Computing Model Could Lead to Quicker Advancements in Medical Research

November 13, 2013

BLACKSBURG, Va., Nov. 13 — With the promise of personalized and customized medicine, one extremely important tool for its success is the knowledge of a person’s unique genetic profile.

This personalized knowledge of one’s genetic profile has been facilitated by the advent of next-generation sequencing (NGS), where sequencing a genome, such as the human genome, has gone from costing $9 million to a mere $5,700. Now the research problem is no longer how to collect this information, but how to compute and analyze it.

“Overall, DNA sequencers in the life sciences are able to generate a terabyte — or 1 trillion bytes — of data a minute. This accumulation means the size of DNA sequence databases will increase 10-fold every 18 months,” said Wu Feng, a professor with the Department of Computer Science in the College of Engineering at Virginia Tech.

“In contrast, Moore’s Law (named after Intel co-founder Gordon E. Moore) implies that a processor’s capability to compute on such ‘BIG DATA’ increases by only two-fold every 24 months,” added Weng. “Clearly, the rate at which data is being generated is far outstripping a processor’s capability to compute on it. Hence the need exists for accessible large-scale computing with multiple processors … though the rate at which the number of processors needs to increase is doing so at an exponential rate.”

For the past two years, Feng has led a research team that has now created a new generation of efficient data management and analysis software for large-scale, data-intensive scientific applications in the cloud.

Cloud computing is a term coined by individuals in the computing field that in general describes a large number of connected computers located all over the world that can simultaneously run a program at a large scale. Feng announced his work in October at the O’Reilly Strata Conference + Hadoop World in New York City.

By background to Feng’s announcement, one needs to go back more than three years. In April 2010, the National Science Foundation teamed with Microsoft on a collaborative cloud computing agreement. One year later, they decided to fund 13 research projects to help researchers quickly integrate cloud technology into their research.

Feng was selected to lead one of these teams. His target was to develop an on-demand, cloud-computing model, using the Microsoft Azure cloud. It then evolved naturally to make use of the Microsoft’s Hadoop-based Azure HDInsight Service.

“Our goal was to keep up with the data deluge in the DNA sequencing space. Our result is that we are now analyzing data faster, and we are also analyzing it more intelligently,” Feng said.

With this analysis, and the ability of researchers from all over the globe to see the same sets of data, collaborative work is facilitated on a 24/7 global perspective. “This cooperative cloud computing solution allows life scientists and their institutions easy sharing of public data sets and helps facilitate large-scale collaborative research,” Feng added.

Think of the advantages of oncologists from Sloan Kettering to the German Cancer Research Center would have by maintaining simultaneous and instantaneous access to each other’s data.

Specifically, Feng and his team, Nabeel Mohamed of Chennai, Tamilnadu, India, and a master’s student, and Heshan Lin, a research scientist with Virginia Tech’s Department of Computer Science, developed two software-based research artifacts: SeqInCloud and CloudFlow.  They are members of the Synergy Lab, directed by Feng.

The first, an abbreviation for the words “sequencing in the clouds,” combined with the Microsoft cloud computing platform and infrastructure, provides a portable cloud solution for next-generation sequence analysis.  This resource optimizes data management, such as data partitioning and data transfer, to deliver better performance and resource use of cloud resources.

The second artifact, CloudFlow, is his team’s scaffolding for managing workflows, such as SeqInCloud.  A researcher can install this software to “allow the construction of pipelines that simultaneously use the client and the cloud resources for running the pipeline and automating data transfers,” Feng said.

“If this DNA data and associated resources are not shared, then life scientists and their institutions need to find the millions of dollars to establish and/or maintain their own supercomputing centers,” he added.

Feng knows about high-performance computing. In 2011, he was the main architect of a supercomputer called HokieSpeed.

That year, HokieSpeed settled in at No. 96 on the Top500 List, the industry-standard ranking of the world’s 500 fastest supercomputers. Its fame, however, came because of the machine’s energy efficiency, recorded as the highest-ranked commodity supercomputer in the United States in 2011 on the Green500 List, a compilation of supercomputers that excel at using less energy to do more.

Economics also was key in Feng’s supercomputing success. HokieSpeed was built for $1.4 million, a small fraction — one-tenth of a percent of the cost — of the Top500’s No. 1 supercomputer at the time, the K Computer from Japan. The majority of funding for HokieSpeed came from a $2 million National Science Foundation Major Research Instrumentation grant.

Feng also has been working in the biotechnology arena for quite some time. One of his key awards was the NVIDIA Foundation’s first worldwide research award for computing the cure for cancer.

This grant, also awarded in 2011, enabled Feng, the principal investigator, and his colleagues to create a client-based framework for faster genome analysis to make it easier for genomics researchers to identify mutations that are relevant to cancer.

Likewise, the more general SeqInCloud and CloudFlow artifacts seek to achieve the same type of advances and more, but via a cloud-based framework.

More recently, Feng was a member of a team that secured a $2 million grant from the National Science Foundation and the National Institutes of Health to develop core techniques that would enable researchers to innovatively leverage high-performance computing to analyze the data deluge of high-throughput DNA sequencing, also known as next-generation sequencing.

The College of Engineering at Virginia Tech is internationally recognized for its excellence in 14 engineering disciplines and computer science. The college’s 6,000 undergraduates benefit from an innovative curriculum that provides a “hands-on, minds-on” approach to engineering education, complementing classroom instruction with two unique design-and-build facilities and a strong Cooperative Education Program. With more than 50 research centers and numerous laboratories, the college offers its 2,000 graduate students opportunities in advanced fields of study such as biomedical engineering, state-of-the-art microelectronics, and nanotechnology. Virginia Tech, the most comprehensive university in Virginia, is dedicated to quality, innovation, and results to the commonwealth, the nation, and the world.


Source: Virginia Tech

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

Deep Learning at 15 PFlops Enables Training for Extreme Weather Identification at Scale

March 19, 2018

Petaflop per second deep learning training performance on the NERSC (National Energy Research Scientific Computing Center) Cori supercomputer has given climate scientists the ability to use machine learning to identify e Read more…

By Rob Farber

Mellanox Reacts to Activist Investor Pressures in Letter to Shareholders

March 16, 2018

Activist investor Starboard Value has been exerting pressure on Mellanox Technologies to increase its returns. In response, the high-performance networking company on Monday, March 12, published a letter to shareholders outlining its proposal for a May 2018 extraordinary general meeting (EGM) of shareholders and highlighting its long-term growth strategy and focus on operating margin improvement. Read more…

By Staff

Quantum Computing vs. Our ‘Caveman Newtonian Brain’: Why Quantum Is So Hard

March 15, 2018

Quantum is coming. Maybe not today, maybe not tomorrow, but soon enough. Within 10 to 12 years, we’re told, special-purpose quantum systems will enter the commercial realm. Assuming this happens, we can also assume that quantum will, over extended time, become increasingly general purpose as it delivers mind-blowing power. Read more…

By Doug Black

HPE Extreme Performance Solutions

Achieve Optimal Performance at Scale with High Performance Fabrics for HPC

High Performance Computing (HPC) is unlocking a new era of speed and productivity to fuel business transformation. Rapid advancements in HPC capabilities are helping organizations operate faster and more effectively than ever, but in today’s fast-paced marketplace, a new generation of technologies is required to reach greater scalability and cost-efficiency. Read more…

How the Cloud Is Falling Short for HPC

March 15, 2018

The last couple of years have seen cloud computing gradually build some legitimacy within the HPC world, but still the HPC industry lies far behind enterprise IT in its willingness to outsource computational power. The m Read more…

By Chris Downing

Deep Learning at 15 PFlops Enables Training for Extreme Weather Identification at Scale

March 19, 2018

Petaflop per second deep learning training performance on the NERSC (National Energy Research Scientific Computing Center) Cori supercomputer has given climate Read more…

By Rob Farber

How the Cloud Is Falling Short for HPC

March 15, 2018

The last couple of years have seen cloud computing gradually build some legitimacy within the HPC world, but still the HPC industry lies far behind enterprise I Read more…

By Chris Downing

Stephen Hawking, Legendary Scientist, Dies at 76

March 14, 2018

Stephen Hawking passed away at his home in Cambridge, England, in the early morning of March 14; he was 76. Born on January 8, 1942, Hawking was an English theo Read more…

By Tiffany Trader

Hyperion Tackles Elusive Quantum Computing Landscape

March 13, 2018

Quantum computing - exciting and off-putting all at once - is a kaleidoscope of technology and market questions whose shapes and positions are far from settled. Read more…

By John Russell

Part Two: Navigating Life Sciences Choppy HPC Waters in 2018

March 8, 2018

2017 was not necessarily the best year to build a large HPC system for life sciences say Ari Berman, VP and GM of consulting services, and Aaron Gardner, direct Read more…

By John Russell

Google Chases Quantum Supremacy with 72-Qubit Processor

March 7, 2018

Google pulled ahead of the pack this week in the race toward "quantum supremacy," with the introduction of a new 72-qubit quantum processor called Bristlecone. Read more…

By Tiffany Trader

SciNet Launches Niagara, Canada’s Fastest Supercomputer

March 5, 2018

SciNet and the University of Toronto today unveiled "Niagara," Canada's most-powerful supercomputer, comprising 1,500 dense Lenovo ThinkSystem SD530 high-perfor Read more…

By Tiffany Trader

Part One: Deep Dive into 2018 Trends in Life Sciences HPC

March 1, 2018

Life sciences is an interesting lens through which to see HPC. It is perhaps not an obvious choice, given life sciences’ relative newness as a heavy user of H Read more…

By John Russell

Inventor Claims to Have Solved Floating Point Error Problem

January 17, 2018

"The decades-old floating point error problem has been solved," proclaims a press release from inventor Alan Jorgensen. The computer scientist has filed for and Read more…

By Tiffany Trader

Japan Unveils Quantum Neural Network

November 22, 2017

The U.S. and China are leading the race toward productive quantum computing, but it's early enough that ultimate leadership is still something of an open questi Read more…

By Tiffany Trader

Researchers Measure Impact of ‘Meltdown’ and ‘Spectre’ Patches on HPC Workloads

January 17, 2018

Computer scientists from the Center for Computational Research, State University of New York (SUNY), University at Buffalo have examined the effect of Meltdown Read more…

By Tiffany Trader

IBM Begins Power9 Rollout with Backing from DOE, Google

December 6, 2017

After over a year of buildup, IBM is unveiling its first Power9 system based on the same architecture as the Department of Energy CORAL supercomputers, Summit a Read more…

By Tiffany Trader

Fast Forward: Five HPC Predictions for 2018

December 21, 2017

What’s on your list of high (and low) lights for 2017? Volta 100’s arrival on the heels of the P100? Appearance, albeit late in the year, of IBM’s Power9? Read more…

By John Russell

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Russian Nuclear Engineers Caught Cryptomining on Lab Supercomputer

February 12, 2018

Nuclear scientists working at the All-Russian Research Institute of Experimental Physics (RFNC-VNIIEF) have been arrested for using lab supercomputing resources to mine crypto-currency, according to a report in Russia’s Interfax News Agency. Read more…

By Tiffany Trader

Chip Flaws ‘Meltdown’ and ‘Spectre’ Loom Large

January 4, 2018

The HPC and wider tech community have been abuzz this week over the discovery of critical design flaws that impact virtually all contemporary microprocessors. T Read more…

By Tiffany Trader

Leading Solution Providers

GlobalFoundries, Ayar Labs Team Up to Commercialize Optical I/O

December 4, 2017

GlobalFoundries (GF) and Ayar Labs, a startup focused on using light, instead of electricity, to transfer data between chips, today announced they've entered in Read more…

By Tiffany Trader

How Meltdown and Spectre Patches Will Affect HPC Workloads

January 10, 2018

There have been claims that the fixes for the Meltdown and Spectre security vulnerabilities, named the KPTI (aka KAISER) patches, are going to affect applicatio Read more…

By Rosemary Francis

Perspective: What Really Happened at SC17?

November 22, 2017

SC is over. Now comes the myriad of follow-ups. Inboxes are filled with templated emails from vendors and other exhibitors hoping to win a place in the post-SC thinking of booth visitors. Attendees of tutorials, workshops and other technical sessions will be inundated with requests for feedback. Read more…

By Andrew Jones

V100 Good but not Great on Select Deep Learning Aps, Says Xcelerit

November 27, 2017

Wringing optimum performance from hardware to accelerate deep learning applications is a challenge that often depends on the specific application in use. A benc Read more…

By John Russell

Lenovo Unveils Warm Water Cooled ThinkSystem SD650 in Rampup to LRZ Install

February 22, 2018

This week Lenovo took the wraps off the ThinkSystem SD650 high-density server with third-generation direct water cooling technology developed in tandem with par Read more…

By Tiffany Trader

AMD Wins Another: Baidu to Deploy EPYC on Single Socket Servers

December 13, 2017

When AMD introduced its EPYC chip line in June, the company said a portion of the line was specifically designed to re-invigorate a single socket segment in wha Read more…

By John Russell

World Record: Quantum Computer with 46 Qubits Simulated

December 18, 2017

Scientists from the Jülich Supercomputing Centre have set a new world record. Together with researchers from Wuhan University and the University of Groningen, Read more…

New Blueprint for Converging HPC, Big Data

January 18, 2018

After five annual workshops on Big Data and Extreme-Scale Computing (BDEC), a group of international HPC heavyweights including Jack Dongarra (University of Te Read more…

By John Russell

  • arrow
  • Click Here for More Headlines
  • arrow
Share This