Wrangler Supercomputer Speeds through Big Data
March 18, 2016 | University of Texas at AustinEstimated reading time: 9 minutes
Gaffney recalled the hang-up scientists had with code called OrthoMCL, which combs through DNA sequences to find common genetic ancestry in seemingly unrelated species. The problem was that OrthoMCL let loose databases wild as a bucking bronco.
"It generates a very large database and then runs computational programs outside and has to interact with this database," said biologist Rebecca Young of the Department of Integrative Biology and the Center for Computational Biology and Bioinformatics at UT Austin. She added, "That's not what Lonestar and Stampede and some of the other TACC resources were set up for."
Young recounted how at first, using OrthoMCL with online resources, she was only able to pull out 350 comparable genes across 10 species. "When I run OrthoMCL on Wrangler, I'm able to get almost 2,000 genes that are comparable across the species," Young said. "This is an enormous improvement from what is already available. What we're looking to do with OrthoMCL is to allow us to make an increasing number of comparisons across species when we're looking at these very divergent, these very ancient species separated by 450 million years of evolution."
"We were able to go through all of these work cases in anywhere between 15 minutes and 6 hours," Gaffney said. "This is a game changer."
Gaffney added that getting results quickly lets scientists explore new and deeper questions by working with larger collections of data and driving previously unattainable discoveries.
Tuning energy efficiency in buildings
Computer scientist Joshua New with the Oak Ridge National Laboratory (ORNL) hopes to take advantage of Wrangler's ability to tame big data. New is the principal investigator of the Autotune project, which creates a software version of a building and calibrates the model with over 3,000 different data inputs from sources like utility bills to generate useful information such as what an optimal energy-efficient retrofit might be.
"Wrangler has enough horsepower that we can run some very large studies and get meaningful results in a single run," New said. He currently uses the Titan supercomputer of ORNL to run 500,000 simulations and write 45 TB of data to disk in 68 minutes. He said he wants to scale out his parametric studies to simulate all 125.1 million buildings in the U.S.
"I think that Wrangler fills a specific niche for us in that we're turning our analysis into an end-to-end workflow, where we define what parameters we want to vary," New said. "It creates the sampling matrix. It creates the input files. It does the computationally challenging task of running all the simulations in parallel. It creates the output. Then we run our artificial intelligence and statistic techniques to analyze that data on the back end. Doing that from beginning to end as a solid workflow on Wrangler is something that we're very excited about."
When Gaffney talks about storage on Wrangler, he's talking about is a lot of data storage -- a 10 petabyte Lustre-based file system hosted at TACC and replicated at Indiana University. "We want to preserve data," Gaffney said. "The system for Wrangler has been set up for making data a first-class citizen amongst what people do for research, allowing one to hold onto data and curate, share, and work with people with it. Those are the founding tenants of what we wanted to do with Wrangler."
Shedding light on dark energy
"Data is really the biggest challenge with our project," said UT Austin astronomer Steve Finkelstein. His NSF-funded project is called HETDEX, the Hobby-Eberly Telescope Dark Energy Experiment. It's the largest survey of galaxies ever attempted. Scientists expect HETDEX to map over a million galaxies in three dimensions, in the process discovering thousands of new galaxies. The main goal is to study dark energy, a mysterious force pushing galaxies apart.
Wrangler Supercomputer
The Wrangler data-intensive supercomputer system during deployment.
"Every single night that we observe -- and we plan to observe more or less every single night for at least three years -- we're going to make 200 GB of data," Finkelstein said. It'll measure the spectra of 34,000 points of skylight every six minutes.
"On Wrangler is our pipeline," Finkelstein said. "It's going to live there. As the data comes in, it's going to have a little routine that basically looks for new data, and as it comes in every six minutes or so it will process it. By the end of the night it will actually be able to take all the data together to find new galaxies."
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