OCZ SSDs Deployed at Johns Hopkins University

OCZ Technology Group, Inc. announced the
Deneva 2 Series SSDs will be used as the storage device in a pending
‘Data-Scope’ research project at The
Johns Hopkins University (JHU) to create servers for
scientific data processing.

This initiative to maximize data processing power is spearheaded by Dr.
Alexander Szalay, Alumni Centennial Professor in the university’s Department of
Physics and Astronomy and Director of the JHU Institute for Data Intensive
Engineering and Science.

With the goal of creating an affordable, powerful computational environment
that can be used as a blueprint for future science applications, the JHU
project comprises a system of nearly one hundred servers using hundreds of OCZ
Deneva 2 SSDs combined with regular hard disk drives with two tiers for storage
and computing. These systems also serve to expose
students and researchers to technology at an early stage.

"We are extremely pleased to
collaborate with The Johns Hopkins University and contribute some of our
technical expertise to projects that are on the cutting edge," said
Dr. Michael Schuette, VP of Technology Development at OCZ Technology. "The Data-Scope project using OCZ Deneva 2
SSDs as key components is an important step towards revolutionizing scientific
computing, and we are proud to be a part of it."

One of several projects on the Data-Scope is a digital ‘multiverse’ which will
contain a database of the most astronomical objects ever detected. The project
will allow every astronomer in the world to perform their own data analyses
through remote access to the entire database, without the need of downloading
tens to hundreds of TB of data through the Internet. Similar projects are in
progress to analyze hundreds of TB of genomic data, and PB-scale numerical
simulations in turbulence, cosmology and ocean circulation, all big data
problems which do not fit the traditional models of scientific computing.

The completed Data-Scope will drive a new approach to science, where discovery
is driven by large data set analysis. In order to be successful, scientists
must be able to simultaneously build statistical aggregations over PBs of data,
yet explore the smallest aspects of the underlying collections. The advantage
of this system is its ability to function both as a ‘microscope’ and as a ‘telescope’
for data, as well as its storage capacity of 6PB, and its 500GB per second
sequential I/O performance and 20 million IOPS. In addition to raw bandwidth,
SSDs provide a smaller operating footprint over traditional HDDs, reducing
power consumption while still delivering the same amount of IOPS performance.

Leveraging the benefits of General Purpose Computing on GPUs (GPGPU) for
scientific and engineering computing, random access data is streamed from SSDs
into the co-hosted GPUs over the system backplane. The two major benefits of
this architecture are the elimination of access latency by the SSD tier of the
storage hierarchy, and the elimination of the network bottleneck by co-locating
storage and processing on the same server.

The JHU Data-Scope project, which is scheduled to deploy in
early spring, is the showcase for the strengths of SSDs in efficiently
and reliably processing multiple PB data.