How NASA Is Meeting the Big Data Challenge

By Tiffany Trader

April 7, 2014

As the scientific community pushes past petaflop into exascale territory, it is imperative that the tools to support ever-more data-intensive workloads keep pace. No where is this more true than at the storied NASA research complex. With 100 active missions supporting cutting-edge science, NASA knows more than most about compute- and data-driven challenges.

A recent paper from Piyush Mehrotra and L. Harper Pryor with NASA’s Advanced Supercomputing (NAS) Division sheds light on how NAS has assisted the diverse workflow of its users, including discovery, access, transportation, management, and dissemination of big data, as well as providing the tools to transform data into insight and knowledge.

“As NASA’s flagship site for computational science and engineering at scale, NAS supports a user base that is at the forefront of data intensive and data driven science,” write Mehrotra and Harper. “Our users’ codes use and generate very large datasets and analyzing these datasets to extract knowledge is a fundamental part of their workflows.”

To get a better understanding of the kinds of challenges faced by their user population, NAS officials went directly to their user base. They then grouped the challenges by the main elements of the workflows, ie “discovery of data and tools, access to and movement of data, storage and management of data, algorithms/tools for performing the analysis/analytics and finally dissemination of the results.”

Discovery hinges on data, which is challenging for NASA based on sheer volume and the distributed nature of the storage archives. Users require tools that support large-scale data movement. There is also the looming need to develop platforms that meet the computational and analytic requirements of the coming exascale era.

With user interviews and several studies to guide them, NAS officials added several initatives to their architecture roadmap. The paper’s authors describe two of these that address user needs:

1) higher level support for scientific workflows to make the challenges of working with big data and big compute more transparent to the user, and

2) tighter integration of compute engines with analytic engines.

The first of these directly relates to the implementation of the NASA Earth Exchange last year. The NASA Earth Exchange (NEX) is a collaborative research platform that brings together advanced supercomputing, earth system modeling, workflow management, and NASA remote-sensing data. It enables users to explore and analyze large earth science data sets, run and share modeling algorithms, collaborate on new or existing projects and share results. To support data-driven workflows, NEX uses VisTrails on Pleiades, NASA’s flagship supercomputer. ParaView is also available as a companino tool to VisTrails. The system will support wide-area workflows encompassing NASA and other agencines, including USGS, NOAA and DOE.

“Our vision is to provide an environment capable of capturing the workflow so that it can be shared with colleagues who can then repeat the experiment and/or tweak the input data/algorithms to generate new knowledge,” write the authors.

The second initiative aims to integrate analytic capability – more specifically visualization – with compute capability. This speeds up what was traditionally a sequential process. In the past, visualization was a post-processing activity that could only be performed after the computation phase. Now NASA’s visualization engine (hyperwall) has been integrated via the same InfiniBand fabric as the Pleiades supercomputer, so that they share storage resources in their Lustre filesystem. Data streams can be directed from computation nodes to the visualization nodes via the InfiniBand I/O fabric while the code is running. The intermediate data can be examined concurrently with execution (to steer computation) or stored for later analysis. This benefit is temporal fidelity at much lower storage cost.

Going forward, NAS aims to continue to optimize the data workflow and they use data knowledged to guide this process. “We don’t want to touch all of the data if we don’t have to,” the authors write. “We know a lot about the structure of the data that might be used to steer the computation toward the subsets of the data that are applicable to the query – and not use the subsets we know are not relevant. This is the good news side…the bad news side is that there is a lot of complexity hiding behind the data and this complexity is critical to using it properly.”

An example of this complexity is remote sensing of atmosphere and land temperatures from space. A satellite does not really measure temperature, it measures radiance, and getting this reading requires a lot of knowledge about the sensor itself. Or take a satellite that is nominally in a sun synchronous orbit, what if the orbit has drifted, they ask. With all this information and metadata being crucial for the discovery challenge, the task at hand is making it all more accessible to the user. A good place to start, according to the authors, is determining what approaches (representation, tools and algorithms) best support the orchestration of metadata. And as always, they emphasize the importance of “never los[ing] sight of the fact that our product is the scientific and engineering knowledge that we extract from big data.”

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!

Doug Kothe on the Race to Build Exascale Applications

May 29, 2017

Ensuring there are applications ready to churn out useful science when the first U.S. exascale computers arrive in the 2021-2023 timeframe is Doug Kothe’s job Read more…

By John Russell

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

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…

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

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

Doug Kothe on the Race to Build Exascale Applications

May 29, 2017

Ensuring there are applications ready to churn out useful science when the first U.S. exascale computers arrive in the 2021-2023 timeframe is Doug Kothe’s job Read more…

By John Russell

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

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