OpenACC Starts to Gather Developer Mindshare

By Michael Feldman

May 17, 2012

PGI, Cray, and CAPS enterprise are moving quickly to get their new OpenACC-supported compilers into the hands of GPGPU developers. At NVIDIA’s GPU Technology Conference (GTC) this week, there was plenty of discussion around the new HPC accelerator framework, and all three OpenACC compiler makers, as well as NVIDIA, were talking up the technology.

Announced at the Supercomputing Conference (SC11) last November, OpenACC is an open standard API developed by NVIDIA, PGI, Cray, and CAPS, to provide a high-level programming framework for programming accelerators like GPUs. OpenACC uses compiler directives, which programmers insert into high-level source (e.g., C, C++ or Fortran), to tell the compiler to execute specific pieces of the code on the accelerator hardware.

GTC conference-goers had plenty of opportunity to encounter OpenACC this week. There two OpenACC tutorials for would-be developers, one by NVIDIA, and the other by CAPS enterprise. In addition, there were four other sessions hosted by Cray, CAPS, and PGI throughout the week. That’s not counting the numerous mentions OpenACC got during other presentations involving GPGPU programming.

The technology is still in its infancy though. The PGI and Cray compilers are pre-production versions. CAPS first commercial offering is just two weeks old.

The initial goal of OpenACC is to bring more developers (and codes) into GPU computing, especially those not being served by the lower-level programming frameworks like CUDA and OpenCL. While CUDA is widely used in universities and in the technical computing realm, and OpenCL is emerging as an open standard for parallel computing, neither is particular attractive to commercial developers.

Most programmers are used to writing high-level code that focuses on the problem at hand, without have to worry about the vagaries of the underlying hardware. That hardware independence is also what makes OpenACC attractive for codes that need to span different processor architectures.

That assumes, of course, that compiler will support multiple accelerator chips. The first crop of OpenACC-enabled compilers from PGI, CAPS and Cray only generate code for NVIDIA GPUs — not too surprising when you consider NVIDIA’s current dominance in HPC acceleration. However all of the compiler efforts plan to widen the aperture of hardware support.

CAPS is perhaps most aggressive in this regard. According to CAPS CTO François Bodin, his company plans to add OpenACC support for AMD GPUs, x86 multicore CPUs and even the Tegra 3 microprocessor, an ARM-GPU design that will be used to power an experimental HPC clusters at the Barcelona Supercomputing Center (BSC). Bodin also said that they have an Intel MIC (Many Integrated Core) port of OpenACC in the pipeline. All of these compiler ports should be available later this year.

PGI is keeping its OpenACC development plans a little closer to the vest. But according to PGI compiler engineer Michael Wolfe, they have received requests for OpenACC support for nearly every processor and co-processor used in high performance computing. The compiler maker will undoubtedly be developing some of these over the next year.

Likewise for Cray, although its OpenACC compiler support is focused on the underlying accelerators of its own XK6 supercomputers. At this point, that’s confined to NVIDIA GPUs. Cray (which also carries CAPS and PGI compilers for its customers) has a unique OpenACC offering in that it supports those directives in PGAS languages Co-Array Fortran and Unified Parallel C (UPC) on the XK6.

Besides its applicability to multiple hardware platforms, OpenACC is just plain easier to use when you have lots of existing code. For one thing, OpenACC lets you attack the acceleration in steps. CUDA and OpenCL ports usually require code rewrites of at least a sizeable chunk of the application being accelerated, using low-level APIs. With OpenACC, the programmer just has to insert high-level directives into existing source, and this can be done iteratively, gradually putting more and more of the code under OpenACC control. This, say, PGI’s Wolfe, is “a hell of a lot more productive” than the low-level approach.

Even at the national labs and research centers, where there are computer scientists aplenty, OpenACC is starting to be recognized as an easier path to bring acceleration to hundreds of thousands of line of legacy codes. NASA Ames is already using PGI’s compiler to speed up some of their CFD codes on one of their GPU clusters. And the upcoming deployments of multi-petaflop GPU-based supercomputers like “Titan” at Oak Ridge National Lab, should provide a lot more opportunities for OpenACC-based application development. Titan project director Buddy Bland is on record endorsing the technology for software development on that machine.

As with all parallel programming though, there’s no free lunch to be had. In general, the programmer is probably going to sacrifice some runtime performance (compared to CUDA, for example) for the sake of programmer productivity. But there seems to be a general consensus that intelligent use of directives can easily get you to within 10 or 15 percent the performance of a low-level implementation. But as CAPS’ Bodin explains, to get in that close, “you have to know what you’re doing.” On the other hand, as the compiler technology matures and developers get more adept with OpenACC, the performance gap could narrow even further.

The other problem is just a lack of accelerator diversity at the moment. With Intel MIC waiting in the wings, and AMD still pretty much a no-show with server-side GPUs, there’s no immediate need to support anything but NVIDIA’s GPU architecture right now. Worse, both Intel and AMD are backing other parallel computing frameworks that they are rolling into to their accelerator programs: OpenMP, Cilk Plus, and TBB for Intel; OpenCL and C++ AMP for AMD.

Fortunately, it probably doesn’t matter that Intel and AMD haven’t hopped on the OpenACC bandwagon. PGI and CAPS can still produce compilers targeting Intel MIC or AMD GPUs, or whatever else comes along. And as long as there are at least two compiler vendors offering such support, the community should be satisfied.

The end game, though, is to fold the OpenACC capabilities into OpenMP. If and when that happens, both Intel, AMD will throw their support behind it. OpenMP has been around for 15 years and is a true industry standard.

There is currently a Working Group on Accelerators in the OpenMP consortium, which is looking at incorporating accelerator directives into the next OpenMP release. And while those directives will be based on the OpenACC directives, they are not likely to be adopted as is. There’s a real risk that if the process gets drawn out much longer and OpenACC captures a critical mass of users, there will end up being two directive-based accelerator standards to choose from.

Twas ever thus.

Related Articles

CAPS Entreprise Now Supports OpenACC Standard

OpenMP Announces Improvements for Multicore and Accelerators

OpenACC Support Available With New PGI Accelerator Fortran and C Compilers

NVIDIA Announces Initial Results of Directives-Based GPU Computing Program

NVIDIA Eyes Post-CUDA Era of GPU Computing

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!

AI-Focused ‘Genius’ Supercomputer Installed at KU Leuven

April 24, 2018

Hewlett Packard Enterprise has deployed a new approximately half-petaflops supercomputer, named Genius, at Flemish research university KU Leuven. The system is built to run artificial intelligence (AI) workloads and, as Read more…

By Tiffany Trader

New Exascale System for Earth Simulation Introduced

April 23, 2018

After four years of development, the Energy Exascale Earth System Model (E3SM) will be unveiled today and released to the broader scientific community this month. The E3SM project is supported by the Department of Energy Read more…

By Staff

RSC Reports 500Tflops, Hot Water Cooled System Deployed at JINR

April 18, 2018

RSC, developer of supercomputers and advanced HPC systems based in Russia, today reported deployment of “the world's first 100% ‘hot water’ liquid cooled supercomputer” at Joint Institute for Nuclear Research (JI Read more…

By Staff

HPE Extreme Performance Solutions

Hybrid HPC is Speeding Time to Insight and Revolutionizing Medicine

High performance computing (HPC) is a key driver of success in many verticals today, and health and life science industries are extensively leveraging these capabilities. Read more…

New Device Spots Quantum Particle ‘Fingerprint’

April 18, 2018

Majorana particles have been observed by university researchers employing a device consisting of layers of magnetic insulators on a superconducting material. The advance opens the door to controlling the elusive particle Read more…

By George Leopold

AI-Focused ‘Genius’ Supercomputer Installed at KU Leuven

April 24, 2018

Hewlett Packard Enterprise has deployed a new approximately half-petaflops supercomputer, named Genius, at Flemish research university KU Leuven. The system is Read more…

By Tiffany Trader

Cray Rolls Out AMD-Based CS500; More to Follow?

April 18, 2018

Cray was the latest OEM to bring AMD back into the fold with introduction today of a CS500 option based on AMD’s Epyc processor line. The move follows Cray’ Read more…

By John Russell

IBM: Software Ecosystem for OpenPOWER is Ready for Prime Time

April 16, 2018

With key pieces of the IBM/OpenPOWER versus Intel/x86 gambit settling into place – e.g., the arrival of Power9 chips and Power9-based systems, hyperscaler sup Read more…

By John Russell

US Plans $1.8 Billion Spend on DOE Exascale Supercomputing

April 11, 2018

On Monday, the United States Department of Energy announced its intention to procure up to three exascale supercomputers at a cost of up to $1.8 billion with th Read more…

By Tiffany Trader

Cloud-Readiness and Looking Beyond Application Scaling

April 11, 2018

There are two aspects to consider when determining if an application is suitable for running in the cloud. The first, which we will discuss here under the title Read more…

By Chris Downing

Transitioning from Big Data to Discovery: Data Management as a Keystone Analytics Strategy

April 9, 2018

The past 10-15 years has seen a stark rise in the density, size, and diversity of scientific data being generated in every scientific discipline in the world. Key among the sciences has been the explosion of laboratory technologies that generate large amounts of data in life-sciences and healthcare research. Large amounts of data are now being stored in very large storage name spaces, with little to no organization and a general unease about how to approach analyzing it. Read more…

By Ari Berman, BioTeam, Inc.

IBM Expands Quantum Computing Network

April 5, 2018

IBM is positioning itself as a first mover in establishing the era of commercial quantum computing. The company believes in order for quantum to work, taming qu Read more…

By Tiffany Trader

FY18 Budget & CORAL-2 – Exascale USA Continues to Move Ahead

April 2, 2018

It was not pretty. However, despite some twists and turns, the federal government’s Fiscal Year 2018 (FY18) budget is complete and ended with some very positi Read more…

By Alex R. Larzelere

Inventor Claims to Have Solved Floating Point Error Problem

January 17, 2018

"The decades-old floating point error problem has been solved," proclaims a press release from inventor Alan Jorgensen. The computer scientist has filed for and Read more…

By Tiffany Trader

Researchers Measure Impact of ‘Meltdown’ and ‘Spectre’ Patches on HPC Workloads

January 17, 2018

Computer scientists from the Center for Computational Research, State University of New York (SUNY), University at Buffalo have examined the effect of Meltdown Read more…

By Tiffany Trader

How the Cloud Is Falling Short for HPC

March 15, 2018

The last couple of years have seen cloud computing gradually build some legitimacy within the HPC world, but still the HPC industry lies far behind enterprise I Read more…

By Chris Downing

Russian Nuclear Engineers Caught Cryptomining on Lab Supercomputer

February 12, 2018

Nuclear scientists working at the All-Russian Research Institute of Experimental Physics (RFNC-VNIIEF) have been arrested for using lab supercomputing resources to mine crypto-currency, according to a report in Russia’s Interfax News Agency. Read more…

By Tiffany Trader

Chip Flaws ‘Meltdown’ and ‘Spectre’ Loom Large

January 4, 2018

The HPC and wider tech community have been abuzz this week over the discovery of critical design flaws that impact virtually all contemporary microprocessors. T Read more…

By Tiffany Trader

How Meltdown and Spectre Patches Will Affect HPC Workloads

January 10, 2018

There have been claims that the fixes for the Meltdown and Spectre security vulnerabilities, named the KPTI (aka KAISER) patches, are going to affect applicatio Read more…

By Rosemary Francis

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

Deep Learning at 15 PFlops Enables Training for Extreme Weather Identification at Scale

March 19, 2018

Petaflop per second deep learning training performance on the NERSC (National Energy Research Scientific Computing Center) Cori supercomputer has given climate Read more…

By Rob Farber

Leading Solution Providers

Lenovo Unveils Warm Water Cooled ThinkSystem SD650 in Rampup to LRZ Install

February 22, 2018

This week Lenovo took the wraps off the ThinkSystem SD650 high-density server with third-generation direct water cooling technology developed in tandem with par Read more…

By Tiffany Trader

Fast Forward: Five HPC Predictions for 2018

December 21, 2017

What’s on your list of high (and low) lights for 2017? Volta 100’s arrival on the heels of the P100? Appearance, albeit late in the year, of IBM’s Power9? Read more…

By John Russell

AI Cloud Competition Heats Up: Google’s TPUs, Amazon Building AI Chip

February 12, 2018

Competition in the white hot AI (and public cloud) market pits Google against Amazon this week, with Google offering AI hardware on its cloud platform intended Read more…

By Doug Black

HPC and AI – Two Communities Same Future

January 25, 2018

According to Al Gara (Intel Fellow, Data Center Group), high performance computing and artificial intelligence will increasingly intertwine as we transition to Read more…

By Rob Farber

US Plans $1.8 Billion Spend on DOE Exascale Supercomputing

April 11, 2018

On Monday, the United States Department of Energy announced its intention to procure up to three exascale supercomputers at a cost of up to $1.8 billion with th Read more…

By Tiffany Trader

New Blueprint for Converging HPC, Big Data

January 18, 2018

After five annual workshops on Big Data and Extreme-Scale Computing (BDEC), a group of international HPC heavyweights including Jack Dongarra (University of Te Read more…

By John Russell

Momentum Builds for US Exascale

January 9, 2018

2018 looks to be a great year for the U.S. exascale program. The last several months of 2017 revealed a number of important developments that help put the U.S. Read more…

By Alex R. Larzelere

Google Chases Quantum Supremacy with 72-Qubit Processor

March 7, 2018

Google pulled ahead of the pack this week in the race toward "quantum supremacy," with the introduction of a new 72-qubit quantum processor called Bristlecone. Read more…

By Tiffany Trader

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