Grid Fights Neurological Disease

By Tiffany Trader

April 16, 2012

Grid computing, the forerunner to today’s more popular cloud-based approach to IT, is being used to create advances in the biomedical field. A pan-European grid computing infrastructure, known as the neuGRID project, was established in 2008 to advance new treatments for neurological diseases such as Alzheimer’s. The goal was to become the “Google for Brain Imaging,” i.e., to provide “a centrally-managed, easy-to-use set of image analysis tools with which scientists can answer complex neuroscientific questions.”

neuGRID logoThe project ran from February 1, 2008, to January 31, 2011, and enabled the processing of thousands of brain scans in less than two weeks instead of five years normally required with traditional methods. The condensed discovery process means that researchers can detect early traces of Alzheimer’s, which should lead to better prognoses.

According to the project website:

The aim of neuGRID was to build a new, user-friendly Grid-based research e-Infrastructure based on existing e-Infrastructures by developing a set of generalised and reusable medical services in order to enable the European neuroscience community to carry out research required for the study of degenerative brain diseases.

Researchers from seven countries worked for three years to develop the infrastructure using EUR 2.8 million in funding from the European Commission. The initial prototype system was comprised of five distributed nodes of 100 cores (CPUs) each, connected with grid middleware and accessible via the Internet with a user-friendly interface. Workability tests were run using datasets of images from the Alzheimer’s Disease Neuroimaging Initiative (ANDI), the largest public database of MRI brain scans documenting the progression of Alzheimer’s disease and mild cognitive impairment. The role of neuGRID was to connect the imaging data with facilities and services for computationally-intensive data analyses.

Principal Investigator Giovanni Frisoni, a neurologist and the deputy scientific director of IRCCS Fatebenefratelli, the Italian National Centre for Alzheimer’s and Mental Diseases, commented on the impetus for the project:

“neuGRID was launched to address a very real need. Neurology departments in most hospitals do not have quick and easy access to sophisticated MRI analysis resources. They would have to send researchers to other labs every time they needed to process a scan. So we thought, why not bring the resources to the researchers rather than sending the researchers to the resources?”

The results were truly remarkable, as explained by Dr. Frisoni:

“In neuGRID we have been able to complete the largest computational challenge ever attempted in neuroscience: we extracted 6,500 MRI scans of patients with different degrees of cognitive impairment and analysed them in two weeks, on an ordinary computer it would have taken five years!”

Going forward, neuGRID will live on in the form of a spin-off project, called neuGRID for You (N4U), which is adding high performance computing (HPC) and cloud computing resources to the original grid infrastructure. With EUR 3.5 million in European Commission funding, N4U is set to become a virtual laboratory for neuroscientists by expanding the user services, algorithm pipelines and datasets.

“In neuGRID we built the grid infrastructure, addressing technical challenges such as the interoperability of core computing resources and ensuring the scalability of the architecture. In N4U we will focus on the user-facing side of the infrastructure, particularly the services and tools available to researchers,” Dr. Frisoni says. “We want to try to make using the infrastructure for research as simple and easy as possible. The learning curve should not be much more difficult than learning to use an iPhone!”

An excerpt from the final report highlights the “business case” for employing the grid/cloud model in research:

During its implementation, neuGRID has pioneered the use of distributed computing in biomedical research. The successful data challenge and success of the user training sessions have proved the validity of the neuGRID concept, justifying the effort of populating the infrastructure with services that neuroscientists need for their daily research activity. It illustrates that a new way of doing science in computational neuroscience, where data algorithms and CPUs are de-coupled from the physical location of the neuroscience lab and externalised to the grid, is realistic and feasible. While it is quite natural to believe that if cloud computing (i.e. outsourcing data, applications, and computational resources) is working for corporate business, it might also work for research, providing empirical proof that this is the case if of course at the same time mandatory and greatly persuasive.

neuGRID’s original mandate was to enable neuroscientists to quickly and efficiently analyse MRI scans of the brains of patients with Alzheimer’s disease. Not only has the team been successful in that endeavor, but now their work has created a use case for grid computing that can be applied to other neurological disorders and additional areas of medicine. The architecture is “such that generic medical services can be flexibly adapted to be interfaced to others, specific to areas outside Alzheimer’s and the neurosciences,” the website explains.

Neelie Kroes, European Commission Vice-President for the Digital Agenda, said: “Today’s e-infrastructures enable us to tackle an unprecedented amount of available data and an increasing complexity of modern experiments. The neuGRID initiative allows scientists in the smallest laboratories of the most remote areas to access data treasures and help patients suffering from dementia. It is up to the scientific community to make the most of this remarkable instrument, to cooperate and break traditional barriers, thus bringing us one decisive step closer to doing away with Alzheimer’s and other brain degenerative diseases.”

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!

PRACEdays Reflects Europe’s HPC Commitment

May 25, 2017

More than 250 attendees and participants came together for PRACEdays17 in Barcelona last week, part of the European HPC Summit Week 2017, held May 15-19 at t Read more…

By Tiffany Trader

Russian Researchers Claim First Quantum-Safe Blockchain

May 25, 2017

The Russian Quantum Center today announced it has overcome the threat of quantum cryptography by creating the first quantum-safe blockchain, securing cryptocurr Read more…

By Doug Black

Google Debuts TPU v2 and will Add to Google Cloud

May 25, 2017

Not long after stirring attention in the deep learning/AI community by revealing the details of its Tensor Processing Unit (TPU), Google last week announced the Read more…

By John Russell

Nvidia CEO Predicts AI ‘Cambrian Explosion’

May 25, 2017

The processing power and cloud access to developer tools used to train machine-learning models are making artificial intelligence ubiquitous across computing pl Read more…

By George Leopold

HPE Extreme Performance Solutions

Exploring the Three Models of Remote Visualization

The explosion of data and advancement of digital technologies are dramatically changing the way many companies do business. With the help of high performance computing (HPC) solutions and data analytics platforms, manufacturers are developing products faster, healthcare providers are improving patient care, and energy companies are improving planning, exploration, and production. Read more…

PGAS Use will Rise on New H/W Trends, Says Reinders

May 25, 2017

If you have not already tried using PGAS, it is time to consider adding PGAS to the programming techniques you know. Partitioned Global Array Space, commonly kn Read more…

By James Reinders

Exascale Escapes 2018 Budget Axe; Rest of Science Suffers

May 23, 2017

President Trump's proposed $4.1 trillion FY 2018 budget is good for U.S. exascale computing development, but grim for the rest of science and technology spend Read more…

By Tiffany Trader

Hedge Funds (with Supercomputing help) Rank First Among Investors

May 22, 2017

In case you didn’t know, The Quants Run Wall Street Now, or so says a headline in today’s Wall Street Journal. Quant-run hedge funds now control the largest Read more…

By John Russell

IBM, D-Wave Report Quantum Computing Advances

May 18, 2017

IBM said this week it has built and tested a pair of quantum computing processors, including a prototype of a commercial version. That progress follows an an Read more…

By George Leopold

PRACEdays Reflects Europe’s HPC Commitment

May 25, 2017

More than 250 attendees and participants came together for PRACEdays17 in Barcelona last week, part of the European HPC Summit Week 2017, held May 15-19 at t Read more…

By Tiffany Trader

PGAS Use will Rise on New H/W Trends, Says Reinders

May 25, 2017

If you have not already tried using PGAS, it is time to consider adding PGAS to the programming techniques you know. Partitioned Global Array Space, commonly kn Read more…

By James Reinders

Exascale Escapes 2018 Budget Axe; Rest of Science Suffers

May 23, 2017

President Trump's proposed $4.1 trillion FY 2018 budget is good for U.S. exascale computing development, but grim for the rest of science and technology spend Read more…

By Tiffany Trader

Cray Offers Supercomputing as a Service, Targets Biotechs First

May 16, 2017

Leading supercomputer vendor Cray and datacenter/cloud provider the Markley Group today announced plans to jointly deliver supercomputing as a service. The init Read more…

By John Russell

HPE’s Memory-centric The Machine Coming into View, Opens ARMs to 3rd-party Developers

May 16, 2017

Announced three years ago, HPE’s The Machine is said to be the largest R&D program in the venerable company’s history, one that could be progressing tow Read more…

By Doug Black

What’s Up with Hyperion as It Transitions From IDC?

May 15, 2017

If you’re wondering what’s happening with Hyperion Research – formerly the IDC HPC group – apparently you are not alone, says Steve Conway, now senior V Read more…

By John Russell

Nvidia’s Mammoth Volta GPU Aims High for AI, HPC

May 10, 2017

At Nvidia's GPU Technology Conference (GTC17) in San Jose, Calif., this morning, CEO Jensen Huang announced the company's much-anticipated Volta architecture a Read more…

By Tiffany Trader

HPE Launches Servers, Services, and Collaboration at GTC

May 10, 2017

Hewlett Packard Enterprise (HPE) today launched a new liquid cooled GPU-driven Apollo platform based on SGI ICE architecture, a new collaboration with NVIDIA, a Read more…

By John Russell

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Just how close real-wo Read more…

By John Russell

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the cam Read more…

By John Russell

Google Pulls Back the Covers on Its First Machine Learning Chip

April 6, 2017

This week Google released a report detailing the design and performance characteristics of the Tensor Processing Unit (TPU), its custom ASIC for the inference Read more…

By Tiffany Trader

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its a Read more…

By Tiffany Trader

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

Since our first formal product releases of OSPRay and OpenSWR libraries in 2016, CPU-based Software Defined Visualization (SDVis) has achieved wide-spread adopt Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Last week, Google reported that its custom ASIC Tensor Processing Unit (TPU) was 15-30x faster for inferencing workloads than Nvidia's K80 GPU (see our coverage Read more…

By Tiffany Trader

Nvidia’s Mammoth Volta GPU Aims High for AI, HPC

May 10, 2017

At Nvidia's GPU Technology Conference (GTC17) in San Jose, Calif., this morning, CEO Jensen Huang announced the company's much-anticipated Volta architecture a Read more…

By Tiffany Trader

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a ne Read more…

By Tiffany Trader

Leading Solution Providers

Facebook Open Sources Caffe2; Nvidia, Intel Rush to Optimize

April 18, 2017

From its F8 developer conference in San Jose, Calif., today, Facebook announced Caffe2, a new open-source, cross-platform framework for deep learning. Caffe2 is Read more…

By Tiffany Trader

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which w Read more…

By Tiffany Trader

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling Read more…

By Steve Campbell

MIT Mathematician Spins Up 220,000-Core Google Compute Cluster

April 21, 2017

On Thursday, Google announced that MIT math professor and computational number theorist Andrew V. Sutherland had set a record for the largest Google Compute Eng Read more…

By Tiffany Trader

US Supercomputing Leaders Tackle the China Question

March 15, 2017

As China continues to prove its supercomputing mettle via the Top500 list and the forward march of its ambitious plans to stand up an exascale machine by 2020, Read more…

By Tiffany Trader

HPC Technique Propels Deep Learning at Scale

February 21, 2017

Researchers from Baidu's Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural networ Read more…

By Tiffany Trader

DOE Supercomputer Achieves Record 45-Qubit Quantum Simulation

April 13, 2017

In order to simulate larger and larger quantum systems and usher in an age of "quantum supremacy," researchers are stretching the limits of today's most advance Read more…

By Tiffany Trader

Knights Landing Processor with Omni-Path Makes Cloud Debut

April 18, 2017

HPC cloud specialist Rescale is partnering with Intel and HPC resource provider R Systems to offer first-ever cloud access to Xeon Phi "Knights Landing" process Read more…

By Tiffany Trader

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