OpenCL Gains Ground On CUDA

By Michael Feldman

February 28, 2012

As the two major programming frameworks for GPU computing, OpenCL and CUDA have been competing for mindshare in the developer community for the past few years. Until recently, CUDA has attracted most of the attention from developers, especially in the high performance computing realm. But OpenCL software has now matured to the point where HPC practitioners are taking a second look.

Both OpenCL and CUDA provide a general-purpose model for data parallelism as well as low-level access to hardware, but only OpenCL provides an open, industry-standard framework. As such, it has garnered support from nearly all processor manufacturers including AMD, Intel, and NVIDIA, as well as others that serve the mobile and embedded computing markets. As a result, applications developed in OpenCL are now portable across a variety of GPUs and CPUs.

Although OpenCL 1.0 was introduced in December 2008, just a year and a half after the NVIDIA launched its first version of CUDA, OpenCL still trails CUDA in popularity by a wide margin, especially with regard to HPC. That is mostly due to a concerted effort by NVIDIA to establish CUDA as the dominant programming framework for GPU application development in this realm..

AMD has been the most vocal booster of OpenCL technology for technical computing, but it’s lack of a competitive product set for high-end GPU computing has muted that message. Thus far, OpenCL usage has been mostly relegated to client-side computing, especially for mobile platforms, which have increasingly incorporated GPU silicon into their designs. Apple, who initially developed OpenCL before handing it off to the open-standard Khronos Group, was instrumental in getting the technology off the ground.

The knock on OpenCL for HPC users has been lack of maturity, which has resulted in low performance, compared to CUDA. There is also the perception that support from the principle HPC chipmakers (Intel, AMD and NVIDIA) would be less than enthusiastic, at least for their high-end processors. In many ways, that’s still true, given that NVIDIA is devoting most of its attention to its home-grown CUDA software, while Intel seems to have settled on its own parallel programming frameworks, mainly Cilk Plus and Threading Building Blocks.

AMD though, continues to champion OpenCL, and some of their more recent compiler and library releases have improved performance considerably. In fact, Kyle Spafford, from the Future Technology Group at Oak Ridge National Lab (ORNL), has been benchmarking the two technologies for some time and is now convinced that OpenCL performance is now on par with that of CUDA. He recently presented his findings at Georgia Tech’s Keeneland Workshop.

Spafford’s ran ORNL’s Scalable Heterogeneous Computing Benchmark Suite (SHOC) that has been optimized for both CUDA and OpenCL, and found that OpenCL can match CUDA performance on most of the basic math kernels. He also found that OpenCL’s performance on some kernels, like SGEMM, has increased 10-fold since 2009. The one code that CUDA still has a significant performance advantage is that of the Fast Fourier Transform (FFT). Spafford attributes CUDA’s better FFT performance on its use of a fast intrinsic, with OpenCL implementation (NVIDIA’s in this case*) employing a slower, more accurate version. If the implementations are matched, the performance difference goes away, says Spafford.

Others have found similar behavior on stand-alone science applications. A research group at Dartmouth running a numerical model of gravitation waves with OpenCL and CUDA found similar performance between OpenCL and CUDA, in this case on Tesla GPUs and IBM’s Cell BE processors. In the resulting paper, the researchers conclude that “an OpenCL-based implementation delivers comparable performance to that based on a native SDK on both types of accelerator hardware.”

GPU software maker AccelerEyes has seen CUDA and OpenCL performance equalize. The company, which recently released OpenCL-powered beta versions of their two flagship software products, ArrayFire and Jacket, has found that for most kernel codes, the two technologies now exhibit similar performance. Like ORNL, they found FFT speed is still better on CUDA due to NVIDIA’s faster implementation, but AMD’s OpenCL compiler and libraries have improved considerably, both in scope and performance.

According to AccelerEyes CEO John Melonakos, over half of their customers develop their GPU-accelerated code on their PCs before deploying to a workstation or cluster, so the ability to support non-NVIDIA hardware can be quite useful. For example, customers using MacBooks as development platforms couldn’t run CUDA there because Apple has no NVIDIA GPU option on its latest laptops. And since the AMD OpenCL libraries that AccelerEyes used in their beta offerings work just fine on Intel CPUs, AMD CPUs, and NVIDIA GPUs, there are no hardware incompatibility issues.

Then there are users who are just unwilling to adopt vendor-specific software stacks such as CUDA. “There are a class of people who absolutely want to do GPU computing but are resistant to anything that is vendor-locked,” Melonakos told HPCwire. He says this is group that has jumped onto their OpenCL-based offerings first.

To counter that kind of perception, NVIDIA has recently opened up the CUDA compiler source code for third-party developers. Significantly though, NVIDIA is not putting its all-important CUDA math libraries, like CUBLAS and CUFFT, into the open source pot. According to Melonakos, the large and mature library set is CUDA’s real strength in the technical computing arena. Open source or not, NVIDIA still retains control of the CUDA software technology, which is why it is still perceived as a vendor-specific solution.

Even NVIDIA and Intel are hedging their bets with OpenCL though, with both vendors offering software hooks for their respective hardware. At this point, these companies are providing this support as a nod to their mobile computing developers (although Intel is reportedly working on a MIC processor port too). But since there is an increasing amount of cross-pollination between mobile and HPC these days, it’s not clear how developers will end up using these technologies.

In fact, if the mobile space latches onto OpenCL in a big way and it becomes the standard low-level solution for heterogenous computing, that could help speed its adoption at the high-end. Once OpenCL reaches a critical mass of acceptance in a volume market such as that, there will be a rapid increase in demand for robust compilers and libraries. As Melonakos put it: “I dont think OpenCL is going away.”

[Editor’s note: The original article erroneously stated that the SHOC benchmark work used AMD’s implementation of OpenCL, rather than NVIDIA’s. We regret the error.]

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!

UCSD Web-based Tool Tracking CA Wildfires Generates 1.5M Views

October 16, 2017

Tracking the wildfires raging in northern CA is an unpleasant but necessary part of guiding efforts to fight the fires and safely evacuate affected residents. One such tool – Firemap – is a web-based tool developed b Read more…

By John Russell

Exascale Imperative: New Movie from HPE Makes a Compelling Case

October 13, 2017

Why is pursuing exascale computing so important? In a new video – Hewlett Packard Enterprise: Eighteen Zeros – four HPE executives, a prominent national lab HPC researcher, and HPCwire managing editor Tiffany Trader Read more…

By John Russell

Intel Delivers 17-Qubit Quantum Chip to European Research Partner

October 10, 2017

On Tuesday, Intel delivered a 17-qubit superconducting test chip to research partner QuTech, the quantum research institute of Delft University of Technology (TU Delft) in the Netherlands. The announcement marks a major milestone in the 10-year, $50-million collaborative relationship with TU Delft and TNO, the Dutch Organization for Applied Research, to accelerate advancements in quantum computing. Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

“Lunch & Learn” to Explore the Growing Applications of Genomic Analytics

In the digital age of medicine, healthcare providers are rapidly transforming their approach to patient care. Traditional technologies are no longer sufficient to process vast quantities of medical data (including patient histories, treatment plans, diagnostic reports, and more), challenging organizations to invest in a new style of IT to enable faster and higher-quality care. Read more…

Fujitsu Tapped to Build 37-Petaflops ABCI System for AIST

October 10, 2017

Fujitsu announced today it will build the long-planned AI Bridging Cloud Infrastructure (ABCI) which is set to become the fastest supercomputer system in Japan and will begin operation in fiscal 2018 (starts in April). A Read more…

By John Russell

Intel Delivers 17-Qubit Quantum Chip to European Research Partner

October 10, 2017

On Tuesday, Intel delivered a 17-qubit superconducting test chip to research partner QuTech, the quantum research institute of Delft University of Technology (TU Delft) in the Netherlands. The announcement marks a major milestone in the 10-year, $50-million collaborative relationship with TU Delft and TNO, the Dutch Organization for Applied Research, to accelerate advancements in quantum computing. Read more…

By Tiffany Trader

Fujitsu Tapped to Build 37-Petaflops ABCI System for AIST

October 10, 2017

Fujitsu announced today it will build the long-planned AI Bridging Cloud Infrastructure (ABCI) which is set to become the fastest supercomputer system in Japan Read more…

By John Russell

HPC Chips – A Veritable Smorgasbord?

October 10, 2017

For the first time since AMD's ill-fated launch of Bulldozer the answer to the question, 'Which CPU will be in my next HPC system?' doesn't have to be 'Whichever variety of Intel Xeon E5 they are selling when we procure'. Read more…

By Dairsie Latimer

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

Intel Debuts Programmable Acceleration Card

October 5, 2017

With a view toward supporting complex, data-intensive applications, such as AI inference, video streaming analytics, database acceleration and genomics, Intel i Read more…

By Doug Black

OLCF’s 200 Petaflops Summit Machine Still Slated for 2018 Start-up

October 3, 2017

The Department of Energy’s planned 200 petaflops Summit computer, which is currently being installed at Oak Ridge Leadership Computing Facility, is on track t Read more…

By John Russell

US Exascale Program – Some Additional Clarity

September 28, 2017

The last time we left the Department of Energy’s exascale computing program in July, things were looking very positive. Both the U.S. House and Senate had pas Read more…

By Alex R. Larzelere

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

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

Reinders: “AVX-512 May Be a Hidden Gem” in Intel Xeon Scalable Processors

June 29, 2017

Imagine if we could use vector processing on something other than just floating point problems.  Today, GPUs and CPUs work tirelessly to accelerate algorithms Read more…

By James Reinders

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

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

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

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in 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

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

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

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

Cray Moves to Acquire the Seagate ClusterStor Line

July 28, 2017

This week Cray announced that it is picking up Seagate's ClusterStor HPC storage array business for an undisclosed sum. "In short we're effectively transitioning the bulk of the ClusterStor product line to Cray," said CEO Peter Ungaro. 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 Advances Web-based Quantum Programming

September 5, 2017

IBM Research is pairing its Jupyter-based Data Science Experience notebook environment with its cloud-based quantum computer, IBM Q, in hopes of encouraging a new class of entrepreneurial user to solve intractable problems that even exceed the capabilities of the best AI systems. Read more…

By Alex Woodie

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

Intel, NERSC and University Partners Launch New Big Data Center

August 17, 2017

A collaboration between the Department of Energy’s National Energy Research Scientific Computing Center (NERSC), Intel and five Intel Parallel Computing Cente Read more…

By Linda Barney

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