Visit additional Tabor Communication Publications
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.
Jun 18, 2013 |
The world's largest supercomputers, like Tianhe-2, are great at traditional, compute-intensive HPC workloads, such as simulating atomic decay or modeling tornados. But data-intensive applications--such as mining big data sets for connections--is a different sort of workload, and runs best on a different sort of computer.
Jun 18, 2013 |
Researchers are finding innovative uses for Gordon, the 285 teraflop supercomputer housed at the San Diego Supercomputer Center (SDSC) that has a unique Flash-based storage system. Since going online, researchers have put the incredibly fast I/O to use on a wide variety of workloads, ranging from chemistry to political science.
Jun 17, 2013 |
The advent of low-power mobile processors and cloud delivery models is changing the economics of computing. But just as an economy car is good at different things than a full size truck, an HPC workload still has certain computing demands that neither the fastest smartphone nor the most elastic cloud cluster can fulfill.
Jun 14, 2013 |
For all the progress we've made in IT over the last 50 years, there's one area of life that has steadfastly eluded the grasp of computers: understanding human language. Now, researchers at the Texas Advanced Computing Center (TACC) are utilizing a Hadoop cluster on its Longhorn supercomputer to move the state of the art of language processing a little bit further.
Jun 13, 2013 |
Titan, the Cray XK7 at the Oak Ridge National Lab that debuted last fall as the fastest supercomputer in the world with 17.59 petaflops of sustained computing power, will rely on its previous LINPACK test for the upcoming edition of the Top 500 list.
05/10/2013 | Cleversafe, Cray, DDN, NetApp, & Panasas | From Wall Street to Hollywood, drug discovery to homeland security, companies and organizations of all sizes and stripes are coming face to face with the challenges – and opportunities – afforded by Big Data. Before anyone can utilize these extraordinary data repositories, however, they must first harness and manage their data stores, and do so utilizing technologies that underscore affordability, security, and scalability.
04/15/2013 | Bull | “50% of HPC users say their largest jobs scale to 120 cores or less.” How about yours? Are your codes ready to take advantage of today’s and tomorrow’s ultra-parallel HPC systems? Download this White Paper by Analysts Intersect360 Research to see what Bull and Intel’s Center for Excellence in Parallel Programming can do for your codes.
Join HPCwire Editor Nicole Hemsoth and Dr. David Bader from Georgia Tech as they take center stage on opening night at Atlanta's first Big Data Kick Off Week, filmed in front of a live audience. Nicole and David look at the evolution of HPC, today's big data challenges, discuss real world solutions, and reveal their predictions. Exactly what does the future holds for HPC?
Join our webinar to learn how IT managers can migrate to a more resilient, flexible and scalable solution that grows with the data center. Mellanox VMS is future-proof, efficient and brings significant CAPEX and OPEX savings. The VMS is available today.