How HPC is Hacking Hadoop

By Nicole Hemsoth

February 11, 2014

Although the trend may be quiet and distributed across only a relative few supercomputing sites, Hadoop and HPC are hopping hand-in-hand more frequently. These two technology areas aren’t necessarily made for another—there are limitations in what Hadoop can do. But a stretch of recent research has been pushing the possibilities, especially when it comes to making Hadoop fit data-intensive corners of scientific computing applications.

Despite the infrequency of news around Hadoop powering key research applications, we’ve watched key centers on this path, including the San Diego Supercomputer Center (which was one of the first to publish a comprehensive overview of using Hadoop on HPC resources) with great interest, and listened as nearly all major HPC system vendors (and many software ones too) targeted Hadoop users with key enhancements, tailored distributions, or even new product lines.

The research momentum behind Hadoop for HPC systems picked up in the last couple of years in particular. Among notable items are other explorations of Hadoop for data-intensive science, adapting MapReduce to an HPC environment, exploring it across different parallel file systems, handling scheduling and more. There are well over 2,000 peer-reviewed articles covering some aspect of this trend. The general theme, when you map it out and reduce it to a few words, is that the tooling required for HPC systems can be tweaked to fit Hadoop, especially when the purpose (offering a potential for more streamlined data management/processing on certain problems) is clear.

When it comes to data-intensive computing and Hadoop’s potential role in HPC, Dr. Glenn K. Lockwood at the San Diego Supercomputer Center (SDSC), is one of the key sources for information about specific challenges and opportunities. Most notably, Lockwood’s work on Hadoop for large-scale systems has drawn attention, particularly in terms of his work with the open source “big data” platform’s role on the Gordon system at SDSC.

Gordon is SDSC’s flash-based data-intensive computing resource. Although aimed at “big data” scientific computing, the Appro-built system still packs some serious compute power with its 16,160 cores, ranking at #88 on the most recent Top 500 list. The true measure of performance for Gordon, which was built to tackle data-intensive challenges, is in its input/output operations per second (IOPs) measurement—back when the machine was undergoing its acceptance cycle, it achieved 35 million IOPs. All of these elements made for some prime experimental ground for Lockwood and his colleagues.

In his role as a User Services Consultant at SDSC, Lockwood has been tracking a number of projects across the data-intensive computing spectrum. His most recent explorations, aside from running Hadoop clusters on Gordon, include writing Hadoop applications in Python with Hadoop Streaming, using (and finding parallel options for) the R language across supercomputers, and benchmarking several data-intensive computing frameworks, architectures and usage models.

“Although traditional supercomputers and Hadoop clusters are designed to solve very different problems and are consequentially architected differently, domain scientists are becoming increasingly interested in learning how Hadoop works and how it may be useful in addressing the data-intensive problems they face,” explained Lockwood.  “Making Hadoop available on Gordon has really made it easy for researchers to explore the features and benefits of Hadoop without having to learn an entirely new cloud API or be a systems administrator.”

He explained that instead, users can launch a Hadoop cluster by submitting a single pre-made job script to the batch system on Gordon with which they are already familiar. A “personal Hadoop cluster” is then launched on their job’s nodes, and users can then load data into their cluster’s distributed file system and run map/reduce tasks.  “Literally one single qsub command starts up a fully featured Hadoop cluster on Gordon’s 40 Gbps InfiniBand fabric with HDFS that is either backed by Gordon’s 300 GB SSDs or its Lustre filesystem,” said Lockwood. “This translates into Hadoop clusters capable of ingesting data to HDFS at a rate in excess of 750 MB/s and completing a 1.6 TB TeraSort in under 15 minutes. Because Gordon delivers this high performance both in traditional and Hadoop-based workloads, researchers can make meaningful performance comparisons on production-scale datasets.”

Lockwood highlighted how this has dramatically reduced the entry barrier for domain scientists who want to see what role Hadoop might play in their analyses, and it follows that training and exploratory work has driven a lot of the Hadoop use SDSC is currently seeing on Gordon.  “Faculty and researchers at universities nationwide have been using Gordon to teach courses in data analytics, and we’ve also been providing plenty of hands-on training to the local and national research communities via XSEDE, SDSC’s Summer Institute, PACE’s Data Mining Boot Camps, and UCSD’s Extension program.  In addition, we’ve provided cycles and classroom training for many applications built upon Hadoop including Mahout, Pig, HBase, and RHadoop.”

In Lockwood’s view, ultimately, Hadoop’s application in the traditional domain sciences is still in its infancy because the application ecosystem based on Hadoop is not as mature as the MPI-based ecosystem.  However, he says there is momentum in several non-traditional domains, including bioinformatics and anthropology, which are embracing Hadoop for production research on Gordon due to the natural fit of these domains’ problems with the map/reduce paradigm. “For example, we are supporting several projects that have begun exploring software built upon Hadoop such as Crossbow, CloudBurst, and SeqPig as scalable alternatives for massive genomic studies.  The evaluation process is still early on, but being able to run these Hadoop-based applications alongside the standard toolchain on Gordon is what is making the effort tractable.”

For anyone interested in the challenges and opportunities of deploying Hadoop on a complex system like Gordon, Lockwood has provided a rich overview here.

Aside from Lockwood’s work and that of his colleagues at SDSC, we wanted to point to some other projects that are helping HPC hack Hadoop to make it fit into a more complex environment. The following short list are a few of our top picks.

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!

TACC Researchers Test AI Traffic Monitoring Tool in Austin

December 13, 2017

Traffic jams and mishaps are often painful and sometimes dangerous facts of life. At this week’s IEEE International Conference on Big Data being held in Boston, researchers from TACC and colleagues will present a new Read more…

AMD Wins Another: Baidu to Deploy EPYC on Single Socket Servers

December 13, 2017

When AMD introduced its EPYC chip line in June, the company said a portion of the line was specifically designed to re-invigorate a single socket segment in what has become an overwhelmingly two-socket landscape in the d Read more…

By John Russell

Microsoft Wants to Speed Quantum Development

December 12, 2017

Quantum computing continues to make headlines in what remains of 2017 as tech giants jockey to establish a pole position in the race toward commercialization of quantum. This week, Microsoft took the next step in advanci Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

Explore the Origins of Space with COSMOS and Memory-Driven Computing

From the formation of black holes to the origins of space, data is the key to unlocking the secrets of the early universe. Read more…

ESnet Now Moving More Than 1 Petabyte/wk

December 12, 2017

Optimizing ESnet (Energy Sciences Network), the world's fastest network for science, is an ongoing process. Recently a two-year collaboration by ESnet users – the Petascale DTN Project – achieved its ambitious goal t Read more…

AMD Wins Another: Baidu to Deploy EPYC on Single Socket Servers

December 13, 2017

When AMD introduced its EPYC chip line in June, the company said a portion of the line was specifically designed to re-invigorate a single socket segment in wha Read more…

By John Russell

Microsoft Wants to Speed Quantum Development

December 12, 2017

Quantum computing continues to make headlines in what remains of 2017 as tech giants jockey to establish a pole position in the race toward commercialization of Read more…

By Tiffany Trader

HPC Iron, Soft, Data, People – It Takes an Ecosystem!

December 11, 2017

Cutting edge advanced computing hardware (aka big iron) does not stand by itself. These computers are the pinnacle of a myriad of technologies that must be care Read more…

By Alex R. Larzelere

IBM Begins Power9 Rollout with Backing from DOE, Google

December 6, 2017

After over a year of buildup, IBM is unveiling its first Power9 system based on the same architecture as the Department of Energy CORAL supercomputers, Summit a Read more…

By Tiffany Trader

Microsoft Spins Cycle Computing into Core Azure Product

December 5, 2017

Last August, cloud giant Microsoft acquired HPC cloud orchestration pioneer Cycle Computing. Since then the focus has been on integrating Cycle’s organization Read more…

By John Russell

GlobalFoundries, Ayar Labs Team Up to Commercialize Optical I/O

December 4, 2017

GlobalFoundries (GF) and Ayar Labs, a startup focused on using light, instead of electricity, to transfer data between chips, today announced they've entered in Read more…

By Tiffany Trader

HPE In-Memory Platform Comes to COSMOS

November 30, 2017

Hewlett Packard Enterprise is on a mission to accelerate space research. In August, it sent the first commercial-off-the-shelf HPC system into space for testing Read more…

By Tiffany Trader

SC17 Cluster Competition: Who Won and Why? Results Analyzed and Over-Analyzed

November 28, 2017

Everyone by now knows that Nanyang Technological University of Singapore (NTU) took home the highest LINPACK Award and the Overall Championship from the recently concluded SC17 Student Cluster Competition. We also already know how the teams did in the Highest LINPACK and Highest HPCG competitions, with Nanyang grabbing bragging rights for both benchmarks. Read more…

By Dan Olds

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

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

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

Japan Unveils Quantum Neural Network

November 22, 2017

The U.S. and China are leading the race toward productive quantum computing, but it's early enough that ultimate leadership is still something of an open questi Read more…

By Tiffany Trader

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

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

Leading Solution Providers

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

Perspective: What Really Happened at SC17?

November 22, 2017

SC is over. Now comes the myriad of follow-ups. Inboxes are filled with templated emails from vendors and other exhibitors hoping to win a place in the post-SC thinking of booth visitors. Attendees of tutorials, workshops and other technical sessions will be inundated with requests for feedback. Read more…

By Andrew Jones

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

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

IBM Begins Power9 Rollout with Backing from DOE, Google

December 6, 2017

After over a year of buildup, IBM is unveiling its first Power9 system based on the same architecture as the Department of Energy CORAL supercomputers, Summit a Read more…

By Tiffany Trader

Tensors Come of Age: Why the AI Revolution Will Help HPC

November 13, 2017

Thirty years ago, parallel computing was coming of age. A bitter battle began between stalwart vector computing supporters and advocates of various approaches to parallel computing. IBM skeptic Alan Karp, reacting to announcements of nCUBE’s 1024-microprocessor system and Thinking Machines’ 65,536-element array, made a public $100 wager that no one could get a parallel speedup of over 200 on real HPC workloads. Read more…

By John Gustafson & Lenore Mullin

Flipping the Flops and Reading the Top500 Tea Leaves

November 13, 2017

The 50th edition of the Top500 list, the biannual publication of the world’s fastest supercomputers based on public Linpack benchmarking results, was released 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

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