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!

Is Data Science the Fourth Pillar of the Scientific Method?

April 18, 2019

Nvidia CEO Jensen Huang revived a decade-old debate last month when he said that modern data science (AI plus HPC) has become the fourth pillar of the scientific method. While some disagree with the notion that statistic Read more…

By Alex Woodie

At ASF 2019: The Virtuous Circle of Big Data, AI and HPC

April 18, 2019

We've entered a new phase in IT -- in the world, really -- where the combination of big data, artificial intelligence, and high performance computing is pushing the bounds of what's possible in business and science, in w Read more…

By Alex Woodie with Doug Black and Tiffany Trader

Google Open Sources TensorFlow Version of MorphNet DL Tool

April 18, 2019

Designing optimum deep neural networks remains a non-trivial exercise. “Given the large search space of possible architectures, designing a network from scratch for your specific application can be prohibitively expens 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.

powercloud_blog.jpgFor 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

Bridging HPC and Cloud Native Development with Kubernetes

The HPC community has historically developed its own specialized software stack including schedulers, filesystems, developer tools, container technologies tuned for performance and large-scale on-premises deployments. Read more…

Interview with 2019 Person to Watch Michela Taufer

April 18, 2019

Today, as part of our ongoing HPCwire People to Watch focus series, we are highlighting our interview with 2019 Person to Watch Michela Taufer. Michela -- the General Chair of SC19 -- is an ACM Distinguished Scientist. Read more…

By HPCwire Editorial Team

At ASF 2019: The Virtuous Circle of Big Data, AI and HPC

April 18, 2019

We've entered a new phase in IT -- in the world, really -- where the combination of big data, artificial intelligence, and high performance computing is pushing Read more…

By Alex Woodie with Doug Black and Tiffany Trader

Interview with 2019 Person to Watch Michela Taufer

April 18, 2019

Today, as part of our ongoing HPCwire People to Watch focus series, we are highlighting our interview with 2019 Person to Watch Michela Taufer. Michela -- the Read more…

By HPCwire Editorial Team

Intel Gold U-Series SKUs Reveal Single Socket Intentions

April 18, 2019

Intel plans to jump into the single socket market with a portion of its just announced Cascade Lake microprocessor line according to one media report. This isn Read more…

By John Russell

BSC Researchers Shrink Floating Point Formats to Accelerate Deep Neural Network Training

April 15, 2019

Sometimes calculating solutions as precisely as a computer can wastes more CPU resources than is necessary. A case in point is with deep learning. In early stag Read more…

By Ken Strandberg

Intel Extends FPGA Ecosystem with 10nm Agilex

April 11, 2019

The insatiable appetite for higher throughput and lower latency – particularly where edge analytics and AI, network functions, or for a range of datacenter ac Read more…

By Doug Black

Nvidia Doubles Down on Medical AI

April 9, 2019

Nvidia is collaborating with medical groups to push GPU-powered AI tools into clinical settings, including radiology and drug discovery. The GPU leader said Monday it will collaborate with the American College of Radiology (ACR) to provide clinicians with its Clara AI tool kit. The partnership would allow radiologists to leverage AI techniques for diagnostic imaging using their own clinical data. Read more…

By George Leopold

Digging into MLPerf Benchmark Suite to Inform AI Infrastructure Decisions

April 9, 2019

With machine learning and deep learning storming into the datacenter, the new challenge is optimizing infrastructure choices to support diverse ML and DL workfl Read more…

By John Russell

AI and Enterprise Datacenters Boost HPC Server Revenues Past Expectations – Hyperion

April 9, 2019

Building on the big year of 2017 and spurred in part by the convergence of AI and HPC, global revenue for high performance servers jumped 15.6 percent last year Read more…

By Doug Black

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

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

ClusterVision in Bankruptcy, Fate Uncertain

February 13, 2019

ClusterVision, European HPC specialists that have built and installed over 20 Top500-ranked systems in their nearly 17-year history, appear to be in the midst o Read more…

By Tiffany Trader

Intel Reportedly in $6B Bid for Mellanox

January 30, 2019

The latest rumors and reports around an acquisition of Mellanox focus on Intel, which has reportedly offered a $6 billion bid for the high performance interconn Read more…

By Doug Black

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

Looking for Light Reading? NSF-backed ‘Comic Books’ Tackle Quantum Computing

January 28, 2019

Still baffled by quantum computing? How about turning to comic books (graphic novels for the well-read among you) for some clarity and a little humor on QC. The Read more…

By John Russell

IBM Quantum Update: Q System One Launch, New Collaborators, and QC Center Plans

January 10, 2019

IBM made three significant quantum computing announcements at CES this week. One was introduction of IBM Q System One; it’s really the integration of IBM’s Read more…

By John Russell

Deep500: ETH Researchers Introduce New Deep Learning Benchmark for HPC

February 5, 2019

ETH researchers have developed a new deep learning benchmarking environment – Deep500 – they say is “the first distributed and reproducible benchmarking s Read more…

By John Russell

Leading Solution Providers

SC 18 Virtual Booth Video Tour

Advania @ SC18 AMD @ SC18
ASRock Rack @ SC18
DDN Storage @ SC18
HPE @ SC18
IBM @ SC18
Lenovo @ SC18 Mellanox Technologies @ SC18
NVIDIA @ SC18
One Stop Systems @ SC18
Oracle @ SC18 Panasas @ SC18
Supermicro @ SC18 SUSE @ SC18 TYAN @ SC18
Verne Global @ SC18

IBM Bets $2B Seeking 1000X AI Hardware Performance Boost

February 7, 2019

For now, AI systems are mostly machine learning-based and “narrow” – powerful as they are by today's standards, they're limited to performing a few, narro Read more…

By Doug Black

The Deep500 – Researchers Tackle an HPC Benchmark for Deep Learning

January 7, 2019

How do you know if an HPC system, particularly a larger-scale system, is well-suited for deep learning workloads? Today, that’s not an easy question to answer Read more…

By John Russell

Arm Unveils Neoverse N1 Platform with up to 128-Cores

February 20, 2019

Following on its Neoverse roadmap announcement last October, Arm today revealed its next-gen Neoverse microarchitecture with compute and throughput-optimized si Read more…

By Tiffany Trader

France to Deploy AI-Focused Supercomputer: Jean Zay

January 22, 2019

HPE announced today that it won the contract to build a supercomputer that will drive France’s AI and HPC efforts. The computer will be part of GENCI, the Fre Read more…

By 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

Oil and Gas Supercloud Clears Out Remaining Knights Landing Inventory: All 38,000 Wafers

March 13, 2019

The McCloud HPC service being built by Australia’s DownUnder GeoSolutions (DUG) outside Houston is set to become the largest oil and gas cloud in the world th Read more…

By Tiffany Trader

HPC Reflections and (Mostly Hopeful) Predictions

December 19, 2018

So much ‘spaghetti’ gets tossed on walls by the technology community (vendors and researchers) to see what sticks that it is often difficult to peer through Read more…

By John Russell

Air Force Research Laboratory Unveils First Shared, Classified DoD HPC Capability

February 28, 2019

In a ceremony on Tuesday, the Air Force Research Laboratory unveiled four new computing clusters, providing the capability for what it is calling the first-ever 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