Revolution Analytics Lifts R Language into Terascale Computing

By Michael Feldman

August 4, 2010

R language booster Revolution Analytics is going after the predictive analytics crowd with its latest Revolution R Enterprise software platform. The company announced this week it will be introducing a package called RevoScaleR to bring the R language into the world of “Big Data,” enabling analytics applications to turbo-charge their performance and scale terabyte-sized mountains of data.

Analytics has increasingly become a way for companies to automate intelligence. Businesses in quantitative finance, life sciences, telecom, manufacturing and retail are all looking to mine their data for profits. Governments are also generating enormous amounts of data, and are looking for ways to make sense of it all. Organizations traditionally looked to SAS and SPSS (now a part of IBM) to provide high-end analytics, but a new ecosystem is growing up around the open-source R language, a framework used for statistical computing and modeling.

Developed in the 1990s by Ross Ihaka and Robert Gentleman in New Zealand, the R language was purpose-built for the needs of statisticians. As such, it is tailor-made for analytics and has become the most popular programming language for such work in academia and, increasingly, in the commercial realm. “It’s really has become the lingua franca of learning statistics at universities,” says Jeff Erhardt, COO at Revolution Analytics.

Because of its open-source nature, R is attracting a lot of innovation from its user community. Erhardt says there are probably close to 2 million users worldwide today, and that number is growing. His company hopes to turn that grassroots popularity into a thriving business by propelling the language into the enterprise.

To accomplish that will require some work. R has two fundamental limitations. First, the language is memory bound. That is, it expects the entire database to be in RAM. For the typical workstation, that becomes a problem for any dataset over a few gigabytes. Second is performance. R executes a single process, so cannot take advantage of the performance inherent in multicore/multithreaded CPUs and cluster architectures. According to Revolution Analytics CTO David Champagne, to make it into the enterprise, both issues have to be addressed. And that’s what Revolution R Enterprise and the new RevoScaleR package aim to do.

Speed is really the big issue here, given that the results of predictive analytics are time-sensitive to one degree or another. For example, a trading desk in the US needs to be ready to execute the optimal trades and arbitrage opportunities when the markets in Tokyo open in the morning. To do that, the trading institution has to be able to churn through its entire portfolio overnight.

Overcoming the memory limitation has been accomplished with what the company calls its “external memory” framework. Essentially, it allows data to be quickly brought into memory in bite-sized chunks so that even terabyte-sized data files with billions of rows can be accommodated. To support this model, Revolution Analytics invented the XDF file format in which data rows and columns can be read and written in arbitrary blocks. In fact, new columns and rows can even be inserted on the fly without having to rewrite the rest of the file. This speeds up data transformations considerably, according to Champagne, and makes the analytics workflow much more efficient.

A lot of the execution speed is the result of good old-fashioned parallelism. The initial RevoScaleR implementation enables R applications to be parallelized across multiple cores (and CPUs) on a laptop, workstation or server. With a dual-socket Intel Xeon 5600 (Westmere) server, that means computation can be distributed across as many as 12 cores. Support for distributing an app across multiple nodes in a datacenter will follow shortly. RevoScaleR provides an interface for a number of common statistical algorithms including linear regression, cross tabulation, logistic regression, and summary statistics, with more on the way.

The company has demonstrated considerable speedups using the RevoScaleR package. On an 8-core Nehalem server, with 8 GB of RAM, they were able to process a 13 GB file in record time. In this case the file contained US airline flight data from 1987 to 2008 and was made up of 123 million rows and 29 columns. They were able to execute a linear regression on two variables (arrival delay and day of the week) in about 1 second. The next best implementation (using a special R package to deal with big data files) took around six minutes.

Specific comparisons against traditional SAS and SPSS implementations are lacking, but according to Champagne, beta customers using RevoScaleR have reported orders of magnitude performance speedup compared to legacy analytics platforms. And although Erhardt claims they are not specifically going after SAS and SPSS accounts, customers looking for a less proprietary solution might be tempted by the Revolution offering. “Clearly they come to us, in particular, when they are looking for cost advantage,” he says.

The company basically has two tiers of pricing for commercial customers (Revolution R Enterprise is free to academic users). For the individual user on a desktop, they’re going to charge in “the low thousands of dollars.” The second tier is for multiple users in a more typical enterprise server-based setup. Depending on the configuration, prices should be in the low-five figure range, with a site license in the six-figure range. According to Erhardt, the goal is to leverage the open-source R software and offer their enterprise product at a fraction of the price of traditional analytics software platforms.

The initial RevoScaleR package will be available in 30 days, but only with multicore/multiprocessor support, and only on Windows. Support for distributed computing across a cluster and on Linux is slated for sometime in the next quarter. Also in the queue is support for C++ users who want to add their home-grown algorithms that take advantage of RevoScaleR’s external memory model. And last on the docket is a Web services product that will make R applications accessible from a browser or some other client interface. For a more detailed look at what’s in store, check out the company’s white paper of its roadmap.

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!

SC Bids Farewell to Denver, Heads to Dallas for 30th

November 17, 2017

After a jam-packed four-day expo and intensive six-day technical program, SC17 has wrapped up another successful event that brought together nearly 13,000 visitors to the Colorado Convention Center in Denver for the larg Read more…

By Tiffany Trader

SC17 Keynote – HPC Powers SKA Efforts to Peer Deep into the Cosmos

November 17, 2017

This week’s SC17 keynote – Life, the Universe and Computing: The Story of the SKA Telescope – was a powerful pitch for the potential of Big Science projects that also showcased the foundational role of high performance computing in modern science. It was also visually stunning. Read more…

By John Russell

How Cities Use HPC at the Edge to Get Smarter

November 17, 2017

Cities are sensoring up, collecting vast troves of data that they’re running through predictive models and using the insights to solve problems that, in some cases, city managers didn’t even know existed. Speaking Read more…

By Doug Black

HPE Extreme Performance Solutions

Harness Scalable Petabyte Storage with HPE Apollo 4510 and HPE StoreEver

As a growing number of connected devices challenges IT departments to rapidly collect, manage, and store troves of data, organizations must adopt a new generation of IT to help them operate quickly and intelligently. Read more…

SC17 Student Cluster Competition Configurations: Fewer Nodes, Way More Accelerators

November 16, 2017

The final configurations for each of the SC17 “Donnybrook in Denver” Student Cluster Competition have been released. Fortunately, each team received their equipment shipments on time and undamaged, so the teams are r Read more…

By Dan Olds

SC Bids Farewell to Denver, Heads to Dallas for 30th

November 17, 2017

After a jam-packed four-day expo and intensive six-day technical program, SC17 has wrapped up another successful event that brought together nearly 13,000 visit Read more…

By Tiffany Trader

SC17 Keynote – HPC Powers SKA Efforts to Peer Deep into the Cosmos

November 17, 2017

This week’s SC17 keynote – Life, the Universe and Computing: The Story of the SKA Telescope – was a powerful pitch for the potential of Big Science projects that also showcased the foundational role of high performance computing in modern science. It was also visually stunning. Read more…

By John Russell

How Cities Use HPC at the Edge to Get Smarter

November 17, 2017

Cities are sensoring up, collecting vast troves of data that they’re running through predictive models and using the insights to solve problems that, in some Read more…

By Doug Black

Student Cluster LINPACK Record Shattered! More LINs Packed Than Ever before!

November 16, 2017

Nanyang Technological University, the pride of Singapore, utterly destroyed the Student Cluster Competition LINPACK record by posting a score of 51.77 TFlop/s a Read more…

By Dan Olds

Hyperion Market Update: ‘Decent’ Growth Led by HPE; AI Transparency a Risk Issue

November 15, 2017

The HPC market update from Hyperion Research (formerly IDC) at the annual SC conference is a business and social “must,” and this year’s presentation at S Read more…

By Doug Black

Nvidia Focuses Its Cloud Containers on HPC Applications

November 14, 2017

Having migrated its top-of-the-line datacenter GPU to the largest cloud vendors, Nvidia is touting its Volta architecture for a range of scientific computing ta Read more…

By George Leopold

HPE Launches ARM-based Apollo System for HPC, AI

November 14, 2017

HPE doubled down on its memory-driven computing vision while expanding its processor portfolio with the announcement yesterday of the company’s first ARM-base Read more…

By Doug Black

OpenACC Shines in Global Climate/Weather Codes

November 14, 2017

OpenACC, the directive-based parallel programming model used mostly for porting codes to GPUs for use on heterogeneous systems, came to SC17 touting impressive 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

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

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

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

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

AMD Showcases Growing Portfolio of EPYC and Radeon-based Systems at SC17

November 13, 2017

AMD’s charge back into HPC and the datacenter is on full display at SC17. Having launched the EPYC processor line in June along with its MI25 GPU the focus he Read more…

By John Russell

Leading Solution Providers

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

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

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

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

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

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

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