SC16 Preview: Modernizing, Modularizing Fortran Codes

By Mark Potts

November 9, 2016

The programming language Fortran has been in existence since 1957, and a large percentage of software that runs on HPC systems worldwide is written, at least in part, in Fortran. Since it has been in existence for so long, and so many scientists and engineers learned it early in their careers and have utilized it extensively, much of this code is not up to modern standards of software development.

Although there is no doubt that most of that code works well and runs fast, as codes have grown more complex and involve more developers, errors can easily be introduced. As I’ll discuss in greater detail next week at SC16, these types of errors can be greatly reduced with a more disciplined approach to software development.

Fortunately, the Fortran language has continued to evolve and has incorporated many of the most successful paradigms of more modern languages such as C++ and Java, while still retaining its overall speed and general simplicity. For example, the 2003 standard, which greatly enhanced Fortran 95, introduced pointers to procedures, object-oriented programming, and better interoperability with C among other things.

The new object-oriented paradigm is particularly useful when refactoring existing Fortran code to make it more modular and robust. It is also fairly straight-forward to implement!

It is fair to ask, “Why change something that’s not broken?” In some cases, it may not make any sense to refactor legacy code, but if the code is still being developed actively, and there are multiple contributors to the code base, refactoring with OOP standards makes a lot of sense. Perhaps the most important reason to refactor is to reduce code duplication. There is a tendency among many programmers to simply copy a subroutine or function that does 90% of what is needed and then modify the new routine to fit the rest. This can lead to lots of headaches if something in the original routine needs to be changed or added, and often leads to discrepancies that are hard to trace. Fortunately, using the classes, inheritance, and polymorphism now available in Fortran 2003, this dilemma can be almost completely avoided.

When two or more files contain very similar routines, it is usually possible to combine the shared functionality in a base class and then add derived classes that “finish off” the calculation in their own unique manner. By eliminating the copied code, the new classes will now make use of the same core computation, which can be easily modified for all classes at once and also lends itself very well to the addition of unit testing—a big component to any modern software design. The figures below show a very simple example of this sort of combination using an abstract base class along with two derived classes.

Figure 1: This is a simple abstract base class with a procedure (process_most_data) defined to handle the common core of computation.


Figure 2: Sample derived classes (sample_one_class and sample_two_class)

Both derived classes inherit the process_most_data procedure from the abstract base class, and both use that function directly in their own version of process_data. The “=>” seen under the extends command refers to the fact that the process_data procedure required in the base class has been implemented locally and renamed within the specific derived class. Figure 3 below shows a sample driver routine that allocates both classes, sets the initial data value for each and then has each instance process the data according to its version of the procedure.

Figure 3: Sample driver program that calls two derived classes and processes sample data.

When compiled and run, the output looks as follows:

first data is now    33.000000000000000
second data is now    22.000000000000000

Both derived classes (first and second) start with data equal to 10.0 when each is called to run the process_data routine. Each then runs through the common core functionality provided by the abstract base class and then performs its own individual calculation. In the case of first, that is multiply by 3.0; for second, it is multiply by 2.0.

While this is clearly a trivial example of combining common calculations into a single procedure, it provides a template for doing so in an object-oriented manner using Fortran. Because abstract classes cannot be instantiated, the use of an abstract base class in this instance also ensures that no future developer will accidentally try to use it rather than a fully defined derived class.

Extending this idea even further, unit tests can now be added to these new classes. Using pFUnit, which is an open source unit-testing framework for Fortran, a unit test for sample_one_class would look something like Figure 4.

Figure 4

In the sample unit test shown in Figure 4, most of the text is boilerplate, with only the highlighted red text indicating the tailoring for the sample class. The class is included at the top of the file, it is defined under @TestCase, allocated in setup, and deallocated in tearDown—all with very simple additions to the boilerplate. The actual test takes place in testSampleOne where the process_data procedure is called after starting with an initial data value of 10.0. The AssertEqual command checks that the value of data matches 33.0, as it should after the process_data procedure is complete. This sort of test will run extremely quickly and will provide an early warning sign if the base class is changed without making sure that all derived classes are updated appropriately.

I’ll be presenting on this topic at SC16 on Wednesday, Nov. 16 at 4 p.m., and would be happy to answer your questions. Please stop by!

About the Author:

Mark Potts, Ph.D., is a Senior Computational Scientist at RedLine Performance Solutions, LLC. Dr. Potts has over 20 years of software development experience, including more than 15 years of work in research and application development using HPC systems. He joined Redline Performance Solutions in 2015 and has since been working with NOAA to accelerate and modernize their Gridpoint Statistical Interpolation (GSI) analysis code used to assimilate data into operational weather models.

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!

What’s New in HPC Research: Rock Art, Protein Design, Genome Assembly & More

June 25, 2019

In this bimonthly feature, HPCwire highlights newly published research in the high-performance computing community and related domains. From parallel programming to exascale to quantum computing, the details are here. Read more…

By Oliver Peckham

Azure Benchmarks HC-series Across 20,000 cores for HPC

June 25, 2019

Cloud provider Microsoft Azure’s push into HPC continues to gain momentum. In a blog last week, Evan Burness, principal program manager, Azure HPC, announced HC-series Virtual Machine are now available in West US 2 and Read more…

By John Russell

MLPerf Expands Toolset; Launches Inferencing Suite

June 24, 2019

MLPerf today launched a benchmark suite for inferencing, v0.5, which joins the MLPerf training suite launched a little over a year ago. The new inferencing benchmark, which has been anticipated, covers models applicable Read more…

By John Russell

HPE Extreme Performance Solutions

HPE and Intel® Omni-Path Architecture: How to Power a Cloud

Learn how HPE and Intel® Omni-Path Architecture provide critical infrastructure for leading Nordic HPC provider’s HPCFLOW cloud service.

For decades, HPE has been at the forefront of high-performance computing, and we’ve powered some of the fastest and most robust supercomputers in the world. Read more…

IBM Accelerated Insights

Avoid AI Redo’s by Starting with the Right Infrastructure

Do you know if you have the right infrastructure for AI? Many organizations don’t have it. In a recent IDC survey, “77.1% of respondents say they ran into one or more limitations with their AI infrastructure on-premise and 90.3% ran into compute limitations in the cloud.” Read more…

A Behind-the-Scenes Look at the Hardware That Powered the Black Hole Image

June 24, 2019

Two months ago, the first-ever image of a black hole took the internet by storm. A team of scientists took years to produce and verify the striking image – and now, Tom Coughlin (on behalf of Supermicro) has provided a Read more…

By Oliver Peckham

MLPerf Expands Toolset; Launches Inferencing Suite

June 24, 2019

MLPerf today launched a benchmark suite for inferencing, v0.5, which joins the MLPerf training suite launched a little over a year ago. The new inferencing benc Read more…

By John Russell

Is Weather and Climate Prediction the Perfect ‘Pilot’ for Exascale?

June 21, 2019

At ISC 2019 this week, Peter Bauer – deputy director of research for the European Centre for Medium-Range Weather Forecasts (ECMWF) – outlined an ambitious Read more…

By Oliver Peckham

ISC Keynote: Thomas Sterling’s Take on Whither HPC

June 20, 2019

Entertaining, insightful, and unafraid to launch the occasional verbal ICBM, HPC pioneer Thomas Sterling delivered his 16th annual closing keynote at ISC yesterday. He explored, among other things: exascale machinations; quantum’s bubbling money pot; Arm’s new HPC viability; Europe’s... Read more…

By John Russell

IBM Claims No. 1 Commercial Supercomputer with Total Oil & Gas System 

June 20, 2019

IBM can now boast not only the two most powerful supercomputers in the world, it also has claimed the top spot for a supercomputer used in a commercial setting. Read more…

By Staff Report

HPC on Pace for 5-Year 6.8% CAGR; Guess Which Hyperscaler Spent $10B on IT Last Year?

June 20, 2019

In the neck-and-neck horse race for HPC server market share, HPE has hung on to a slim, shrinking lead over Dell EMC – but if server and storage market shares Read more…

By Doug Black

ISC 2019 Research Paper Award Winners Announced

June 19, 2019

At the 2019 International Supercomputing Conference (ISC) in Frankfurt this week, the ISC committee awarded the event's top prizes for outstanding research pape Read more…

By Oliver Peckham

ISC Keynote: The Algorithms of Life – Scientific Computing for Systems Biology

June 19, 2019

Systems biology has existed loosely under many definitions for a couple of decades. It’s the notion of describing living systems using first-principle physics Read more…

By John Russell

Summit Achieves 445 Petaflops on New ‘HPL-AI’ Benchmark

June 19, 2019

Summit -- the world's top-ranking supercomputer -- has been used to test-drive a new mixed-precision Linpack benchmark, which for now is being called HPL-AI. Traditionally, supercomputer performance is measured using the High-Performance Linpack (HPL) benchmark, which is the basis for the Top500 list that biannually ranks world's fastest supercomputers. Read more…

By Oliver Peckham

High Performance (Potato) Chips

May 5, 2006

In this article, we focus on how Procter & Gamble is using high performance computing to create some common, everyday supermarket products. Tom Lange, a 27-year veteran of the company, tells us how P&G models products, processes and production systems for the betterment of consumer package goods. Read more…

By Michael Feldman

Cray, AMD to Extend DOE’s Exascale Frontier

May 7, 2019

Cray and AMD are coming back to Oak Ridge National Laboratory to partner on the world’s largest and most expensive supercomputer. The Department of Energy’s Read more…

By Tiffany Trader

Graphene Surprises Again, This Time for Quantum Computing

May 8, 2019

Graphene is fascinating stuff with promise for use in a seeming endless number of applications. This month researchers from the University of Vienna and Institu Read more…

By John Russell

Why Nvidia Bought Mellanox: ‘Future Datacenters Will Be…Like High Performance Computers’

March 14, 2019

“Future datacenters of all kinds will be built like high performance computers,” said Nvidia CEO Jensen Huang during a phone briefing on Monday after Nvidia revealed scooping up the high performance networking company Mellanox for $6.9 billion. Read more…

By Tiffany Trader

AMD Verifies Its Largest 7nm Chip Design in Ten Hours

June 5, 2019

AMD announced last week that its engineers had successfully executed the first physical verification of its largest 7nm chip design – in just ten hours. The AMD Radeon Instinct Vega20 – which boasts 13.2 billion transistors – was tested using a TSMC-certified Calibre nmDRC software platform from Mentor. Read more…

By Oliver Peckham

It’s Official: Aurora on Track to Be First US Exascale Computer in 2021

March 18, 2019

The U.S. Department of Energy along with Intel and Cray confirmed today that an Intel/Cray supercomputer, "Aurora," capable of sustained performance of one exaf Read more…

By Tiffany Trader

Deep Learning Competitors Stalk Nvidia

May 14, 2019

There is no shortage of processing architectures emerging to accelerate deep learning workloads, with two more options emerging this week to challenge GPU leader Nvidia. First, Intel researchers claimed a new deep learning record for image classification on the ResNet-50 convolutional neural network. Separately, Israeli AI chip startup Read more…

By George Leopold

TSMC and Samsung Moving to 5nm; Whither Moore’s Law?

June 12, 2019

With reports that Taiwan Semiconductor Manufacturing Co. (TMSC) and Samsung are moving quickly to 5nm manufacturing, it’s a good time to again ponder whither goes the venerable Moore’s law. Shrinking feature size has of course been the primary hallmark of achieving Moore’s law... Read more…

By John Russell

Leading Solution Providers

ISC 2019 Virtual Booth Video Tour


Nvidia Embraces Arm, Declares Intent to Accelerate All CPU Architectures

June 17, 2019

As the Top500 list was being announced at ISC in Frankfurt today with an upgraded petascale Arm supercomputer in the top third of the list, Nvidia announced its Read more…

By Tiffany Trader

The Case Against ‘The Case Against Quantum Computing’

January 9, 2019

It’s not easy to be a physicist. Richard Feynman (basically the Jimi Hendrix of physicists) once said: “The first principle is that you must not fool yourse Read more…

By Ben Criger

Top500 Purely Petaflops; US Maintains Performance Lead

June 17, 2019

With the kick-off of the International Supercomputing Conference (ISC) in Frankfurt this morning, the 53rd Top500 list made its debut, and this one's for petafl Read more…

By Tiffany Trader

Cray – and the Cray Brand – to Be Positioned at Tip of HPE’s HPC Spear

May 22, 2019

More so than with most acquisitions of this kind, HPE’s purchase of Cray for $1.3 billion, announced last week, seems to have elements of that overused, often Read more…

By Doug Black and Tiffany Trader

Intel Launches Cascade Lake Xeons with Up to 56 Cores

April 2, 2019

At Intel's Data-Centric Innovation Day in San Francisco (April 2), the company unveiled its second-generation Xeon Scalable (Cascade Lake) family and debuted it Read more…

By Tiffany Trader

Announcing four new HPC capabilities in Google Cloud Platform

April 15, 2019

When you’re running compute-bound or memory-bound applications for high performance computing or large, data-dependent machine learning training workloads on Read more…

By Wyatt Gorman, HPC Specialist, Google Cloud; Brad Calder, VP of Engineering, Google Cloud; Bart Sano, VP of Platforms, Google Cloud

In Wake of Nvidia-Mellanox: Xilinx to Acquire Solarflare

April 25, 2019

With echoes of Nvidia’s recent acquisition of Mellanox, FPGA maker Xilinx has announced a definitive agreement to acquire Solarflare Communications, provider Read more…

By Doug Black

Nvidia Claims 6000x Speed-Up for Stock Trading Backtest Benchmark

May 13, 2019

A stock trading backtesting algorithm used by hedge funds to simulate trading variants has received a massive, GPU-based performance boost, according to Nvidia, Read more…

By Doug Black

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