Adapteva Unveils 64-Core Chip

By Michael Feldman

August 22, 2012

Chipmaker Adapteva is sampling its 4th-generation multicore processor, known as Epiphany-IV. The 64-core chip delivers a peak performance of 100 gigaflops and draws just two watts of power, yielding a stunning 50 gigaflops/watt. The engineering samples were manufactured by GLOBALFOUNDRIES on its latest 28nm process technology.

Based in LEXINGTON, Massachusetts, Adapteva is in the business of developing ultra-efficient floating point accelerators. Andreas Olofsson, a former chip engineer at Texas Instruments and Analog Devices, founded the company in 2008, and gathered $2.5 million from various VCs and private investors. With that shoestring budget, he managed to produce four generations of the Epiphany architecture, including two actual chips. The technology is initially aimed at the mobile and embedded market, but Olofsson also has designs on penetrating the supercomputing space.

Epiphany is essentially a stripped down general-purpose RISC CPU that throws out almost everything but the number-crunching silicon. But since it doesn’t incorporate features needed by operating systems, like memory management, it relies on a host processor to feed it application kernels in the same manner as a GPGPU. The current implementation supports single precision floating point only, but plans are already in the works for a double precision implementation.

The general layout of Epiphany is a 2D mesh of simple cores, which talk to each other via a high-speed interconnect.  In that sense, it looks more like Intel’s manycore Xeon Phi than a graphics processor, but without the x86 ISA baggage (but also without the benefit of the x86 ecosystem).

The latest Epiphany chip, which was spec’d out last fall, runs at a relatively slow 800MHz.  But thanks to its highly parallel design and simplified cores, its 50 gigaflops/watt energy efficiency is among the best in the business. NVIDIA’s new K10 GPU computing card can hit about 20 single precision gigaflops/watt, but that also includes 8GB of GDDR5 memory and a few other on-board components, so it’s not an apples-to-apples comparison. Regardless, a 100 gigaflop chip drawing a couple of watts is a significant achievement.

The downside of the design is that it uses Adapteva’s own proprietary ISA, so there are no ready-made software tools that developers can tap into. “Everybody is very impressed by the numbers,” Olofsson told HPCwire. “They just haven’t quite been convinced they can program this thing.”

That has now changed.  In conjunction with the 28nm samples, Adapteva has also released its own OpenCL compiler wrapped in their new software developer kit (SDK). The compiler is an adaptation of Brown Deer Technology’s OpenCL implementation developed for ARM and x86 platforms. Brown Deer provides tools and support for high performance computing applications and is especially focused on acceleration technologies based on GPUs and FPGAs. The Adapteva implementation means developers can now use standard OpenCL source to program the Epiphany processor.
Olofsson says they chose OpenCL because it’s a recognized open standard that is being used for heterogeneous computing platforms in all the segments Adapteva is interested in. In particular, it’s getting some traction on heterogeneous platforms in the embedded space, where GPUs are increasingly being targeted to general-purpose computing.  “The way we are pitching [Epiphany] is that OpenCL GPGPUs may not be good at everything, because of their architectural limitations,” say Olofsson. “So why not put another accelerator next to it that is also OpenCL-programmable.”  

Adapteva is putting the SDK through its paces using existing OpenCL codes like 2D Fast Fourier Transform (FFT) and multi-body physics algorithms that were downloaded off the Internet. The company is currently using an x86-based board for these test runs, but since OpenCL has bindings for C/C++, essentially any commodity CPU is fair game as the host driver. Adapteva’s SDK is currently in beta form and is being released to the company’s early access partners.

As far as getting the Epiphany chips onto useful platforms, that’s still a work in progress. At least some of the engineering samples of the 28nm chip will go to Bittware, an early customer of Adapteva’s. Bittware used the early 16-core, 32-gigaflop version of Epiphany on its custom PCIe boards.  Those products are aimed at military and industrial application for things like embedded signal processing. Because of the need to minimize power usage in embedded computing, Epiphany is a good fit for this application domain.  At least one more vendor has signed up to develop Epiphany-based PCIe boards, but that company is not ready to go public just yet.

Adapteva’s market aspirations extend beyond the military-industrial complex though. Olofsson believes Epiphany is ideal for mobile computing, and eventually HPC.  With regard to the former, Adapteva is planning to use the new chip to demonstrate face detection, an application aimed at devices like smartphones and tablets. Face detection and recognition rely on very compute-intensive algorithms, which is fine if you’ve got a server or two to spare, but it’s beyond the number-crunching capabilities of most mobile-grade CPUs and GPUs today.

Other flop-hungry applications that could find a home on in this market include augmented overlays, gesture recognition, real-time speech recognition, realistic game physics, and computational photography. Like mobile-based face detection/recognition, all of these require lots of computational performance operating within very restricted power envelopes.

For high performance computing, the path is a little more complex. For starters, someone has to build a Epiphany-based PCIe card suitable for HPC servers, and then an OEM has to be enticed to support that board. To deliver a reasonable amount of computation for  a server — say, a teraflop or so — you would need multiple Epiphany chips glued to a card, which would necessitate a PCIe expansion setup of some sort. Not an impossibility, but probably not a job for a do-it-yourselfer.

More fundamentally though, the architecture has to add support for double precision floating point to be taken seriously for HPC (although applications like seismic modeling, image and audio processing, and video analysis are fine with single precision).  
In any case, double precision is already on Adapteva’s roadmap. “We’ll definitely have something next year,” says Olofsson.

Beyond that, the company has plans on the drawing board to scale this architecture up to the teraflop/watt realm. Following a Moore’s Law trajectory, that would mean that by 2018 a 7nm Epiphany processor could house 1,000 cores and deliver a whopping two teraflops.  Since such a chip would draw the same two watts as the current 100 gigaflops version, it could easily provide the foundation for an exascale supercomputer. Or a killer tablet.

 


 

Related Articles

Adapteva Builds Manycore Processor That Will Deliver 70 Gigaflops/Watt

Startup Launches Manycore Floating Point Acceleration Technology

 

 

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!

UK to Launch Six Major HPC Centers

March 27, 2017

Six high performance computing centers will be formally launched in the U.K. later this week intended to provide wider access to HPC resources to U.K. Read more…

By John Russell

AI in the News: Rao in at Intel, Ng out at Baidu, Nvidia on at Tencent Cloud

March 26, 2017

Just as AI has become the leitmotif of the advanced scale computing market, infusing much of the conversation about HPC in commercial and industrial spheres, it also is impacting high-level management changes in the industry. Read more…

By Doug Black

Scalable Informatics Ceases Operations

March 23, 2017

On the same day we reported on the uncertain future for HPC compiler company PathScale, we are sad to learn that another HPC vendor, Scalable Informatics, is closing its doors. Read more…

By Tiffany Trader

‘Strategies in Biomedical Data Science’ Advances IT-Research Synergies

March 23, 2017

“Strategies in Biomedical Data Science: Driving Force for Innovation” by Jay A. Etchings is both an introductory text and a field guide for anyone working with biomedical data. Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

Quants Achieving Maximum Compute Power without the Learning Curve

The financial services industry is a fast-paced and data-intensive environment, and financial firms are realizing that they must modernize their IT infrastructures and invest in high performance computing (HPC) tools in order to survive. Read more…

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its assets. Read more…

By Tiffany Trader

Google Launches New Machine Learning Journal

March 22, 2017

On Monday, Google announced plans to launch a new peer review journal and “ecosystem” Read more…

By John Russell

Swiss Researchers Peer Inside Chips with Improved X-Ray Imaging

March 22, 2017

Peering inside semiconductor chips using x-ray imaging isn’t new, but the technique hasn’t been especially good or easy to accomplish. Read more…

By John Russell

LANL Simulation Shows Massive Black Holes Break ‘Speed Limit’

March 21, 2017

A new computer simulation based on codes developed at Los Alamos National Laboratory (LANL) is shedding light on how supermassive black holes could have formed in the early universe contrary to most prior models which impose a limit on how fast these massive ‘objects’ can form. Read more…

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its assets. Read more…

By Tiffany Trader

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Read more…

By John Russell

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the campaign. Read more…

By John Russell

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

In this contributed perspective piece, Intel’s Jim Jeffers makes the case that CPU-based visualization is now widely adopted and as such is no longer a contrarian view, but is rather an exascale requirement. Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

US Supercomputing Leaders Tackle the China Question

March 15, 2017

Joint DOE-NSA report responds to the increased global pressures impacting the competitiveness of U.S. supercomputing. Read more…

By Tiffany Trader

New Japanese Supercomputing Project Targets Exascale

March 14, 2017

Another Japanese supercomputing project was revealed this week, this one from emerging supercomputer maker, ExaScaler Inc., and Keio University. The partners are working on an original supercomputer design with exascale aspirations. Read more…

By Tiffany Trader

Nvidia Debuts HGX-1 for Cloud; Announces Fujitsu AI Deal

March 9, 2017

On Monday Nvidia announced a major deal with Fujitsu to help build an AI supercomputer for RIKEN using 24 DGX-1 servers. Read more…

By John Russell

HPC4Mfg Advances State-of-the-Art for American Manufacturing

March 9, 2017

Last Friday (March 3, 2017), the High Performance Computing for Manufacturing (HPC4Mfg) program held an industry engagement day workshop in San Diego, bringing together members of the US manufacturing community, national laboratories and universities to discuss the role of high-performance computing as an innovation engine for American manufacturing. Read more…

By Tiffany Trader

For IBM/OpenPOWER: Success in 2017 = (Volume) Sales

January 11, 2017

To a large degree IBM and the OpenPOWER Foundation have done what they said they would – assembling a substantial and growing ecosystem and bringing Power-based products to market, all in about three years. Read more…

By John Russell

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the campaign. Read more…

By John Russell

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Read more…

By John Russell

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

IBM Wants to be “Red Hat” of Deep Learning

January 26, 2017

IBM today announced the addition of TensorFlow and Chainer deep learning frameworks to its PowerAI suite of deep learning tools, which already includes popular offerings such as Caffe, Theano, and Torch. Read more…

By John Russell

Lighting up Aurora: Behind the Scenes at the Creation of the DOE’s Upcoming 200 Petaflops Supercomputer

December 1, 2016

In April 2015, U.S. Department of Energy Undersecretary Franklin Orr announced that Intel would be the prime contractor for Aurora: Read more…

By Jan Rowell

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling was pretty much the exclusive realm of the Cray-2 and IBM mainframe class products. That’s changing. We are now seeing an emergence of x86 class server products with exotic plumbing technology ranging from Direct-to-Chip to servers and storage completely immersed in a dielectric fluid. Read more…

By Steve Campbell

Leading Solution Providers

Enlisting Deep Learning in the War on Cancer

December 7, 2016

Sometime in Q2 2017 the first ‘results’ of the Joint Design of Advanced Computing Solutions for Cancer (JDACS4C) will become publicly available according to Rick Stevens. He leads one of three JDACS4C pilot projects pressing deep learning (DL) into service in the War on Cancer. Read more…

By John Russell

BioTeam’s Berman Charts 2017 HPC Trends in Life Sciences

January 4, 2017

Twenty years ago high performance computing was nearly absent from life sciences. Today it’s used throughout life sciences and biomedical research. Genomics and the data deluge from modern lab instruments are the main drivers, but so is the longer-term desire to perform predictive simulation in support of Precision Medicine (PM). There’s even a specialized life sciences supercomputer, ‘Anton’ from D.E. Shaw Research, and the Pittsburgh Supercomputing Center is standing up its second Anton 2 and actively soliciting project proposals. There’s a lot going on. Read more…

By John Russell

HPC Startup Advances Auto-Parallelization’s Promise

January 23, 2017

The shift from single core to multicore hardware has made finding parallelism in codes more important than ever, but that hasn’t made the task of parallel programming any easier. Read more…

By Tiffany Trader

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its assets. Read more…

By Tiffany Trader

HPC Technique Propels Deep Learning at Scale

February 21, 2017

Researchers from Baidu’s Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural network training and now they are sharing their implementation with the larger deep learning community. Read more…

By Tiffany Trader

CPU Benchmarking: Haswell Versus POWER8

June 2, 2015

With OpenPOWER activity ramping up and IBM’s prominent role in the upcoming DOE machines Summit and Sierra, it’s a good time to look at how the IBM POWER CPU stacks up against the x86 Xeon Haswell CPU from Intel. Read more…

By Tiffany Trader

IDG to Be Bought by Chinese Investors; IDC to Spin Out HPC Group

January 19, 2017

US-based publishing and investment firm International Data Group, Inc. (IDG) will be acquired by a pair of Chinese investors, China Oceanwide Holdings Group Co., Ltd. Read more…

By Tiffany Trader

US Supercomputing Leaders Tackle the China Question

March 15, 2017

Joint DOE-NSA report responds to the increased global pressures impacting the competitiveness of U.S. supercomputing. Read more…

By Tiffany Trader

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