December 13, 2011
World's largest genomics institute tackles DNA data deluge using NVIDIA Tesla GPUs
BEIJING, Dec. 14 -- NVIDIA today announced that BGI, the world's largest genomics institute, has slashed the time to analyze batches of DNA sequencing data from nearly four days to just six hours using a NVIDIA Tesla GPU-based server farm.
The speed up is considered a critically important step in determining, in an affordable manner, the chemical building blocks that make up a DNA molecule. This is key for the genomics industry to achieve its target of the $1,000 genome -- the point at which genomics can be used in clinical diagnostic tests as a practical component of patient care.
"We are drowning in the genome data that our high-throughput sequencing machines create every day," said Dr. Bingqiang Wang, head of high performance computing from BGI. "GPU acceleration of our genome analysis applications enables our scientists to crunch through data and gain insights into bacteria, plants and humans faster than was ever possible. It offers the potential for researchers and healthcare professionals to identify highly effective and affordable individualized medicines and treatments."
BGI researchers and collaborators have developed three genome data analysis applications that are accelerated by NVIDIA Tesla GPUs:
"The only way for science to reach the $1,000 genome milestone is through technologies that make analyzing DNA data easier, faster and more affordable," said Sumit Gupta, manager of the Tesla business at NVIDIA. "GPU computing enables researchers to achieve game-changing speedups in their scientific applications, which can help reduce the cost and complexity of all types of critical research."
BGI does groundbreaking work in sequencing the genomes of a wide range of life forms, ranging from plants and E.coli to the giant panda, to develop better medicines, improve healthcare and develop genetically enhanced food. BGI's sequencing output is expected to soon surpass the equivalent of more than 700,000 human genomes per year, a dramatic increase over initial efforts, which took 13 years to sequence a single genome.
Tesla GPUs are massively parallel accelerators based on the NVIDIA CUDAR parallel computing architecture. Application developers can accelerate their applications either by using CUDA C, CUDA C++, CUDA Fortran, or by using the simple, easy-to-use directive-based compilers.
For more information about BGI, visit the BGI web site. To learn more about Tesla GPUs, visit the Tesla web site. To learn more about CUDA, visit the CUDA web site. For more NVIDIA news, company and product information, videos/images, and other information, visit the NVIDIA newsroom.
About NVIDIA
NVIDIA (NASDAQ: NVDA) awakened the world to computer graphics when it invented the GPU in 1999. Today, its processors power a broad range of products from smart phones to supercomputers. NVIDIA¡'s mobile processors are used in cell phones, tablets and auto infotainment systems. PC gamers rely on GPUs to enjoy spectacularly immersive worlds. Professionals use them to create visual effects in movies and design everything from golf clubs to jumbo jets. And researchers utilize GPUs to advance the frontiers of science with high-performance computing. The company holds more than 2,100 patents worldwide, including ones covering ideas essential to modern computing. For more information, see www.nvidia.com.
-----
Source: NVIDIA
The Xeon Phi coprocessor might be the new kid on the high performance block, but out of all first-rate kickers of the Intel tires, the Texas Advanced Computing Center (TACC) got the first real jab with its new top ten Stampede system.We talk with the center's Karl Schultz about the challenges of programming for Phi--but more specifically, the optimization...
Read more...
Although Horst Simon was named Deputy Director of Lawrence Berkeley National Laboratory, he maintains his strong ties to the scientific computing community as an editor of the TOP500 list and as an invited speaker at conferences.
Read more...
Supercomputing veteran, Bo Ewald, has been neck-deep in bleeding edge system development since his twelve-year stint at Cray Research back in the mid-1980s, which was followed by his tenure at large organizations like SGI and startups, including Scale Eight Corporation and Linux Networx. He has put his weight behind quantum company....
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...
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.
Read more...
May 10, 2013 |
Program provides cash awards up to $10,000 for the best open-source end-user applications deployed on 100G network.
Read more...
May 09, 2013 |
The Japanese government has revealed its plans to best its previous K Computer efforts with what they hope will be the first exascale system...
Read more...
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.
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.
04/15/2013 | 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.