Nielsen and Intel Migrate HPC Efficiency and Data Analytics to Big Data

By Rob Farber

May 16, 2016

Nielsen has collaborated with Intel to migrate important pieces of HPC technology into Nielsen’s big-data analytic workflows including MPI, mature numerical libraries from NAG (the Numerical Algorithms Group), as well as custom C++ analytic codes. This complementary hybrid approach integrates the benefits of Hadoop data management and workflow scheduling with an extensive pool of HPC tools and C/C++ capabilities for analytic applications. In particular, the use of MPI reduces latency, permits reuse of the Hadoop servers, and co-locates the MPI applications close to the data.

John Mansour, vice president, Advanced Solutions Group, at Nielsen became interested in the integration of both Hadoop and HPC technology to enable faster, better, and more powerful analysis of the huge volumes of data collected by Nielsen as part of their Consumer Package Goods (CPG) market research. Nielsen is well-known for the ‘Nielsen ratings’ of audience measurement in Television, Radio, and online content. The company also provides Retail Measurement Services (RMS) that track and report on CPG sales around the world to understand sales performance. The success of Nielsen’s efforts are presented in his talk Bridging the Worlds of HPC and Big-Data at Supercomputing 2015.

Nielsen already utilizes the Cloudera Hadoop infrastructure to ingest and manage a daily deluge of data used in their market research. What Nielsen wanted was to make this infrastructure HPC-friendly so the wealth of scientific and data-analytic HPC codes created since the 1960s could be added to the Nielsen set of computational tools. This required integrating MPI (Message Passing Interface), which is the distributed framework utilized by the HPC community, into the Cloudera Hadoop framework. This integration allows Nielsen the choice of using C/C++ MPI in addition to Spark and Map-Reduce for situations that either require the performance or are a team’s preferred language.

Nielsen thinks Integrating Hadoop and MPI brings together the best of two complementary technologies. This integration will provide the data management capabilities of Hadoop with the performance of native MPI applications on the same cluster. Intel and Cloudera plan to provide production support for this integration in future releases of their software while Nielsen continues to explore the possibilities that such an integration will have for their clients.
Nielsen thinks Integrating Hadoop and MPI brings together the best of two complementary technologies. This integration will provide the data management capabilities of Hadoop with the performance of native MPI applications on the same cluster. Intel and Cloudera plan to provide production support for this integration in future releases of their software while Nielsen continues to explore the possibilities that such an integration will have for their clients.

MPI has been designed and refined since the 1990s to remove as much of the communications overhead from distributed HPC applications as possible, while Hadoop and the cloud computing infrastructure in general has been designed to run in a big-way on COTS (Commodity Off The Shelf) hardware where fault- and latency-tolerance is a requirement. A successful integration of the two means that existing MPI and data analytic codes can be ported without having to be re-implemented in another language such as SPARK, and very importantly, the integration can occur without affecting existing operational cloud infrastructure.

The integration, performed in collaboration with Intel, is quite straight-forward from a high-level perspective: simply start a python script that requests resources based on a set of input parameters and writes out a machine file that can be utilized by mpiexec to run the MPI job. The script then starts the MPI run and cleans up resources upon completion.

In actuality, the process is more complicated as it is necessary to ensure the data is in the right place and that errors are correctly handled. Nielsen uses Cloudera’s llama as the application master and yarn as the resource manager.

The performance of MPI in the Nielsen Hadoop framework has been superb and is expected to get even better. In testing with other Hadoop technologies, Nielsen has found MPI to consistently perform better than the others. Speedups come from the use of C/C++, sophisticated numerical libraries such as those offered by the NAG Numerical Algorithms Group and MPI’s design for low-latency communications which help in tightly coupled communications such the reduction operations needed in regressions and machine learning applications. In a future publication Nielsen will provide more detailed performance comparisons but typically see about a factor of between 5 to 10 times in performance compared to SPARK 1.5.1.

All this work to date has been at the proof-of-concept (POC) phase. In particular, high-performance storage I/O has proven to be an issue with significant amounts of runtime – sometimes as much as 85% – being consumed by the data loads. The challenge is that HDFS, which is written in Java, appears to be a bottleneck. Nielsen is experimenting with different technologies including local file systems and new apis such as RecordService and libhdfs3. Unfortunately, there are issues using common MPI data methods like mpiio which present a problem in Hadoop.

In addition to optimizing I/O performance, Nielsen has demonstrated significant performance benefits preloading data into distributed shared memory using BOOST shared memory STL vectors. With a working MPI and ability to integrate existing C/C++ codes, Nielsen has opened the door to a wealth of computational tools and analytic packages. In particular, the NAG library is a well-known, highly-regarded numerical toolkit. For example, NAG offers routines for data cleaning (including imputation and outlier detection), data transformations (scaling, principal component analysis), clustering, classification, regression models and machine learning methods (neural networks, radial basis function, decision trees, nearest neighbors), and association rules plus a plethora of utility functions.

Author Bio:
Rob Farber is a global technology consultant and author with an extensive background in scientific and commercial HPC plus a long history of working with national labs and corporations. He can be reached at [email protected].

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!

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, code-named Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from its predecessors, including the red-hot H100 and A100 GPUs. Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. While Nvidia may not spring to mind when thinking of the quant Read more…

2024 Winter Classic: Meet the HPE Mentors

March 18, 2024

The latest installment of the 2024 Winter Classic Studio Update Show features our interview with the HPE mentor team who introduced our student teams to the joys (and potential sorrows) of the HPL (LINPACK) and accompany Read more…

Houston We Have a Solution: Addressing the HPC and Tech Talent Gap

March 15, 2024

Generations of Houstonian teachers, counselors, and parents have either worked in the aerospace industry or know people who do - the prospect of entering the field was normalized for boys in 1969 when the Apollo 11 missi Read more…

Apple Buys DarwinAI Deepening its AI Push According to Report

March 14, 2024

Apple has purchased Canadian AI startup DarwinAI according to a Bloomberg report today. Apparently the deal was done early this year but still hasn’t been publicly announced according to the report. Apple is preparing Read more…

Survey of Rapid Training Methods for Neural Networks

March 14, 2024

Artificial neural networks are computing systems with interconnected layers that process and learn from data. During training, neural networks utilize optimization algorithms to iteratively refine their parameters until Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, code-named Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. Wh Read more…

Houston We Have a Solution: Addressing the HPC and Tech Talent Gap

March 15, 2024

Generations of Houstonian teachers, counselors, and parents have either worked in the aerospace industry or know people who do - the prospect of entering the fi Read more…

Survey of Rapid Training Methods for Neural Networks

March 14, 2024

Artificial neural networks are computing systems with interconnected layers that process and learn from data. During training, neural networks utilize optimizat Read more…

PASQAL Issues Roadmap to 10,000 Qubits in 2026 and Fault Tolerance in 2028

March 13, 2024

Paris-based PASQAL, a developer of neutral atom-based quantum computers, yesterday issued a roadmap for delivering systems with 10,000 physical qubits in 2026 a Read more…

India Is an AI Powerhouse Waiting to Happen, but Challenges Await

March 12, 2024

The Indian government is pushing full speed ahead to make the country an attractive technology base, especially in the hot fields of AI and semiconductors, but Read more…

Charles Tahan Exits National Quantum Coordination Office

March 12, 2024

(March 1, 2024) My first official day at the White House Office of Science and Technology Policy (OSTP) was June 15, 2020, during the depths of the COVID-19 loc Read more…

AI Bias In the Spotlight On International Women’s Day

March 11, 2024

What impact does AI bias have on women and girls? What can people do to increase female participation in the AI field? These are some of the questions the tech Read more…

Alibaba Shuts Down its Quantum Computing Effort

November 30, 2023

In case you missed it, China’s e-commerce giant Alibaba has shut down its quantum computing research effort. It’s not entirely clear what drove the change. 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…

Analyst Panel Says Take the Quantum Computing Plunge Now…

November 27, 2023

Should you start exploring quantum computing? Yes, said a panel of analysts convened at Tabor Communications HPC and AI on Wall Street conference earlier this y Read more…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a 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…

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…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia Read more…

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Leading Solution Providers

Contributors

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…

Training of 1-Trillion Parameter Scientific AI Begins

November 13, 2023

A US national lab has started training a massive AI brain that could ultimately become the must-have computing resource for scientific researchers. Argonne N Read more…

Shutterstock 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t 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…

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…

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…

Google Introduces ‘Hypercomputer’ to Its AI Infrastructure

December 11, 2023

Google ran out of monikers to describe its new AI system released on December 7. Supercomputer perhaps wasn't an apt description, so it settled on Hypercomputer Read more…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire