E4 Computer Engineering Unveils New ARM-GPU Clusters

By Nicole Hemsoth

November 13, 2012

This week at SC12, Italian cluster maker E4 Computer Engineering, launched a new series heterogeneous clusters, which pair an NVIDIA’s ARM+GPU Tegra3 with a discrete Quadro GPU. We asked E4’s Simone Tinti, who leads the HPC team at E4, to describe the new systems and talk about the advantage they offer to high performance computing users.

HPCwire: What does E4 Computer Engineering do, and who are your primary customers today?

Simone Tinti: E4 Computer Engineering new web site went online just before SC12 with a renewed look and a lot of contents) designs and manufactures high  performance computing and storage systems. We have a vast portfolio of solutions ranging from technical workstation to complete datacenter. E4 is also very active in providing storage solutions.

E4 Computer Engineering is currently operating in Europe, although CARMA solutions will be available worldwide. Our primary customer base is academia and research. For the past 7 years we have been one of the major supplier of CERN. At present we have more than 11,000 cores active in the CERN  datacenter –1700 computing nodes — and more than 20 petabytes of storage.

Other relevant customers are ETHZ, EPFL, INFN, SISSA, ICTP,  Novartis, Merck, NATO and many more.
 
CARMA solutions are the results a E4 and SECO partnership. SECO is a European  designer  and manufacturer  of  high  integrated  board computers  and  systems  for  embedded applications. Founded in 1979 in Italy, SECO attention is focused on developing   innovative products with high performances efficiency, low power    consumption and increased functionality, offering in the meantime a short time-to-market. SECO has designed and manufactured the CARMA Devkit
 
HPCwire:  In a nutshell, could you briefly describe the three ARM-based solutions you are introducing and the application domains they are targeted at?
 
Tinti: We are introducing two platforms able to host carrier boards for the Qseven modules.

The CARMA microcluster, a 5U chassis, contains up to 8 CARMA blades  — by default they have one NVIDIA Tegra 3 plus one NVIDIA Quadro 1000 — and one x86-based  management node.

The CARMA cluster is a 3U chassis, containing up to 12 CARMA2 blades. These are high density blades, each one containing two CARMA blades for a total of two ARM CPUs plus two Quadro 1000 GPUs or 12 DARMA blades with four ARM CPUs per blade. You can, of course, mix DARMA and CARMA2 blades in the same chassis.

All blades (CARMA, CARMA2 , DARMA) are compliant with the Qseven standard so  the motherboard  — or to be more accurate the carrier board — contains only I/O devices like network, HDMI, SATA and so on.

The CPU component  — actually a SoC containing CPU, RAM, Flash memory, graphics adapter — may be selected from broad range of x86 architecture http://www.seco.com/it/itemlist/qseven/. Qseven technology  provides the highest flexibility while reducing engineering costs. In fact you can swap the CPU architecture re-using  the same carrier board without any modification.  SECO is a co-founder of Qseven consortium.

HPCwire: Regarding HPC applications, what are the advantages of the CARMA solutions compared to a more traditional x86/Tesla GPU cluster?  What niche are you filling with these ARM-based solutions?

Tinti: CARMA solutions provides a low power platform, ideal for applications that relies mainly on GPU computing power. With typical GPU computing systems you need a platform in the range of 250 to 350 watt, for example, a dual-Intel Xeon E5 or dual-AMD Opteron 6200 or 6300 in order to have your GPUs up and running. This is fine as long as a relevant part of the computation relies on CPUs, otherwise this is simply a waste a of power.

Usually GPUs are claimed to have a gigaflops per watt ratio of 3 (higher that the ~2 you can achieve on a BlueGene/Q systems, this is true only if you consider the GPU devices — around 200 watts for  600 peak gigaflops. When you consider the whole platform this ratio drops down 1.2 /0.9 not far from a pure CPU systems as documented in the Green500.

With CARMA blades you need only 10 watts for the CPU, RAM, and flash drive; therefore most of the power — 45 watts — is dedicated to GPUs.

The “must” for exploiting CARMA solution is to have an application that is strongly focused on CUDA for CARMA and CARMA2 blades, or on big data/cloud for DARMA blades.

HPCwire:  What is the advantage of pairing a heterogeneous ARM plus GPU Tegra 3 with a discrete Quadro GPU?  What is the intended programming model for such an arrangement?

Tinti: With the current generation of ARM CPUs, you cannot address algorithms based on floating point arithmetic, therefore most scientific applications are excluded. NVIDIA Quadro GPU broadens the range of applications that can be addressed and gives a huge boost to performance.  CARMA is the one and the only platform available on the market that combines ARM’s low power CPUs with powerful NVIDIA GPUs.

HPCwire: Will developers with existing CUDA applications, run on an x86-Tesla set-up, be able to port their codes to the CARMA platform?

Yes, we provide a pre-configured cross compiling environment for ARM, CUDA, and MPI that makes this process very easy. Support services are also available. We are currently porting some applications, which will be disclosed soon. The systems come with the NVIDIA SDK and ORNL’s SHOC benchmark suite.

HPCwire: Are these clusters intended for production environments?

Tinti: The CARMA cluster is designed to be used in production environment, and provides a robust platform for a wide range of application: HPC, big data, and cloud.

The CARMA microcluster is designed to be a perfect development platform. It’s very quiet and can also be placed beside a desk. It could be used to create, but not for critical environments since a redundant power supply or remote management feature, like IPMI, are not available yet. Based upon the feedback we will receive at SC we will eventually release a more robust version of CARMA microcluster.

HPCwire:  Do you have customers with installed systems, or in the pipeline, for any of  the CARMA or DARMA systems?  What geographies do you intend to serve?

Tinti: More than 2000 CARMA dev kit has been sold so far to the most relevant research centers around the world. A lot of industries in different market such as animation, oil & gas, microelectronics, telecommunications, defense, and manufacturing have adopted it as a development platform. Unfortunately we cannot disclose the name, most of them are developing innovative applications and prefer to keep their privacy right now. Most of these customers are of course waiting for a platform ready for production, like the CARMA series.

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!

Advancing Modular Supercomputing with DEEP and DEEP-ER Architectures

February 24, 2017

Knowing that the jump to exascale will require novel architectural approaches capable of delivering dramatic efficiency and performance gains, researchers around the world are hard at work on next-generation HPC systems. Read more…

By Sean Thielen

Weekly Twitter Roundup (Feb. 23, 2017)

February 23, 2017

Here at HPCwire, we aim to keep the HPC community apprised of the most relevant and interesting news items that get tweeted throughout the week. Read more…

By Thomas Ayres

HPE Server Shows Low Latency on STAC-N1 Test

February 22, 2017

The performance of trade and match servers can be a critical differentiator for financial trading houses. Read more…

By John Russell

HPC Financial Update (Feb. 2017)

February 22, 2017

In this recurring feature, we’ll provide you with financial highlights from companies in the HPC industry. Check back in regularly for an updated list with the most pertinent fiscal information. Read more…

By Thomas Ayres

HPE Extreme Performance Solutions

O&G Companies Create Value with High Performance Remote Visualization

Today’s oil and gas (O&G) companies are striving to process datasets that have become not only tremendously large, but extremely complex. And the larger that data becomes, the harder it is to move and analyze it – particularly with a workforce that could be distributed between drilling sites, offshore rigs, and remote offices. Read more…

Rethinking HPC Platforms for ‘Second Gen’ Applications

February 22, 2017

Just what constitutes HPC and how best to support it is a keen topic currently. Read more…

By John Russell

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

IDC: Will the Real Exascale Race Please Stand Up?

February 21, 2017

So the exascale race is on. And lots of organizations are in the pack. Government announcements from the US, China, India, Japan, and the EU indicate that they are working hard to make it happen – some sooner, some later. Read more…

By Bob Sorensen, IDC

ExxonMobil, NCSA, Cray Scale Reservoir Simulation to 700,000+ Processors

February 17, 2017

In a scaling breakthrough for oil and gas discovery, ExxonMobil geoscientists report they have harnessed the power of 717,000 processors – the equivalent of 22,000 32-processor computers – to run complex oil and gas reservoir simulation models. Read more…

By Doug Black

Advancing Modular Supercomputing with DEEP and DEEP-ER Architectures

February 24, 2017

Knowing that the jump to exascale will require novel architectural approaches capable of delivering dramatic efficiency and performance gains, researchers around the world are hard at work on next-generation HPC systems. Read more…

By Sean Thielen

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

IDC: Will the Real Exascale Race Please Stand Up?

February 21, 2017

So the exascale race is on. And lots of organizations are in the pack. Government announcements from the US, China, India, Japan, and the EU indicate that they are working hard to make it happen – some sooner, some later. Read more…

By Bob Sorensen, IDC

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

Drug Developers Use Google Cloud HPC in the Fight Against ALS

February 16, 2017

Within the haystack of a lethal disease such as ALS (amyotrophic lateral sclerosis / Lou Gehrig’s Disease) there exists, somewhere, the needle that will pierce this therapy-resistant affliction. Read more…

By Doug Black

Azure Edges AWS in Linpack Benchmark Study

February 15, 2017

The “when will clouds be ready for HPC” question has ebbed and flowed for years. Read more…

By John Russell

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

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

US, China Vie for Supercomputing Supremacy

November 14, 2016

The 48th edition of the TOP500 list is fresh off the presses and while there is no new number one system, as previously teased by China, there are a number of notable entrants from the US and around the world and significant trends to report on. Read more…

By Tiffany Trader

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

D-Wave SC16 Update: What’s Bo Ewald Saying These Days

November 18, 2016

Tucked in a back section of the SC16 exhibit hall, quantum computing pioneer D-Wave has been talking up its new 2000-qubit processor announced in September. Forget for a moment the criticism sometimes aimed at D-Wave. This small Canadian company has sold several machines including, for example, ones to Lockheed and NASA, and has worked with Google on mapping machine learning problems to quantum computing. In July Los Alamos National Laboratory took possession of a 1000-quibit D-Wave 2X system that LANL ordered a year ago around the time of SC15. Read more…

By John Russell

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

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

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

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

Leading Solution Providers

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

Nvidia Sees Bright Future for AI Supercomputing

November 23, 2016

Graphics chipmaker Nvidia made a strong showing at SC16 in Salt Lake City last week. Read more…

By Tiffany Trader

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

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

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

Dell Knights Landing Machine Sets New STAC Records

November 2, 2016

The Securities Technology Analysis Center, commonly known as STAC, has released a new report characterizing the performance of the Knight Landing-based Dell PowerEdge C6320p server on the STAC-A2 benchmarking suite, widely used by the financial services industry to test and evaluate computing platforms. The Dell machine has set new records for both the baseline Greeks benchmark and the large Greeks benchmark. Read more…

By Tiffany Trader

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

Intel and Trump Announce $7B for Fab 42 Targeting 7nm

February 8, 2017

In what may be an attempt by President Trump to reset his turbulent relationship with the high tech industry, he and Intel CEO Brian Krzanich today announced plans to invest more than $7 billion to complete Fab 42. Read more…

By John Russell

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