The Revolution in the Lab is Overwhelming IT

By John Russell

October 5, 2015

Sifting through the vast treasure trove of data spilling from modern life science instruments is perhaps the defining challenge for biomedical research today. NIH, for example, generates about 1.5PB of data a month, and that excludes NIH-funded external research. Not only have DNA sequencers become extraordinarily powerful, but also they have proliferated in size and type, from big workhorse instruments like the Illumina HiSeq X Ten, down to reliable bench-top models (MiSeq) suitable for small labs, and there are now in advanced development USB-stick sized devices that plug into a USB port.

“The flood of sequence data, human and non-human that may impact human health, is certainly growing and in need of being integrated, mined, and understood. Further, there are emerging technologies in imaging and high resolution structure studies that will be generating a huge amount of data that will need to be analyzed, integrated, and understood,”[i] said Jack Collins, Director of the Advanced Biomedical Computing Center at the Frederick National Laboratory for Cancer Research, NCI.

Here are just a few of the many feeder streams to the data deluge:

  • DNA Sequencers. An Illumina (NASDAQ: ILMN) top-of-the-line HiSeq Ten Series can generate a full human genome in just 18 hours (and generate 3TB) and deliver 18000 genomes in a year. File size for a single whole genome sample may exceed 75GB.
  • Live cell imaging. High throughput imaging in which robots screen hundreds of millions of compounds on live cells typically generate tens of terabytes weekly.
  • Confocal imaging. Scanning 100s of tissue section, with sometimes many scans per section, each with 20-40 layers and multiple fluorescent channels can produce on the order of 10TB weekly.
  • Structural Data. Advanced investigation into form and structure is driving huge and diverse datasets derived from many sources.

Broadly, the flood of data from various LS instruments stresses virtually every part of most research computational environment (cpu, network, storage, system and application software). Indeed, important research and clinical work can be delayed or not attempted because although generating the data is feasible, the time required to perform the data analysis can be impractical. Faced with these situations, research organizations are forced to retool the IT infrastructure.

“Bench science is changing month to month while IT infrastructure is refreshed every 2-7 years. Right now IT is not part of the conversation [with life scientists] and running to catch up,” noted Ari Berman, GM of Government Services, the BioTeam consulting firm and a member of Tabor EnterpriseHPC Conference Advisory Board.

The sheer volume of data is only one aspect of the problem. Diversity in files and data types further complicates efforts to build the “right” infrastructure. Berman noted in a recent presentation that life sciences generates massive text files, massive binary files, large directories (many millions of files), large files ~600Gb and very many small files ~30kb or less. Workflows likewise vary. Sequencing alignment and variant calling offer one set of challenges; pathway simulation presents another; creating 3D models – perhaps of the brain and using those to perform detailed neurosurgery with real-time analytic feedback

“Data piles up faster than it ever has before. In fact, a single new sequencer can typically generate terabytes of data a day. And as a result, an organization or lab with multiple sequencers is capable of producing petabytes of data in a year. The data from the sequencers must be analyzed and visualized using third-party tools. And then it must be managed over time,” said Berman.

Human Brain ProjectAn excellent, though admittedly high-end, example of the growing complexity of computational tools being contemplated and developed in life science research is presented by the European Union Human Brain Project[ii] (HBP). Among its lofty goals are creation of six information and communications technology (ICT) platforms intended to enable “large-scale collaboration and data sharing, reconstruction of the brain at different biological scales, federated analysis of clinical data to map diseases of the brain, and development of brain-inspired computing systems.”

The elements of the planned HPC platform include[iii]:

  • Neuroinformatics: a data repository, including brain atlases.
  • Brain Simulation: building ICT models and simulations of brains and brain components.
  • Medical Informatics: bringing together information on brain diseases.
  • Neuromorphic Computing: ICT that mimics the functioning of the brain.
  • Neurorobotics: testing brain models and simulations in virtual environments.
  • HPC Infrastructure: hardware and software to support the other Platforms.

(Tellingly HBP organizers have recognized the limited computational expertise of many biomedical researchers and also plan to develop technical support and training programs for users of the platforms.)

There is broad agreement in the life sciences research community that there is no single best HPC infrastructure to handle the many LS use cases. The best approach is to build for the dominant use cases. Even here, said Berman, building HPC environments for LS is risky, “The challenge is to design systems today that can support unknown research requirements over many years.” And of course, this all must be accomplished in a cost-constrained environment.

Vertical Focus: HPC in BioIT“Some lab instruments know how to submit jobs to clusters. You need heterogeneous systems. Homogeneous clusters don’t work well in life sciences because of the varying uses cases. Newer clusters are kind of a mix and match of things we have fat nodes with tons of cpus and thin nodes with really fast cpus, [for example],” said Berman.

Just one genome, depending upon the type of sequencing and the coverage, can generate 100GB of data to manage. Capturing, analyzing, storing, and presenting the accumulating data requires a hybrid HPC infrastructure that blends traditional cluster computing with emerging tools such as iRODS (Integrated Rule-Oriented Data System) and Hadoop. Unsurprisingly the HPC infrastructure is always a work in progress

Here’s a snapshot of the two of the most common genomic analysis pipelines:

  1. DNA Sequencing. DNA extracted from tissue samples is run through the high-throughput NGS instruments. These modern sequencers generate hundreds of millions of short DNA sequences for each sample, which must then be ‘assembled’ into proper order to determine the genome. Researchers use parallelized computational workflows to assemble the genome and perform quality control on the reassembly—fixing errors in the reassembly.
  2. Variant Calling. DNA variations (SNPs, haplotypes, indels, etc) for an individual are detected, often using large patient populations to help resolve ambiguities in the individual’s sequence data. Data may be organized into a hybrid solution that uses a relational database to store canonical variations, high-performance file systems to hold data, and a Hadoop-based approach for specialized data-intensive analysis. Links to public and private databases help researchers identify the impact of variations including, for example, whether variants have known associations with clinically relevant conditions.

The point is that life science research – and soon healthcare delivery – has been transformed by productivity leaps in the lab that now are creating immense computational challenges. (next Part 2: Storage Strategies)

[i] Presented on a panel at Leverage Big Data conference, March 2015; http://www.leveragebigdata.com;

[ii] https://www.humanbrainproject.eu/

[iii] https://www.humanbrainproject.eu/discover/the-project/platforms;jsessionid=emae995mioyqxt99x2a14ljg

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!

Researchers Scale COSMO Climate Code to 4888 GPUs on Piz Daint

October 17, 2017

Effective global climate simulation, sorely needed to anticipate and cope with global warming, has long been computationally challenging. Two of the major obstacles are the needed resolution and prolonged time to compute Read more…

By John Russell

Student Cluster Competition Coverage New Home

October 16, 2017

Hello computer sports fans! This is the first of many (many!) articles covering the world-wide phenomenon of Student Cluster Competitions. Finally, the Student Cluster Competition coverage has come to its natural home: H Read more…

By Dan Olds

UCSD Web-based Tool Tracking CA Wildfires Generates 1.5M Views

October 16, 2017

Tracking the wildfires raging in northern CA is an unpleasant but necessary part of guiding efforts to fight the fires and safely evacuate affected residents. One such tool – Firemap – is a web-based tool developed b Read more…

By John Russell

HPE Extreme Performance Solutions

Transforming Genomic Analytics with HPC-Accelerated Insights

Advancements in the field of genomics are revolutionizing our understanding of human biology, rapidly accelerating the discovery and treatment of genetic diseases, and dramatically improving human health. Read more…

Exascale Imperative: New Movie from HPE Makes a Compelling Case

October 13, 2017

Why is pursuing exascale computing so important? In a new video – Hewlett Packard Enterprise: Eighteen Zeros – four HPE executives, a prominent national lab HPC researcher, and HPCwire managing editor Tiffany Trader Read more…

By John Russell

Student Cluster Competition Coverage New Home

October 16, 2017

Hello computer sports fans! This is the first of many (many!) articles covering the world-wide phenomenon of Student Cluster Competitions. Finally, the Student Read more…

By Dan Olds

Intel Delivers 17-Qubit Quantum Chip to European Research Partner

October 10, 2017

On Tuesday, Intel delivered a 17-qubit superconducting test chip to research partner QuTech, the quantum research institute of Delft University of Technology (TU Delft) in the Netherlands. The announcement marks a major milestone in the 10-year, $50-million collaborative relationship with TU Delft and TNO, the Dutch Organization for Applied Research, to accelerate advancements in quantum computing. Read more…

By Tiffany Trader

Fujitsu Tapped to Build 37-Petaflops ABCI System for AIST

October 10, 2017

Fujitsu announced today it will build the long-planned AI Bridging Cloud Infrastructure (ABCI) which is set to become the fastest supercomputer system in Japan Read more…

By John Russell

HPC Chips – A Veritable Smorgasbord?

October 10, 2017

For the first time since AMD's ill-fated launch of Bulldozer the answer to the question, 'Which CPU will be in my next HPC system?' doesn't have to be 'Whichever variety of Intel Xeon E5 they are selling when we procure'. Read more…

By Dairsie Latimer

Delays, Smoke, Records & Markets – A Candid Conversation with Cray CEO Peter Ungaro

October 5, 2017

Earlier this month, Tom Tabor, publisher of HPCwire and I had a very personal conversation with Cray CEO Peter Ungaro. Cray has been on something of a Cinderell Read more…

By Tiffany Trader & Tom Tabor

Intel Debuts Programmable Acceleration Card

October 5, 2017

With a view toward supporting complex, data-intensive applications, such as AI inference, video streaming analytics, database acceleration and genomics, Intel i Read more…

By Doug Black

OLCF’s 200 Petaflops Summit Machine Still Slated for 2018 Start-up

October 3, 2017

The Department of Energy’s planned 200 petaflops Summit computer, which is currently being installed at Oak Ridge Leadership Computing Facility, is on track t Read more…

By John Russell

US Exascale Program – Some Additional Clarity

September 28, 2017

The last time we left the Department of Energy’s exascale computing program in July, things were looking very positive. Both the U.S. House and Senate had pas Read more…

By Alex R. Larzelere

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

Reinders: “AVX-512 May Be a Hidden Gem” in Intel Xeon Scalable Processors

June 29, 2017

Imagine if we could use vector processing on something other than just floating point problems.  Today, GPUs and CPUs work tirelessly to accelerate algorithms Read more…

By James Reinders

NERSC Scales Scientific Deep Learning to 15 Petaflops

August 28, 2017

A collaborative effort between Intel, NERSC and Stanford has delivered the first 15-petaflops deep learning software running on HPC platforms and is, according Read more…

By Rob Farber

Oracle Layoffs Reportedly Hit SPARC and Solaris Hard

September 7, 2017

Oracle’s latest layoffs have many wondering if this is the end of the line for the SPARC processor and Solaris OS development. As reported by multiple sources Read more…

By John Russell

US Coalesces Plans for First Exascale Supercomputer: Aurora in 2021

September 27, 2017

At the Advanced Scientific Computing Advisory Committee (ASCAC) meeting, in Arlington, Va., yesterday (Sept. 26), it was revealed that the "Aurora" supercompute Read more…

By Tiffany Trader

Google Releases Deeplearn.js to Further Democratize Machine Learning

August 17, 2017

Spreading the use of machine learning tools is one of the goals of Google’s PAIR (People + AI Research) initiative, which was introduced in early July. Last w Read more…

By John Russell

GlobalFoundries Puts Wind in AMD’s Sails with 12nm FinFET

September 24, 2017

From its annual tech conference last week (Sept. 20), where GlobalFoundries welcomed more than 600 semiconductor professionals (reaching the Santa Clara venue Read more…

By Tiffany Trader

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in Read more…

By Tiffany Trader

Leading Solution Providers

Amazon Debuts New AMD-based GPU Instances for Graphics Acceleration

September 12, 2017

Last week Amazon Web Services (AWS) streaming service, AppStream 2.0, introduced a new GPU instance called Graphics Design intended to accelerate graphics. The 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

EU Funds 20 Million Euro ARM+FPGA Exascale Project

September 7, 2017

At the Barcelona Supercomputer Centre on Wednesday (Sept. 6), 16 partners gathered to launch the EuroEXA project, which invests €20 million over three-and-a-half years into exascale-focused research and development. Led by the Horizon 2020 program, EuroEXA picks up the banner of a triad of partner projects — ExaNeSt, EcoScale and ExaNoDe — building on their work... Read more…

By Tiffany Trader

Delays, Smoke, Records & Markets – A Candid Conversation with Cray CEO Peter Ungaro

October 5, 2017

Earlier this month, Tom Tabor, publisher of HPCwire and I had a very personal conversation with Cray CEO Peter Ungaro. Cray has been on something of a Cinderell Read more…

By Tiffany Trader & Tom Tabor

Cray Moves to Acquire the Seagate ClusterStor Line

July 28, 2017

This week Cray announced that it is picking up Seagate's ClusterStor HPC storage array business for an undisclosed sum. "In short we're effectively transitioning the bulk of the ClusterStor product line to Cray," said CEO Peter Ungaro. Read more…

By Tiffany Trader

Intel Launches Software Tools to Ease FPGA Programming

September 5, 2017

Field Programmable Gate Arrays (FPGAs) have a reputation for being difficult to program, requiring expertise in specialty languages, like Verilog or VHDL. Easin Read more…

By Tiffany Trader

IBM Advances Web-based Quantum Programming

September 5, 2017

IBM Research is pairing its Jupyter-based Data Science Experience notebook environment with its cloud-based quantum computer, IBM Q, in hopes of encouraging a new class of entrepreneurial user to solve intractable problems that even exceed the capabilities of the best AI systems. Read more…

By Alex Woodie

Intel, NERSC and University Partners Launch New Big Data Center

August 17, 2017

A collaboration between the Department of Energy’s National Energy Research Scientific Computing Center (NERSC), Intel and five Intel Parallel Computing Cente Read more…

By Linda Barney

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