ORNL Researchers Bridge the Gap Between R, HPC Communities

April 20, 2017

OAK RIDGE, Tenn., April 20, 2017 — The ability to realistically simulate a range of scientific phenomena, such as supernova explosions and the behavior of materials at the nanoscale, has proven a boon to researchers across the scientific spectrum.

Many now consider simulation the third pillar of scientific inquiry, alongside the centuries-old pillars of theory and experiment.

Yet for some areas of science, parallel computing’s promise remains untapped—specifically, fields such as statistics, genomics, finance, economics, sociology, and the environmental sciences, all of which rely strongly on the R programming language. That’s a shame, says Oak Ridge National Laboratory’s George Ostrouchov, who is heading up the Programming with Big Data in R (pbdR) project to bring these untapped domains into the high-performance computing fold.

These “untapped domains” represent an enormous potential user base for world-class computers such as those owned by the Department of Energy and an enormous opportunity for the power of HPC to accelerate research breakthroughs across the statistical sciences.

Ostrouchov and his colleagues have started the ball rolling with a paper in the journal Big Data Research that serves as a tutorial on how to achieve scalable performance with R on leadership computing resources such as ORNL’s Titan, currently the fastest computer in the country for open science. “70-80 percent of statisticians use R,” said Ostrouchov, “and we want to make HPC tools usable for the statistics community.”

The goal of pbdR is to make the tools familiar to R-based communities compatible with HPC, as opposed to the much more taxing option of having these communities change the way in which they do research. Whereas traditional simulation science produces data, R-based research areas seek to use and understand data.

“These communities don’t know HPC, so by providing these tools at least part of their workflow is in a familiar environment,” said Ostrouchov. “We want to make it easier for these communities to accelerate their science.”

Ostrouchov is a statistician by training, but his work at ORNL has brought him into contact with the most powerful machines and some of the brightest minds in the HPC community. His previous experience with R, and his more recent experience with HPC, gave him some ideas on what might work and what wouldn’t, and which pieces were most likely to fit together.

After exploring the potential of R on world-class resources such as Titan for the Department of Energy’s Office of Science and the now retired Kraken for the National Science Foundation, Ostrouchov and his colleagues Wei-Chen Chen, Drew Schmidt and Pragneshkumar Patel have made great strides in merging the two seemingly disparate platforms, and by extension two very different cultures.

The evolution of R

R’s real strength lies in data exploration and the creation of graphics to explain complex datasets, supported by an unmatched variety of transparent and understandable machine learning tools. “It’s probably the gold standard for graphics in data exploration,” said Ostrouchov. Much like other popular languages such as Python and MATLAB it’s scripted – as opposed to compiled as in the case of C and Fortran.

This presents a unique set of challenges for running effectively on HPC platforms, particularly given that all scripted languages load libraries dynamically during runtime, a process which can bog down file systems when thousands of parallel library requests are made.

Fortunately, Ostrouchov’s BDR co-author Mike Matheson has developed a set of partial solutions that enable libraries to load almost seamlessly up to 10,000 cores thus far on Titan. These solutions are still being optimized, meaning that the 10,000-core metric will almost certainly increase in the future.

Thus far the overhead of using a scripted language to drive the libraries has proven remarkably small, approaching the performance of the underlying linear algebra code known as ScaLAPACK used by other codes to perform matrix calculations. “In theory,” said Ostrouchov, “there’s no reason that R couldn’t match the performance of the leading science codes on Titan.”

Equally important is the fact that the pbdR team has made it possible to run R on HPC systems without changes to the serial code in matrix computations, meaning much less work for programmers looking to make the jump; the same code will do the same thing on a single-processor matrix or a multi-processor matrix such as those employed across Titan, or any other world-class HPC resource for that matter.

Portability was always a top priority, said Ostrouchov, adding that the same code will work on nearly any HPC resource, no matter the architecture; one need only swap out the libraries.

The pbdR team’s achievements bode well for the future of R and HPC, but bringing together these two very different communities will take time, and a few pioneers such as ORNL computational biologist Dan Jacobson who, along with a team including graduate research assistant and PhD student at the University of Tennessee’s Bredesen Center Piet Jones, is using R on Titan to advance the state of the art in genomics and bioenergy.

The team has used the pbdR team’s streamlined R bindings for MPI, a messaging framework that enables the many compute nodes in a parallel machine such as Titan to communicate, to distribute gene expression data to multiple nodes for rapid analyses. This technique will enable a better understanding of the biological functions assigned to individual genes and help discover what metabolites are driving certain observations.

“We need to know what is influencing a biological function, whether this be a gene, regulatory element, metabolite or something else,” said Jones, adding that these analyses help researchers better understand pleiotropy, or the idea that genes have multiple functions, and epistasis, in which the interactions of multiple genes results in a certain characteristic.

Their various projects allow for multiple comparisons using different techniques, and by extension allow them to tackle ever bigger problems in genomics.

Jacobson is also now collaborating with other institutions to use R to study plant microbial interfaces for bioenergy applications, work that he can later apply to clinical datasets for a scientific win-win across very different domains.

It will no doubt be the first of many as the R programming community becomes more comfortable with this whole new world of massive computing capability.

Titan is part of the Oak Ridge Leadership Computing Facility, a DOE Office of Science User Facility located at ORNL.

About Oak Ridge National Laboratory

Oak Ridge National Laboratory is supported by the DOE’s Office of Science. The single largest supporter of basic research in the physical sciences in the United States, the Office of Science is working to address some of the most pressing challenges of our time. For more information, please visit science.energy.gov.


Source: Scott Jones, ORNL Communications

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!

Google Announces Sixth-generation AI Chip, a TPU Called Trillium

May 17, 2024

On Tuesday May 14th, Google announced its sixth-generation TPU (tensor processing unit) called Trillium.  The chip, essentially a TPU v6, is the company's latest weapon in the AI battle with GPU maker Nvidia and clou Read more…

ISC 2024 Student Cluster Competition

May 16, 2024

The 2024 ISC 2024 competition welcomed 19 virtual (remote) and eight in-person teams. The in-person teams participated in the conference venue and, while the virtual teams competed using the Bridges-2 supercomputers at t Read more…

Grace Hopper Gets Busy with Science 

May 16, 2024

Nvidia’s new Grace Hopper Superchip (GH200) processor has landed in nine new worldwide systems. The GH200 is a recently announced chip from Nvidia that eliminates the PCI bus from the CPU/GPU communications pathway.  Read more…

Europe’s Race towards Quantum-HPC Integration and Quantum Advantage

May 16, 2024

What an interesting panel, Quantum Advantage — Where are We and What is Needed? While the panelists looked slightly weary — their’s was, after all, one of the last panels at ISC 2024 — the discussion was fascinat Read more…

The Future of AI in Science

May 15, 2024

AI is one of the most transformative and valuable scientific tools ever developed. By harnessing vast amounts of data and computational power, AI systems can uncover patterns, generate insights, and make predictions that Read more…

Some Reasons Why Aurora Didn’t Take First Place in the Top500 List

May 15, 2024

The makers of the Aurora supercomputer, which is housed at the Argonne National Laboratory, gave some reasons why the system didn't make the top spot on the Top500 list of the fastest supercomputers in the world. At s Read more…

Google Announces Sixth-generation AI Chip, a TPU Called Trillium

May 17, 2024

On Tuesday May 14th, Google announced its sixth-generation TPU (tensor processing unit) called Trillium.  The chip, essentially a TPU v6, is the company's l Read more…

Europe’s Race towards Quantum-HPC Integration and Quantum Advantage

May 16, 2024

What an interesting panel, Quantum Advantage — Where are We and What is Needed? While the panelists looked slightly weary — their’s was, after all, one of Read more…

The Future of AI in Science

May 15, 2024

AI is one of the most transformative and valuable scientific tools ever developed. By harnessing vast amounts of data and computational power, AI systems can un Read more…

Some Reasons Why Aurora Didn’t Take First Place in the Top500 List

May 15, 2024

The makers of the Aurora supercomputer, which is housed at the Argonne National Laboratory, gave some reasons why the system didn't make the top spot on the Top Read more…

ISC 2024 Keynote: High-precision Computing Will Be a Foundation for AI Models

May 15, 2024

Some scientific computing applications cannot sacrifice accuracy and will always require high-precision computing. Therefore, conventional high-performance c Read more…

Shutterstock 493860193

Linux Foundation Announces the Launch of the High-Performance Software Foundation

May 14, 2024

The Linux Foundation, the nonprofit organization enabling mass innovation through open source, is excited to announce the launch of the High-Performance Softw Read more…

ISC 2024: Hyperion Research Predicts HPC Market Rebound after Flat 2023

May 13, 2024

First, the top line: the overall HPC market was flat in 2023 at roughly $37 billion, bogged down by supply chain issues and slowed acceptance of some larger sys Read more…

Top 500: Aurora Breaks into Exascale, but Can’t Get to the Frontier of HPC

May 13, 2024

The 63rd installment of the TOP500 list is available today in coordination with the kickoff of ISC 2024 in Hamburg, Germany. Once again, the Frontier system at 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…

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…

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…

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…

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…

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…

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…

Some Reasons Why Aurora Didn’t Take First Place in the Top500 List

May 15, 2024

The makers of the Aurora supercomputer, which is housed at the Argonne National Laboratory, gave some reasons why the system didn't make the top spot on the Top Read more…

Leading Solution Providers

Contributors

Eyes on the Quantum Prize – D-Wave Says its Time is Now

January 30, 2024

Early quantum computing pioneer D-Wave again asserted – that at least for D-Wave – the commercial quantum era has begun. Speaking at its first in-person Ana 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…

The GenAI Datacenter Squeeze Is Here

February 1, 2024

The immediate effect of the GenAI GPU Squeeze was to reduce availability, either direct purchase or cloud access, increase cost, and push demand through the roof. A secondary issue has been developing over the last several years. Even though your organization secured several racks... Read more…

Intel Plans Falcon Shores 2 GPU Supercomputing Chip for 2026  

August 8, 2023

Intel is planning to onboard a new version of the Falcon Shores chip in 2026, which is code-named Falcon Shores 2. The new product was announced by CEO Pat Gel Read more…

The NASA Black Hole Plunge

May 7, 2024

We have all thought about it. No one has done it, but now, thanks to HPC, we see what it looks like. Hold on to your feet because NASA has released videos of wh Read more…

GenAI Having Major Impact on Data Culture, Survey Says

February 21, 2024

While 2023 was the year of GenAI, the adoption rates for GenAI did not match expectations. Most organizations are continuing to invest in GenAI but are yet to Read more…

How the Chip Industry is Helping a Battery Company

May 8, 2024

Chip companies, once seen as engineering pure plays, are now at the center of geopolitical intrigue. Chip manufacturing firms, especially TSMC and Intel, have b 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…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire