facilities, NASA introduced what they call ‘Climate in a Box,’ a system they note acts as a desktop supercomputer.
Read more...
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.
Read more...
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.