Targeted Care through a High-Performance Cloud

By Nicole Hemsoth

July 9, 2012

by James Coffin, Ph.D., vice president and general manager, Dell Healthcare and Life Sciences

The transformation of healthcare from episodic to true personalized care is being met with both optimism and the realities of a system that does not take into account a patient’s full health record (both genomic and non-genomic attributes) or the need to collaborate effectively to coordinate care. With the advent of new high-performance computing (HPC) technologies and genomic tools, we are entering an era where healthcare professionals can make more informed decisions on clinical care. While high-throughput research platforms, like next-generation sequencing (NGS), allow researchers to investigate genome-wide variations in genetic markers between normal and diseased tissue, they also create a new problem: the management, sharing and analysis of massive amounts of genomic data related to a patient needed by healthcare professionals to improve diagnosis and treatment. A fresh approach is needed to bridge the gap between clinical research and practice in order to build a more complete picture of disease and treatment strategies and allow healthcare professionals to share knowledge with other experts to determine the best course of care and improve outcomes.

A collaboration between the Translational Genomics Research Institute (TGen) and the Neuroblastoma and Medulloblastoma Translational Research Consortium (NMTRC) is underway on the world’s first FDA-approved personalized medicine clinical trial for pediatric cancer. TGen will use its genomic technology to help NMTRC identify a greater depth of personalized treatment strategies for children with neuroblastoma who are enrolled in the trial, which brings together scientific and medical partners from all across the country. Crucial to its success is an information technology (IT) platform that supports collaboration among the participating clinical sites to create the knowledge base critical for targeted care. 

In conjunction with Dell and its partners, the organizations have built a best-in-class, HPC and cloud-based IT infrastructure designed to accelerate genetic analysis and identification of targeted treatments for patients. As part of the infrastructure, trial-specific portals and a high-speed, grid-based architecture are being implemented to facilitate the rapid transfer of genomic and relevant clinical data between collaborators in the trial. This will help facilitate the integration of genomic data into the studies to build a unique medical profile for each patient that will allow clinicians to predict which of the available therapeutic drugs will be most effective. The goals of the collaboration are long-term object storage, quick data transfer between sites and transparency for everyone from patients to bioinformaticians to scientists to trial administrators. 

The Big Data Challenge

The initial focus of the project was to tackle the “big data” challenge faced by the organizations performing the NGS experiments. The raw data generated by these instruments is extremely large and, in the case of TGen, is doubling every six months. The data objects are complex files with important metadata about the samples and instruments themselves and can be up to 3TB in size and require significant processing resources to collect, manage and analyze. With TGen managing up to 200TB in genomic data per patient, it was important to develop an IT strategy to allow them to analyze these massive files quickly and affordably. After all, the children enrolled in these studies require a quick turnaround to give them the best chance in fighting their disease.

To overcome these challenges, TGen replaced a legacy Dell PowerEdge C2100 system with a cluster of Dell PowerEdge M710HD blade servers. The blades, which run CentOS Linux, are housed in three Dell M1000e modular blade enclosures. Dell Force10 C300 and S4810 10-Gigabit switches provide connectivity for the cluster’s 800 cores. All told, the cluster’s maximum performance is eight teraflops, but despite the dramatic improvement in processing power, the HPC cluster has a small footprint—with three-fold more cores packed into the same floor space—and reduced energy consumption as the blades use 25 percent less power per core than the legacy servers.

For data storage, TGen is building a multi-tier solution that combines multiple technologies as part of the Dell Fluid Data architecture. The technology implemented in this case keeps the data available for researchers and clinicians to collaborate on care while at the same time making it easy to manage and back up to archive. The storage architecture includes a high-performance file system for high-speed, parallel file access, plus Dell Compellent storage in support of more traditional applications, such as Microsoft SQL Server databases and laboratory file sharing. For back-up and archiving, TGen is leveraging the Dell DX Object Storage Platform. The DX platform is especially important because the cost per terabyte makes it affordable to store large amounts of data, scaling well into the petabytes, while allowing TGen’s researchers to use their advanced algorithms to mine these large data sets.

Facilitating Collaboration

The next phase of the implementation is addressing the challenge of long-distance communication. As part of this clinical trial, TGen must partner on research projects with many different professionals from organizations around the world. In addition to patients and their families, the trial involves many clinicians, researchers and pathologists. Patient samples are collected and dissected by biologists, geneticists apply the latest genomics technology to the samples, and bioinformaticians mine the data. Add in the supporting biostatisticians, computer scientists and software engineers and it is critical to create a high-throughput environment that everyone can use as targeted treatments are being developed. TGen and Dell are developing a cloud-based collaboration system to facilitate such interactions. The cloud-based platform provides a virtual library of data that can be accessed by researchers and allow data to be checked out and analyzed using HPC capabilities.  This enables fluid integration between premise-based capabilities and virtual capabilities (the cloud) and is providing the framework to move the data seamlessly through the research lifecycle, protect it, and make it available for future use. In addition, the system includes a high-performance, grid-based architecture to move the massive amounts of genomic data around quickly and securely. Data can be ingested at various sites, moved to the cloud and then made available for analysis either in premise-based HPC environments or any HPC cloud environment. Another important feature of the IT strategy was to localize data near HPC capacity both in the cloud and on-premise to speed analysis and validation.

Meaningful Results

The HPC environment and first phase of the cloud infrastructure is already yielding significant benefits.  The project has increased TGen’s gene sequencing and analysis capacity by 1,200 percent and improved collaboration between physicians, genetic researchers, pharmacists and computer scientists involved in the clinical trial. This cloud infrastructure and portal technology is designed to efficiently manage the volume and complexity of that data while making it secure and accessible to many. For this personalized medicine trial to be successful, doctors and researchers will need the ability to interpret their patient’s genomic information into useful knowledge for targeted care both quickly and affordably. With TGen translational knowledge and the Dell high-performance cloud technology, researchers have accelerated the analysis of patient-specific genomic data from several days down to one day, resulting in a significant improvement in time to targeted treatment. For patients with neuroblastoma, this literally means the difference between life and death.

Link to Video:
http://content.dell.com/us/en/corp/d/videos~en/Documents~2012-tgen-10011267.aspx.aspx

 

James Coffin, Ph.D.Jamie Coffin
Vice President and General Manager, Dell Healthcare and Life Sciences

As vice president and general manager of Dell Healthcare and Life Sciences, James Coffin leads teams in developing the latest innovative information technology solutions and services for healthcare, building the partner ecosystem and driving Dell’s thought leadership in healthcare. Prior to joining Dell, Coffin spent more than 12 years at IBM, where he held a variety of leadership positions. Prior to joining IBM, he was considered a leader in the application of computational chemistry techniques and high-performance computing to real world chemical and biological problems. Coffin holds a Ph.D. in physical chemistry from the University of Arkansas and a Bachelor of Science degree from Louisiana Tech. He studied at Cambridge University as a Cambridge Fulbright Postdoctoral Fellow and was a member of the scientific staff of the National Center for Supercomputing Applications at the University of Illinois. He lectures worldwide on innovation in the field of electronic medical records, personalized medicine, high-performance computing and leading edge in silico techniques to accelerate drug discovery. 

 

Subscribe to HPCwire's Weekly Update!

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

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion XL — were added to the benchmark suite as MLPerf continues Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing power it brings to artificial intelligence.  Nvidia's DGX Read more…

Call for Participation in Workshop on Potential NSF CISE Quantum Initiative

March 26, 2024

Editor’s Note: Next month there will be a workshop to discuss what a quantum initiative led by NSF’s Computer, Information Science and Engineering (CISE) directorate could entail. The details are posted below in a Ca Read more…

Waseda U. Researchers Reports New Quantum Algorithm for Speeding Optimization

March 25, 2024

Optimization problems cover a wide range of applications and are often cited as good candidates for quantum computing. However, the execution time for constrained combinatorial optimization applications on quantum device Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at the network layer threatens to make bigger and brawnier pro Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HBM3E memory as well as the the ability to train 1 trillion pa Read more…

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing po Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HB Read more…

Nvidia Looks to Accelerate GenAI Adoption with NIM

March 19, 2024

Today at the GPU Technology Conference, Nvidia launched a new offering aimed at helping customers quickly deploy their generative AI applications in a secure, s Read more…

The Generative AI Future Is Now, Nvidia’s Huang Says

March 19, 2024

We are in the early days of a transformative shift in how business gets done thanks to the advent of generative AI, according to Nvidia CEO and cofounder Jensen Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, codenamed Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. Wh Read more…

Alibaba Shuts Down its Quantum Computing Effort

November 30, 2023

In case you missed it, China’s e-commerce giant Alibaba has shut down its quantum computing research effort. It’s not entirely clear what drove the change. Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia Read more…

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Leading Solution Providers

Contributors

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

Shutterstock 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

Google Introduces ‘Hypercomputer’ to Its AI Infrastructure

December 11, 2023

Google ran out of monikers to describe its new AI system released on December 7. Supercomputer perhaps wasn't an apt description, so it settled on Hypercomputer Read more…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E Read more…

Intel Won’t Have a Xeon Max Chip with New Emerald Rapids CPU

December 14, 2023

As expected, Intel officially announced its 5th generation Xeon server chips codenamed Emerald Rapids at an event in New York City, where the focus was really o Read more…

IBM Quantum Summit: Two New QPUs, Upgraded Qiskit, 10-year Roadmap and More

December 4, 2023

IBM kicks off its annual Quantum Summit today and will announce a broad range of advances including its much-anticipated 1121-qubit Condor QPU, a smaller 133-qu Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire