Visit additional Tabor Communication Publications
December 08, 2006
Sun Microsystems has announced that Cedars-Sinai Medical Center is now using a Sun Grid Rack system, comprised of 400 Sun Fire x64 servers, Sun StorageTek solutions, Sun N1 software and pre-integrated by Sun Customer Ready Systems, to process and analyze vast amounts of complex data in the pursuit of medical discoveries that could lead to new treatments for life-threatening and chronic diseases. One of the largest academic medical centers in the United States and a leader in clinical research, Cedars-Sinai expects to more than quadruple its previous data processing capacity using the Sun high performance computing grid, while also decreasing cost and power consumption.
At the new Spielberg Family Center for Applied Proteomics at Cedars-Sinai Medical Center in Los Angeles, researchers are doing highly complex analyses of the proteins in patient blood samples in order to discover and develop treatments -- for cancer, heart disease, epilepsy, high cholesterol and other diseases -- that are based on an individual's biochemical makeup and medical history. To undertake this task, Cedars-Sinai sought a supercomputer capable of massive computational power and data storage to process multiple terabytes of raw data daily and reveal patterns that could be correlated to clinical outcomes.
"Sun looked at the tasks and the computational needs we had and was able to provide an optimal solution. They were able to meet our needs at every level," said Jonathan Katz, senior scientist and director of operations, Spielberg Family Center for Applied Proteomics, Cedars-Sinai Medical Center.
The 400 Sun servers form a supercomputer in a compact footprint that perform huge volumes of statistical and data analysis. The system is aiming to generate four terabytes of data daily by 2007 -- four times what was previously processed by the grid -- and eight terabytes daily by 2008. The processing power enables researchers to analyze complex data sets in days rather than weeks or months and cross-compare data to uncover new disease connections.
"Leading research organizations come to Sun for our proven expertise in high-performance computing. Sun's technologies and services enable organizations to accelerate real-world problem solving, while also decreasing cost and power consumption," said Marc Hamilton, senior director of High Performance Computing, Sun Microsystems. "Sun's commitment goes beyond the technology though -- what drives our innovation in HPC is the belief that our supercomputers can help organizations like Cedars-Sinai solve some of the most pressing healthcare challenges that humans face."
Cedars-Sinai estimates that it saved $60,000 and two months' time by having the Sun Customer Ready Program integrate and deploy the pre-assembled grid. Moreover, the Sun servers provide further cost savings by scaling down to one-third their normal power when not active.
"We have a remarkable relationship with Sun. The passion of the employees goes far beyond selling equipment. They offer to come in on weekends to help us. The enthusiasm and dedication is something I haven't experienced with any company -- ever," said David Agus, director, Spielberg Family Center for Applied Proteomics, Cedars-Sinai Medical Center.
In quieter times, sounding the bell of funding big science with big systems tends to resonate further than when ears are already burning with sour economic and national security news. For exascale's future, however, the time could be ripe to instill some sense of urgency....
In a recent solicitation, the NSF laid out needs for furthering its scientific and engineering infrastructure with new tools to go beyond top performance, Having already delivered systems like Stampede and Blue Waters, they're turning an eye to solving data-intensive challenges. We spoke with the agency's Irene Qualters and Barry Schneider about..
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).
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.
May 22, 2013 |
At some point in the not-too-distant future, building powerful, miniature computing systems will be considered a hobby for high schoolers, just as robotics or even Lego-building are today. That could be made possible through recent advancements made with the Raspberry Pi computers.
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 15, 2013 |
Supercomputers at the Department of Energy’s National Energy Research Scientific Computing Center (NERSC) have worked on important computational problems such as collapse of the atomic state, the optimization of chemical catalysts, and now modeling popping bubbles.
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.
04/15/2013 | Bull | “50% of HPC users say their largest jobs scale to 120 cores or less.” How about yours? Are your codes ready to take advantage of today’s and tomorrow’s ultra-parallel HPC systems? Download this White Paper by Analysts Intersect360 Research to see what Bull and Intel’s Center for Excellence in Parallel Programming can do for your codes.
In this demonstration of SGI DMF ZeroWatt disk solution, Dr. Eng Lim Goh, SGI CTO, discusses a function of SGI DMF software to reduce costs and power consumption in an exascale (Big Data) storage datacenter.
The Cray CS300-AC cluster supercomputer offers energy efficient, air-cooled design based on modular, industry-standard platforms featuring the latest processor and network technologies and a wide range of datacenter cooling requirements.