The MathWorks Gets Serious About Distributed Computing

By Michael Feldman

October 21, 2008

Scientific computing is quickly moving to parallel platforms and most software vendors are following suit. The MathWorks, which started parallelizing MATLAB and the company’s other numerical and scientific computing products four years ago, is now setting its sights on cluster and grid computing — and even computing in the cloud. With this in mind, MATLAB has recently been enhanced to work more intimately with distributed computing environments.

The enhancements consist of refinements to The MathWorks’ Parallel Computing Toolbox and MATLAB Distributed Computing Server that allow MATLAB sessions to run transparently over cluster and grid platforms. In addition, new MATLAB compiler and builder upgrades now let developers incorporate MATLAB libraries or functions into standalone executables, which can then be run on clusters or grids, themselves.

The latest MATLAB upgrade includes built-in support for the European EGEE grid (Enabling Grids for E-sciencE). This was accomplished by integrating the Parallel Computing Toolbox and MATLAB Distributed Computing Server with EGEE’s middleware, gLite. This enables MATLAB parallel applications to utilize the European grid infrastructure while running from the desktop. Since EGEE contains more than 70,000 CPUs spread across the continent, that represents almost unlimited computing power for an application.

It’s also now possible for MATLAB users to tap Amazon’s Elastic Compute Cloud. This requires a little more fiddling than hooking up to EGEE, since a system admin person will be required to deal with EC2 licensing and network issues. The MathWorks has written a technical paper on how to configure its products for EC2 and has a consulting service available to help you get started. And while EC2 is not specifically geared for scientific workloads, it might provide a useful platform for loosely-coupled, but highly-scalable technical computing applications.

Making MATLAB cluster- and grid-friendly solves the problems of two related groups of customers: desktop technical computing users and traditional HPC users. The desktop contingent — engineers, analysts, scientific algorithm developers — are already heavily invested in MATLAB products, but their challenges are growing larger. “The problem they have today is that their applications exceed the capacity of their desktop machines,” explains Silvina Grad-Freilich, manager of parallel computing and application deployment marketing at The MathWorks. In many cases they want to move up to HPC clusters, but would rather not leave their familiar MATLAB environment behind.

Traditional supercomputing users, on the other hand, are looking for ease of programming, but don’t want to give up the portability and scalability of the traditional MPI/C and Fortran model. “They want a simple technical computing environment so that they can focus on their science and not on the parallel programming aspects of the problem,” says Grad-Freilich.

Whether on a local cluster or a distributed grid, the underlying model is essentially the same: Use MATLAB parallel constructs and libraries to distribute workloads off the desktop. The way this is accomplished is via the MATLAB Distributed Computing Server, which manages remote MATLAB workers in a compute cluster. A remote worker is essentially the same as a desktop MATLAB process, but it operates remotely and runs its own process in parallel. In truth, multiple workers can also be run locally on the desktop if the user wants to take advantage of multiple CPU cores and doesn’t require the level of parallelism of a distributed solution.

To the MATLAB user, the execution of the workers is usually transparent. Their presence and location is managed underneath the covers and is determined by the hardware configuration visible to MATLAB. The configuration is selected by the user before beginning a MATLAB session if something other than the default setup is required. For example, if a user wants to override his default configuration — say his desktop — he/she could select a local cluster, a remote cluster, or even Amazon’s EC2. When the user initiates the session, any parallelism encountered in the software will try to take advantage of the hardware resources available.

There are multiple ways to inject parallelism into a MATLAB program depending on the nature of the problem and how hard the developers want to work. If they don’t want to make any extra effort, developers can just rely on the latest versions of the MATLAB libraries (the Optimization Toolbox and Genetic Algorithm and Direct Search Toolbox), which come pre-parallelized. No application code changes are needed. If developers are willing to make some minimal changes, they can employ MATLAB parallel constructs in their own application code to achieve additional parallelization. The parallel-for loop (parfor) can be used to execute a loop in parallel, while the new spmd (single program, multiple data) construct allows a developer to distribute data, such as large matrices or arrays, and their associated operations across a distributed system.

Application code and the pre-built MATLAB toolbox libraries are portable across desktops, clusters and grids, since the low-level parallelization is performed by the runtime system based on the configuration resources it sees. Even for a single-core CPU environment, MATLAB is smart enough to fall back to serial execution when it encounters parallel code. Developers can insist on parallelization by specifying a number of workers to employ for a particular instance of a parfor or spmd construct. In this case, if the workers are not available (not enough resources or not enough licenses), an error is thrown back to the application, which then must deal with it.

Another way The MathWorks is expanding MATLAB’s horizons is by leveraging this new distributed functionality for standalone applications. Using the MATLAB compiler and builder, developers can construct MATLAB executables or shared libraries, which can be hooked into C, Fortran, or even Java applications. The resulting programs can take advantage of MATLAB’s parallelization abilities while maintaining portability across different platforms.

For example, a quantitative analyst (quant) could develop a MATLAB-based financial model on his or her desktop and then incorporate that model into a portfolio manager’s high-level spreadsheet application. The idea is an old one in software engineering: build a repository of portable software libraries to be used for a wide range of applications. In this case, since the libraries can utilize MATLAB’s distributed computing capabilities, it becomes a path to parallelization.

There are no royalty fees associated with deployed MATLAB code. But the end user has to buy enough MATLAB worker licenses to support the level of parallelization required by the application. A worker license is checked out from the license manager when a worker starts up and is returned to the pool when the worker is shut down. The hardware that the application is being executed upon is only indirectly related to the number of licenses purchased. It’s up to the user how to map workers to hardware.

Loren Dean, director in the MATLAB development organization, says their general recommendation is to map one worker per socket. And although MATLAB supports multithreading to some extent, one computational thread per worker is probably optimal in most cases, especially if the application is memory bound. While in many cases, that means cores are going to be idle, the economics of distributed computing may allow for such inefficiencies. Says Dean: “When you look at the cloud and grid resources that are becoming available, for the most part, that’s all about multi-processing. So when you really want to have once piece of code that’s going to scale naturally, multi-processing just seems more logical.”

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!

At SC19: What Is UrgentHPC and Why Is It Needed?

November 14, 2019

The UrgentHPC workshop, taking place Sunday (Nov. 17) at SC19, is focused on using HPC and real-time data for urgent decision making in response to disasters such as wildfires, flooding, health emergencies, and accidents. We chat with organizer Nick Brown, research fellow at EPCC, University of Edinburgh, to learn more. Read more…

By Tiffany Trader

China’s Tencent Server Design Will Use AMD Rome

November 13, 2019

Tencent, the Chinese cloud giant, said it would use AMD’s newest Epyc processor in its internally-designed server. The design win adds further momentum to AMD’s bid to erode rival Intel Corp.’s dominance of the glo Read more…

By George Leopold

NCSA Industry Conference Recap – Part 1

November 13, 2019

Industry Program Director Brendan McGinty welcomed guests to the annual National Center for Supercomputing Applications (NCSA) Industry Conference, October 8-10, on the University of Illinois campus in Urbana (UIUC). One hundred seventy from 40 organizations attended the invitation-only, two-day event. Read more…

By Elizabeth Leake, STEM-Trek

Cray, Fujitsu Both Bringing Fujitsu A64FX-based Supercomputers to Market in 2020

November 12, 2019

The number of top-tier HPC systems makers has shrunk due to a steady march of M&A activity, but there is increased diversity and choice of processing components with Intel Xeon, AMD Epyc, IBM Power, and Arm server ch Read more…

By Tiffany Trader

Intel AI Summit: New ‘Keem Bay’ Edge VPU, AI Product Roadmap

November 12, 2019

At its AI Summit today in San Francisco, Intel touted a raft of AI training and inference hardware for deployments ranging from cloud to edge and designed to support organizations at various points of their AI journeys. The company revealed its Movidius Myriad Vision Processing Unit (VPU)... Read more…

By Doug Black

AWS Solution Channel

Making High Performance Computing Affordable and Accessible for Small and Medium Businesses with HPC on AWS

High performance computing (HPC) brings a powerful set of tools to a broad range of industries, helping to drive innovation and boost revenue in finance, genomics, oil and gas extraction, and other fields. Read more…

IBM Accelerated Insights

Help HPC Work Smarter and Accelerate Time to Insight

 

[Attend the IBM LSF & HPC User Group Meeting at SC19 in Denver on November 19]

To recklessly misquote Jane Austen, it is a truth, universally acknowledged, that a company in possession of a highly complex problem must be in want of a massive technical computing cluster. Read more…

SIA Recognizes Robert Dennard with 2019 Noyce Award

November 12, 2019

If you don’t know what Dennard Scaling is, the chances are strong you don’t labor in electronics. Robert Dennard, longtime IBM researcher, inventor of the DRAM and the fellow for whom Dennard Scaling was named, is th Read more…

By John Russell

Cray, Fujitsu Both Bringing Fujitsu A64FX-based Supercomputers to Market in 2020

November 12, 2019

The number of top-tier HPC systems makers has shrunk due to a steady march of M&A activity, but there is increased diversity and choice of processing compon Read more…

By Tiffany Trader

Intel AI Summit: New ‘Keem Bay’ Edge VPU, AI Product Roadmap

November 12, 2019

At its AI Summit today in San Francisco, Intel touted a raft of AI training and inference hardware for deployments ranging from cloud to edge and designed to support organizations at various points of their AI journeys. The company revealed its Movidius Myriad Vision Processing Unit (VPU)... Read more…

By Doug Black

IBM Adds Support for Ion Trap Quantum Technology to Qiskit

November 11, 2019

After years of percolating in the shadow of quantum computing research based on superconducting semiconductors – think IBM, Rigetti, Google, and D-Wave (quant Read more…

By John Russell

Tackling HPC’s Memory and I/O Bottlenecks with On-Node, Non-Volatile RAM

November 8, 2019

On-node, non-volatile memory (NVRAM) is a game-changing technology that can remove many I/O and memory bottlenecks and provide a key enabler for exascale. That’s the conclusion drawn by the scientists and researchers of Europe’s NEXTGenIO project, an initiative funded by the European Commission’s Horizon 2020 program to explore this new... Read more…

By Jan Rowell

MLPerf Releases First Inference Benchmark Results; Nvidia Touts its Showing

November 6, 2019

MLPerf.org, the young AI-benchmarking consortium, today issued the first round of results for its inference test suite. Among organizations with submissions wer Read more…

By John Russell

Azure Cloud First with AMD Epyc Rome Processors

November 6, 2019

At Ignite 2019 this week, Microsoft's Azure cloud team and AMD announced an expansion of their partnership that began in 2017 when Azure debuted Epyc-backed instances for storage workloads. The fourth-generation Azure D-series and E-series virtual machines previewed at the Rome launch in August are now generally available. Read more…

By Tiffany Trader

Nvidia Launches Credit Card-Sized 21 TOPS Jetson System for Edge Devices

November 6, 2019

Nvidia has launched a new addition to its Jetson product line: a credit card-sized (70x45mm) form factor delivering up to 21 trillion operations/second (TOPS) o Read more…

By Doug Black

In Memoriam: Steve Tuecke, Globus Co-founder

November 4, 2019

HPCwire is deeply saddened to report that Steve Tuecke, longtime scientist at Argonne National Lab and University of Chicago, has passed away at age 52. Tuecke Read more…

By Tiffany Trader

Supercomputer-Powered AI Tackles a Key Fusion Energy Challenge

August 7, 2019

Fusion energy is the Holy Grail of the energy world: low-radioactivity, low-waste, zero-carbon, high-output nuclear power that can run on hydrogen or lithium. T Read more…

By Oliver Peckham

Using AI to Solve One of the Most Prevailing Problems in CFD

October 17, 2019

How can artificial intelligence (AI) and high-performance computing (HPC) solve mesh generation, one of the most commonly referenced problems in computational engineering? A new study has set out to answer this question and create an industry-first AI-mesh application... Read more…

By James Sharpe

Cray Wins NNSA-Livermore ‘El Capitan’ Exascale Contract

August 13, 2019

Cray has won the bid to build the first exascale supercomputer for the National Nuclear Security Administration (NNSA) and Lawrence Livermore National Laborator Read more…

By Tiffany Trader

DARPA Looks to Propel Parallelism

September 4, 2019

As Moore’s law runs out of steam, new programming approaches are being pursued with the goal of greater hardware performance with less coding. The Defense Advanced Projects Research Agency is launching a new programming effort aimed at leveraging the benefits of massive distributed parallelism with less sweat. Read more…

By George Leopold

AMD Launches Epyc Rome, First 7nm CPU

August 8, 2019

From a gala event at the Palace of Fine Arts in San Francisco yesterday (Aug. 7), AMD launched its second-generation Epyc Rome x86 chips, based on its 7nm proce Read more…

By Tiffany Trader

D-Wave’s Path to 5000 Qubits; Google’s Quantum Supremacy Claim

September 24, 2019

On the heels of IBM’s quantum news last week come two more quantum items. D-Wave Systems today announced the name of its forthcoming 5000-qubit system, Advantage (yes the name choice isn’t serendipity), at its user conference being held this week in Newport, RI. Read more…

By John Russell

Ayar Labs to Demo Photonics Chiplet in FPGA Package at Hot Chips

August 19, 2019

Silicon startup Ayar Labs continues to gain momentum with its DARPA-backed optical chiplet technology that puts advanced electronics and optics on the same chip Read more…

By Tiffany Trader

Crystal Ball Gazing: IBM’s Vision for the Future of Computing

October 14, 2019

Dario Gil, IBM’s relatively new director of research, painted a intriguing portrait of the future of computing along with a rough idea of how IBM thinks we’ Read more…

By John Russell

Leading Solution Providers

ISC 2019 Virtual Booth Video Tour

CRAY
CRAY
DDN
DDN
DELL EMC
DELL EMC
GOOGLE
GOOGLE
ONE STOP SYSTEMS
ONE STOP SYSTEMS
PANASAS
PANASAS
VERNE GLOBAL
VERNE GLOBAL

Intel Confirms Retreat on Omni-Path

August 1, 2019

Intel Corp.’s plans to make a big splash in the network fabric market for linking HPC and other workloads has apparently belly-flopped. The chipmaker confirmed to us the outlines of an earlier report by the website CRN that it has jettisoned plans for a second-generation version of its Omni-Path interconnect... Read more…

By Staff report

Kubernetes, Containers and HPC

September 19, 2019

Software containers and Kubernetes are important tools for building, deploying, running and managing modern enterprise applications at scale and delivering enterprise software faster and more reliably to the end user — while using resources more efficiently and reducing costs. Read more…

By Daniel Gruber, Burak Yenier and Wolfgang Gentzsch, UberCloud

Dell Ramps Up HPC Testing of AMD Rome Processors

October 21, 2019

Dell Technologies is wading deeper into the AMD-based systems market with a growing evaluation program for the latest Epyc (Rome) microprocessors from AMD. In a Read more…

By John Russell

Rise of NIH’s Biowulf Mirrors the Rise of Computational Biology

July 29, 2019

The story of NIH’s supercomputer Biowulf is fascinating, important, and in many ways representative of the transformation of life sciences and biomedical res Read more…

By John Russell

Xilinx vs. Intel: FPGA Market Leaders Launch Server Accelerator Cards

August 6, 2019

The two FPGA market leaders, Intel and Xilinx, both announced new accelerator cards this week designed to handle specialized, compute-intensive workloads and un Read more…

By Doug Black

When Dense Matrix Representations Beat Sparse

September 9, 2019

In our world filled with unintended consequences, it turns out that saving memory space to help deal with GPU limitations, knowing it introduces performance pen Read more…

By James Reinders

With the Help of HPC, Astronomers Prepare to Deflect a Real Asteroid

September 26, 2019

For years, NASA has been running simulations of asteroid impacts to understand the risks (and likelihoods) of asteroids colliding with Earth. Now, NASA and the European Space Agency (ESA) are preparing for the next, crucial step in planetary defense against asteroid impacts: physically deflecting a real asteroid. Read more…

By Oliver Peckham

Cerebras to Supply DOE with Wafer-Scale AI Supercomputing Technology

September 17, 2019

Cerebras Systems, which debuted its wafer-scale AI silicon at Hot Chips last month, has entered into a multi-year partnership with Argonne National Laboratory and Lawrence Livermore National Laboratory as part of a larger collaboration with the U.S. Department of Energy... Read more…

By Tiffany Trader

  • arrow
  • Click Here for More Headlines
  • arrow
Do NOT follow this link or you will be banned from the site!
Share This