Supercomputing Pipeline Aids DESI’s Quest to Create 3D Map of the Universe

July 21, 2020

July 21, 2020 — As neuroscientists work to better understand the complex inner workings of the brain, a focus of their efforts lies in reimagining and reinventing one of their most basic research tools: the microscope. Likewise, as astrophysicists and cosmologists strive to gain new insights into the universe and its origins, they are eager to observe farther, faster, and with increasing detail via enhancements to their primary instrument: the telescope.

A view of the Mayall Telescope (tallest structure) and the Kitt Peak National Observatory site near Tucson, Arizona. The Dark Energy Spectroscopic Instrument is housed within the Mayall dome. (Image: Marilyn Sargent/Berkeley Lab)

In each case, to unravel scientific mysteries that are either too big or too small to see with a physical instrument alone, they must work in conjunction with yet another critical piece of equipment: the computer. This means more data and increasingly complex datasets, which in turn impacts how quickly scientists can sift through these datasets to find the most relevant clues about where their research should go next.

Fortunately, being able to do this sort of data collection and processing in near real time is becoming a reality for projects like the Dark Energy Spectroscopic Instrument (DESI), a multi-facility collaboration led by Lawrence Berkeley National Laboratory whose goal is to produce the largest 3D map of the universe ever created. Installed on the Mayall Telescope at Kitt Peak National Observatory near Tucson, Arizona, DESI is bringing high-speed automation, high-performance computing, and high-speed networking to its five-year galaxy-mapping mission, capturing light from 35 million galaxies and 2.4 million quasars and transmitting that data to the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy user facility based at Berkeley Lab that serves as DESI’s primary computing center.

“We turn the raw data into useful data,” said Stephen Bailey, a physicist at Berkeley Lab who is the technical lead and manager of the DESI data systems. “The raw data coming off the telescope isn’t the map, so we have to take that data, calibrate it, process it, and turn it into a 3D map that the scientists within the broader collaboration (some 600 worldwide) use for their analyses.”

Over the last several years the DESI team has been using NERSC to build catalogues of the most interesting observational targets, modeling the shapes and colors of more than 1.6 billion individual galaxies detected in 4.3 million images collected by three large-scale sky surveys. The resulting DESI Legacy Imaging Surveys, hosted at NERSC, have performed their catalogue generation at NERSC over the course of eight data releases. The DESI project also leverages the Cosmology Data Repository hosted at NERSC, which contains about 900TB of data, and NERSC’s Community File System, scratch, and HPSS storage systems.

“The previous big survey was a few million objects, but now we are going up to 35-50 million objects,” Bailey said. “It’s a big step forward in the size of the map and the science you can do with.”

But storage is only part of the services NERSC delivers for DESI. The supercomputing center has also been instrumental in developing and supporting DESI’s data processing pipeline, which facilitates the transfer of data from the surveys to the computing center and to users. The project uses 10 dedicated nodes on the Cori supercomputer, enabling the pipeline to run throughout each night during a survey and ensure that the results are available to users by morning for same-day analysis, often helping to inform the next night’s observation plan. The DESI team also uses hundreds of nodes for other processing and expects to scale to thousands of nodes as the dataset increases. To facilitate data I/O, DESI depends on the NERSC data transfer nodes, which are managed as part of a collaborative effort between ESnet and NERSC to enable high performance data movement over the high-bandwidth 100Gb ESnet wide-area network.

“DESI is using the full NERSC ecosystem: computing services, storage, the real-time queue, and real-time data transfer,” Bailey said. “It’s a real game changer for being able to keep up with the data.”

Optimizing Python for CPUs and GPUs

While gearing up for the five-year DESI survey, which is expected to begin in late 2020, NERSC worked with the DESI team to identify  the most computationally intensive parts of the data processing pipeline and implement changes to speed them up. Through the NERSC Exascale Science Applications Program (NESAP), Laurie Stephey, then a postdoctoral researcher and now a data analytics engineer at NERSC, began examining the code.

The pipeline is written almost exclusively in Python – a specialty of Stephey’s – which enables domain scientists to write readable and maintainable scientific code in a relatively short amount of time. Stephey’s goal was to improve the pipeline’s performance while satisfying the DESI team’s requirement that the software remain in Python. The challenge, she explained, was in staying true to the original code while finding new and efficient ways to speed its performance.

“It was my job to keep their code readable and maintainable and to speed it up on the Cori supercomputer’s KNL manycore architecture,” Stephey said. “In the end, we increased their processing throughput 5 to 7 times, which was a big accomplishment – bigger than I’d expected.” This means that something that previously took up to 48 hours now happens overnight, thus enabling analysis during the day and feedback to the following night’s observations, Bailey noted. It also saves the DESI project tens of millions of compute hours at NERSC annually.

“New experiments funded by DOE approach NERSC for support all the time,” said Rollin Thomas who runs NESAP for Data. “And experiments that already use NERSC are capitalizing on our diverse capabilities to do new and exciting things with data. DESI’s sustained engagement with NERSC, through NESAP for Data, the Superfacility initiative and so on, is a model for other experiments. What we learn from these engagements helps us serve the broader experimental and observational data science community better.

And the optimization effort isn’t over yet. The next challenge is to make the DESI code compatible with the GPUs in NERSC’s Perlmutter system, which is slated to arrive in late 2020. Bailey and Stephey began this process last year – “Stephen was instrumental in rewriting the algorithm in a GPU-friendly way,” Stephey noted – but in April NERSC hired one of its newest NESAP postdocs, Daniel Margala, to take over. As a graduate student, Margala had previously worked with Bailey on the Baryon Oscillation Spectroscopic Survey, a DESI predecessor project, “so I’m familiar with a lot of the data processing that needs to be done for DESI,” he said.

So far, Margala’s focus is on preparing DESI’s code for GPUs so that it will be ready to leverage the full potential of the Perlmutter system. He is currently working with a small subset of DESI data on Cori’s GPU testbed nodes; the long-term goal is to make sure the software is ready to handle DESI’s entire five-year dataset.

“The astrophysicists and scientists on DESI are pretty comfortable using Python, so we are trying to do all of this in Python so that they will be able to understand the code we are writing and learn from it, contribute back to it, and maintain it going forward,” Margala said.

Over the next few years, NERSC resources will also be critical to another, larger goal of the DESI project: reprocessing and updating the data.

“Every year we are going to reprocess our data from the very beginning using the latest version of all of our code, and those will become our data assemblies that will then flow into the science papers for the collaboration,” Bailey said. “We only need 10 nodes at NERSC to keep up with the data in real time through the night, but if you want to go back and process 2, 3, 5 years of data, that’s where being able to use hundreds or thousands of nodes will allow us to quickly catch up on all that processing.”

About NERSC and Berkeley Lab

The National Energy Research Scientific Computing Center (NERSC) is a U.S. Department of Energy Office of Science User Facility that serves as the primary high-performance computing center for scientific research sponsored by the Office of Science. Located at Lawrence Berkeley National Laboratory, the NERSC Center serves more than 7,000 scientists at national laboratories and universities researching a wide range of problems in combustion, climate modeling, fusion energy, materials science, physics, chemistry, computational biology, and other disciplines. Berkeley Lab is a DOE national laboratory located in Berkeley, California. It conducts unclassified scientific research and is managed by the University of California for the U.S. Department of Energy. »Learn more about computing sciences at Berkeley Lab.


Source: Kathy Kincade, NERSC and Berkeley Lab

 

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!

Q&A with Altair CEO James Scapa, an HPCwire Person to Watch in 2021

May 14, 2021

Chairman, CEO and co-founder of Altair James R. Scapa closed several acquisitions for the company in 2020, including the purchase and integration of Univa and Ellexus. Scapa founded Altair more than 35 years ago with two Read more…

HLRS HPC Helps to Model Muscle Movements

May 13, 2021

The growing scale of HPC is allowing simulation of more and more complex systems at greater detail than ever before, particularly in the biological research spheres. Now, researchers at the University of Stuttgart are le Read more…

Behind the Met Office’s Procurement of a Billion-Dollar Microsoft System

May 13, 2021

The UK’s national weather service, the Met Office, caused shockwaves of curiosity a few weeks ago when it formally announced that its forthcoming billion-dollar supercomputer – expected to be the most powerful weather and climate-focused supercomputer in the world when it launches in 2022... Read more…

AMD, GlobalFoundries Commit to $1.6 Billion Wafer Supply Deal

May 13, 2021

AMD plans to purchase $1.6 billion worth of wafers from GlobalFoundries in the 2022 to 2024 timeframe, the chipmaker revealed today (May 13) in an SEC filing. In the face of global semiconductor shortages and record-high demand, AMD is renegotiating its Wafer Supply Agreement and bumping up capacity. Read more…

Hyperion Offers Snapshot of Quantum Computing Market

May 13, 2021

The nascent quantum computer (QC) market will grow 27 percent annually (CAGR) reaching $830 million in 2024 according to an update provided today by analyst firm Hyperion Research at the HPC User Forum being held this we Read more…

AWS Solution Channel

Numerical weather prediction on AWS Graviton2

The Weather Research and Forecasting (WRF) model is a numerical weather prediction (NWP) system designed to serve both atmospheric research and operational forecasting needs. Read more…

Hyperion: HPC Server Market Ekes 1 Percent Gain in 2020, Storage Poised for ‘Tipping Point’

May 12, 2021

The HPC User Forum meeting taking place virtually this week (May 11-13) kicked off with Hyperion Research’s market update, covering the 2020 period. Although the HPC server market had been facing a 6.7 percent COVID-re Read more…

Behind the Met Office’s Procurement of a Billion-Dollar Microsoft System

May 13, 2021

The UK’s national weather service, the Met Office, caused shockwaves of curiosity a few weeks ago when it formally announced that its forthcoming billion-dollar supercomputer – expected to be the most powerful weather and climate-focused supercomputer in the world when it launches in 2022... Read more…

AMD, GlobalFoundries Commit to $1.6 Billion Wafer Supply Deal

May 13, 2021

AMD plans to purchase $1.6 billion worth of wafers from GlobalFoundries in the 2022 to 2024 timeframe, the chipmaker revealed today (May 13) in an SEC filing. In the face of global semiconductor shortages and record-high demand, AMD is renegotiating its Wafer Supply Agreement and bumping up capacity. Read more…

Hyperion Offers Snapshot of Quantum Computing Market

May 13, 2021

The nascent quantum computer (QC) market will grow 27 percent annually (CAGR) reaching $830 million in 2024 according to an update provided today by analyst fir Read more…

Hyperion: HPC Server Market Ekes 1 Percent Gain in 2020, Storage Poised for ‘Tipping Point’

May 12, 2021

The HPC User Forum meeting taking place virtually this week (May 11-13) kicked off with Hyperion Research’s market update, covering the 2020 period. Although Read more…

IBM Debuts Qiskit Runtime for Quantum Computing; Reports Dramatic Speed-up

May 11, 2021

In conjunction with its virtual Think event, IBM today introduced an enhanced Qiskit Runtime Software for quantum computing, which it says demonstrated 120x spe Read more…

AMD Chipmaker TSMC to Use AMD Chips for Chipmaking

May 8, 2021

TSMC has tapped AMD to support its major manufacturing and R&D workloads. AMD will provide its Epyc Rome 7702P CPUs – with 64 cores operating at a base cl Read more…

Fast Pass Through (Some of) the Quantum Landscape with ORNL’s Raphael Pooser

May 7, 2021

In a rather remarkable way, and despite the frequent hype, the behind-the-scenes work of developing quantum computing has dramatically accelerated in the past f Read more…

IBM Research Debuts 2nm Test Chip with 50 Billion Transistors

May 6, 2021

IBM Research today announced the successful prototyping of the world's first 2 nanometer chip, fabricated with silicon nanosheet technology on a standard 300mm Read more…

AMD Chipmaker TSMC to Use AMD Chips for Chipmaking

May 8, 2021

TSMC has tapped AMD to support its major manufacturing and R&D workloads. AMD will provide its Epyc Rome 7702P CPUs – with 64 cores operating at a base cl Read more…

Intel Launches 10nm ‘Ice Lake’ Datacenter CPU with Up to 40 Cores

April 6, 2021

The wait is over. Today Intel officially launched its 10nm datacenter CPU, the third-generation Intel Xeon Scalable processor, codenamed Ice Lake. With up to 40 Read more…

Julia Update: Adoption Keeps Climbing; Is It a Python Challenger?

January 13, 2021

The rapid adoption of Julia, the open source, high level programing language with roots at MIT, shows no sign of slowing according to data from Julialang.org. I Read more…

CERN Is Betting Big on Exascale

April 1, 2021

The European Organization for Nuclear Research (CERN) involves 23 countries, 15,000 researchers, billions of dollars a year, and the biggest machine in the worl Read more…

HPE Launches Storage Line Loaded with IBM’s Spectrum Scale File System

April 6, 2021

HPE today launched a new family of storage solutions bundled with IBM’s Spectrum Scale Erasure Code Edition parallel file system (description below) and featu Read more…

10nm, 7nm, 5nm…. Should the Chip Nanometer Metric Be Replaced?

June 1, 2020

The biggest cool factor in server chips is the nanometer. AMD beating Intel to a CPU built on a 7nm process node* – with 5nm and 3nm on the way – has been i Read more…

Saudi Aramco Unveils Dammam 7, Its New Top Ten Supercomputer

January 21, 2021

By revenue, oil and gas giant Saudi Aramco is one of the largest companies in the world, and it has historically employed commensurate amounts of supercomputing Read more…

Quantum Computer Start-up IonQ Plans IPO via SPAC

March 8, 2021

IonQ, a Maryland-based quantum computing start-up working with ion trap technology, plans to go public via a Special Purpose Acquisition Company (SPAC) merger a Read more…

Leading Solution Providers

Contributors

AMD Launches Epyc ‘Milan’ with 19 SKUs for HPC, Enterprise and Hyperscale

March 15, 2021

At a virtual launch event held today (Monday), AMD revealed its third-generation Epyc “Milan” CPU lineup: a set of 19 SKUs -- including the flagship 64-core, 280-watt 7763 part --  aimed at HPC, enterprise and cloud workloads. Notably, the third-gen Epyc Milan chips achieve 19 percent... Read more…

Can Deep Learning Replace Numerical Weather Prediction?

March 3, 2021

Numerical weather prediction (NWP) is a mainstay of supercomputing. Some of the first applications of the first supercomputers dealt with climate modeling, and Read more…

Livermore’s El Capitan Supercomputer to Debut HPE ‘Rabbit’ Near Node Local Storage

February 18, 2021

A near node local storage innovation called Rabbit factored heavily into Lawrence Livermore National Laboratory’s decision to select Cray’s proposal for its CORAL-2 machine, the lab’s first exascale-class supercomputer, El Capitan. Details of this new storage technology were revealed... Read more…

African Supercomputing Center Inaugurates ‘Toubkal,’ Most Powerful Supercomputer on the Continent

February 25, 2021

Historically, Africa hasn’t exactly been synonymous with supercomputing. There are only a handful of supercomputers on the continent, with few ranking on the Read more…

GTC21: Nvidia Launches cuQuantum; Dips a Toe in Quantum Computing

April 13, 2021

Yesterday Nvidia officially dipped a toe into quantum computing with the launch of cuQuantum SDK, a development platform for simulating quantum circuits on GPU-accelerated systems. As Nvidia CEO Jensen Huang emphasized in his keynote, Nvidia doesn’t plan to build... Read more…

New Deep Learning Algorithm Solves Rubik’s Cube

July 25, 2018

Solving (and attempting to solve) Rubik’s Cube has delighted millions of puzzle lovers since 1974 when the cube was invented by Hungarian sculptor and archite Read more…

The History of Supercomputing vs. COVID-19

March 9, 2021

The COVID-19 pandemic poses a greater challenge to the high-performance computing community than any before. HPCwire's coverage of the supercomputing response t Read more…

Microsoft to Provide World’s Most Powerful Weather & Climate Supercomputer for UK’s Met Office

April 22, 2021

More than 14 months ago, the UK government announced plans to invest £1.2 billion ($1.56 billion) into weather and climate supercomputing, including procuremen Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire