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US Exascale Program – Some Additional Clarity

Thu, 09/28/2017 - 12:12

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 passed solid Fiscal Year 2018 (FY-18) appropriations for the exascale activities for both the National Nuclear Security Administration (NNSA) and the Office of Science (SC). However, it also looked like there would be potential major challenges with other parts of the DOE’s budget. These included significant differences with some programs, such as ARPA-E that was over $300 million apart between the House and Senate appropriation bills.

After its August recess, Congress was expected to have some major budget fights in September. This not only included reconciling the difference between the versions of House and Senate appropriations, but also the question of raising the U.S. debt ceiling. Then on September 6th, those potential fights came to a sudden end when President Trump reached an agreement with the House and Senate Democratic leaders for a FY-18 Continuing Budget Resolution (CR) and to raise the government debt ceiling until early December 2017. That effectively maintains the Exascale FY-17 status quo in the short term. From a funding perspective, things for the exascale program continue to look very good.

On September 26th and 27th, some more clarity about the technical aspects of the program was provided during the public SC Advanced Scientific Computing Advisory Committee (ASCAC) meeting. The ASCAC is a regular meeting of the officially endorsed Federal Advisory Committee Act (FACA) group that provides advice to Advanced Scientific Computing Research (ASCR) program. During the meeting, Barb Helland, the associate director for the ASCR office, provided a presentation about the status of the their activities (link). The presentation included some very interesting information about the status of the SC Exascale program.

On slide number 7, she told the ASCAC that there had been a shift in the delivery of the Argonne National Laboratory (ANL) Aurora system. That computer had originally been scheduled to be delivered in 2018 with a performance of 180 petaflops. However, the revised plan for the system is for a 1,000 petaflops (or 1 exaflops) computer to be delivered in 2021. The machine would use “novel technology choices” and would focus on the three pillars of simulation, big data, and machine learning. This shift in the program seems to explain the House’s concern “that the deployment plan for an exascale machine has undergone major changes without an appropriately defined cost and performance baseline.”

Ms. Helland reported that the shift in the machine architecture had been subject to a review in September of 2017 and had received very favorable comments. These included, “The system as presented is exciting with many novel technology choices that can change the way computing is done. The committee supports the bold strategy and innovation, which is required to meet the targets of exascale computing. The committee sees a credible path to success.” Another comment was, “The hardware choices/design within the node is extremely well thought through. Early projections suggest that the system will support a broad workload.” She also reported that a Rebaseline Independent Project Review was scheduled for November 7th to 9th.

Another important piece of news was about the status of the installation of the Oak Ridge National Laboratory (ORNL) Leadership Computing Facility’s Summit computer. This is expected to be a 150 petaflops computer based on the IBM Power9 processors with Nvidia Volta graphic processing units (GPUs). During the meeting, it was reported that the system cabinets had been installed along with the interconnection switches. The computer node boards are expected to arrive sometime towards the end of October and that acceptance testing would start soon after that. It was also reported, that installation of the NNSA’s Lawrence Livermore National Laboratory (LLNL) Sierra computer (similar to Summit) was also underway. One interesting feature of the ORNL computers is that they are installed on a concrete slab with all of the supporting wiring and cooling coming from overhead.

During her presentation, Barb Helland made the point that ASCR would soon be releasing information about the procurement of additional exascale systems to be delivered in the 2022 timeframe. No details were provided, but she explained that these systems would be follow-on systems to the ones delivered as part of the CORAL procurement.

Finally, there were two other interesting exascale revelations during the ASCAC meeting. One was the clarification of the differences between the acronyms of ECI and ECP that appeared in the President’s budget request. Slide number 5 provides the definitions of the terms and states that the ECI (Exascale Computing Initiative) is the partnership between the NNSA and SC. On the other hand, ECP (Exascale Computing Project) is a subprogram within ASCR (SC-ECP) and includes only support for research and development activities in applications, and in partnership with NNSA, investments in software and hardware technology and co- design required for the design of capable exascale computers. The other revelation is that Paul Messina of ANL, the founding director of ECP, is stepping down and will be replaced as of October 1st by Doug Kothe of ORNL. The ASCAC thanked Paul for his service to the country in establishing the foundations for the ECP.

All in all, the most recent ASCAC meeting provided some valuable insights into the U.S. exascale program. Certainly not all of the questions have been answered, but the information provided at the meeting helps to clarify the Department of Energy cutting edge computing program. Perhaps the best news is that the program is still receiving strong Presidential and Congressional support. However, the new December 2017 budget deadline continues to lurk in the background. Once again, more to come.

About the Author

Alex Larzelere is a senior fellow at the U.S. Council on Competitiveness, the president of Larzelere & Associates Consulting and HPCwire’s policy editor. He is currently a technologist, speaker and author on a number of disruptive technologies that include: advanced modeling and simulation; high performance computing; artificial intelligence; the Internet of Things; and additive manufacturing. Alex’s career has included time in federal service (working closely with DOE national labs), private industry, and as founder of a small business. Throughout that time, he led programs that implemented the use of cutting edge advanced computing technologies to enable high resolution, multi-physics simulations of complex physical systems. Alex is the author of “Delivering Insight: The History of the Accelerated Strategic Computing Initiative (ASCI).”

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Penguin Computing Announces NVIDIA Tesla V100-based Servers

Thu, 09/28/2017 - 12:05

FREMONT, Calif., Sept. 28, 2017 — Penguin Computing, provider of high performance computing, enterprise datacenter and cloud solutions, today announced strategic support for the field of artificial intelligence through availability of its servers based on the highly-advanced NVIDIA Tesla V100 GPU accelerator, powered by the NVIDIA Volta GPU architecture.

“Deep learning, machine learning and artificial intelligence are vital tools for addressing the world’s most complex challenges and improving many aspects of our lives,” said William Wu, Director of Product Management, Penguin Computing. “Our breadth of products covers configurations that accelerate various demanding workloads – maximizing performance, minimizing P2P latency of multiple GPUs and providing minimal power consumption through creative cooling solutions.”

NVIDIA Tesla V100 GPUs join an expansive GPU server line that covers Penguin Computing’s Relion servers (Intel-based) and Altus servers (AMD-based) in both 19” and 21” Tundra form factors. Penguin Computing will debut a high density 21” Tundra 1OU GPU server to support 4x Tesla V100 SXM2, and 19” 4U GPU server to support 8x Tesla V100 SXM2 with NVIDIA NVLink interconnect technology optional in single root complex.

The NVIDIA Volta architecture is bolstered by pairing NVIDIA CUDA cores and NVIDIA Tensor Cores within a unified architecture. A single server with Tesla V100 GPUs can replace hundreds of CPU servers for AI. Equipped with 640 Tensor Cores, Tesla V100 delivers 125 TeraFLOPS of deep learning performance. That’s 12X Tensor FLOPS for deep learning training, and 6X Tensor FLOPS for deep learning inference when compared to NVIDIA Pascal GPUs.

“Penguin Computing continues to demonstrate leadership by providing Volta-based systems to support critical AI research,” said Paresh Kharya, Group Product Marketing Manager, NVIDIA. “Tesla V100 systems will enable their customers to create innovative AI products and services by accelerating their AI research and deployments.”

Today’s announcement reinforces Penguin Computing’s philosophy and broader capabilities as a full-spectrum provider offering complete solutions. This includes tailored, custom designs that are supportable and scale to large deployments, and fully engineered and architected designs.

About Penguin Computing

Penguin Computing is one of the largest private suppliers of enterprise and high-performance computing solutions in North America and has built and operates a specialized public HPC cloud service, Penguin Computing On-Demand (POD). Penguin Computing pioneers the design, engineering, integration and delivery of solutions that are based on open architectures and comprise non-proprietary components from a variety of vendors. Penguin Computing is also one of a limited number of authorized Open Compute Project (OCP) solution providers leveraging this Facebook-led initiative to bring the most efficient open data center solutions to a broader market, and has announced the Tundra product line which applies the benefits of OCP to high performance computing. Penguin Computing has systems installed with more than 2,500 customers in 40 countries across eight major vertical markets. Visit www.penguincomputing.com to learn more about the company and follow @PenguinHPC on Twitter.

Source: Penguin Computing

The post Penguin Computing Announces NVIDIA Tesla V100-based Servers appeared first on HPCwire.

Students from Underrepresented Groups Research Data Science with Brookhaven Lab

Thu, 09/28/2017 - 11:55

Sept. 28, 2017 — Computing is one of the least diverse science, technology, engineering, and mathematics (STEM) fields, with an underrepresentation of women and minorities, including African Americans and Hispanics. Leveraging this largely untapped talent pool will help address our nation’s growing demand for data scientists. Computational approaches for extracting insights from big data require the creativity, innovation, and collaboration of a diverse workforce.

As part of its efforts to train the next generation of computational and computer scientists, this past summer, the Computational Science Initiative (CSI) at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory hosted a diverse group of high school, undergraduate, and graduate students. This group included students from Jackson State University and Lincoln University, both historically black colleges and universities. The Lincoln University students were supported through the National Science Foundation’s Louis Stokes Alliances for Minority Participation program, which provides research and other academic opportunities for minority students to advance in STEM. Two of the students are recipients of prestigious fellowship programs: the Graduate Education for Minorities (GEM) Fellowship, through which qualified students from underrepresented minorities receive funding to pursue STEM graduate education; and the DOE Computational Science Graduate Fellowship (CSGF), which supports doctoral research using mathematics and computers to solve problems in many scientific fields of study, including astrophysics, environmental science, and nuclear engineering.

“To address challenges in science, we need to bring together the best minds available,” said CSI Director Kerstin Kleese van Dam. “Great talents are rare but can be found among all groups, so we reach out to the broadest talent pools in search of our top researchers at every education level and career stage. In return, we offer them the opportunity to work on some of the most exciting problems with experts who are pushing the state of the art in computer science and applied mathematics.”

The students’ research spanned many areas, including visualization and machine learning techniques for big data analysis, modeling and simulation applications, and automated approaches to data validation and verification.

To read the full story, with graphics, please visit the original story at: https://www.bnl.gov/newsroom/news.php?a=212478

Source: Ariana Tantillo, Brookhaven National Laboratory

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US-Based CryoEM Company, SingleParticle.com, Partners with Bright

Thu, 09/28/2017 - 10:57

SAN JOSE, Calif., Sept. 28, 2017 — Bright Computing, a leader in cluster and cloud infrastructure automation software, today announced a reseller agreement with San Diego-based SingleParticle.com.

SingleParticle.com is the US subsidiary of Chinese company, BlueJay Imaging, and specializes in turn-key HPC infrastructure designed for high performance and low total cost of ownership (TCO), serving the global research community of cryo-electron microscopy (cryoEM).

The partnership with Bright Computing enables SingleParticle.com to add cluster management to its portfolio. By offering Bright technology to its customer base, SingleParticle.com reduces the IT burden on its customers’ cryoEM facilities. With Bright Cluster Manager, managing SingleParticle.com clusters become much less time-consuming and onerous, enabling customers to focus on solving new structures that can lead to new scientific discoveries and even new drug designs.

Recognized as the Method of the Year 2015 by Nature Methods, SingleParticle.com offers single-particle cryo-electron microscopy (cryoEM), working with macromolecular structures at high resolution. The advancement of cryoEM in recent years brings about two challenges to many labs; a) the large amount of image data being generated every day from state-of-the-art direct electron detectors, b) intensive computation needed for 3D reconstruction software, such as the RELION package, developed by MRC-LMB in the UK.

SingleParticle.com’s solution features:

  • Fully scalable solution from 8 nodes to hundreds of nodes
  • Hybrid CPU/GPU cluster nodes in collaboration with AMAX information technologies, a leading provider of enterprise computing infrastructure solutions
  • High performance data storage with a proprietary file system, offering 300PB in single volume and great TCO with no hardware lock-in using commodity hardware
  • Expert support and service with a focus on cryoEM software

Dr. Clara Cai, Manager at SingleParticle.com, commented; “With Bright, the management of an HPC cluster becomes very straightforward, empowering end users to administer their workloads, rather than relying on HPC experts. We are confident that with Bright’s technology, our customers can maintain our turn-key cryoEM cluster with little to no prior HPC experience.”

Clemens Engler, Director Alliances at Bright Computing, added; “We welcome SingleParticle.com to the Bright partner community. This is an exciting opportunity for Bright technology to serve the cryoEM researchers.”

About Bright Computing

Bright Computing is a leading provider of hardware-agnostic cluster and cloud management software in the world. Bright Cluster Manager, Bright Cluster Manager for Big Data, and Bright OpenStack provide a unified approach to installing, provisioning, configuring, managing, and monitoring HPC clusters, big data clusters, and OpenStack clouds. Bright’s products are currently deployed in more than 650 data centers around the world. Bright Computing’s customer base includes global academic, governmental, financial, healthcare, manufacturing, oil/gas/energy, and pharmaceutical organizations such as Boeing, Intel, NASA, Stanford University, and St. Jude Children’s Research Hospital. Bright partners with Amazon, Cray, Dell, Intel, Nvidia, SGI, and other leading vendors to deliver powerful, integrated solutions for managing advanced IT infrastructure such as high-performance computing clusters, big data clusters, and OpenStack-based private clouds.  www.brightcomputing.com

Source: Bright Computing

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Exxact Announces HPC Solutions Featuring NVIDIA Tesla V100 GPU Accelerators

Thu, 09/28/2017 - 10:44

FREMONT, Calif., Sept. 28, 2017 — Exxact Corporation, a provider of high performance computing, today announced its planned production of HPC solutions using the new NVIDIA Tesla V100 GPU accelerator. Exxact will be integrating the Tesla V100 into its Quantum series of servers, which are currently offered with NVIDIA Tesla P100 GPUs. The NVIDIA Tesla V100 was first introduced at the GPU Technology Conference 2017 held in San Jose, California. 

The NVIDIA Tesla V100 is engineered for the convergence of AI and HPC. It offers a platform for Exxact HPC systems to excel at both computational science for scientific simulation and data science for finding insights in data. By pairing NVIDIA CUDA cores and Tensor Cores within a unified architecture, a single Exxact Quantum server with Tesla V100 GPUs can replace hundreds of commodity CPU-only servers for both traditional HPC and AI workloads. Every researcher and engineer can now afford an AI supercomputer to tackle their most challenging work with Exxact Quantum servers featuring NVIDIA Tesla V100 GPUs.

“The NVIDIA Tesla V100 GPU accelerator introduces a new foundation for artificial intelligence.” said Jason Chen, Vice President of Exxact Corporation. “With its key compute features coupled with top tier performance and efficiency, the Tesla V100 GPUs will enable us to create exceptional HPC systems designed to power the most computationally intensive workloads.”

NVIDIA Tesla V100 is the world’s most advanced data center GPU ever built to accelerate AI, HPC, and graphics. Powered by the latest GPU architecture, NVIDIA Volta, Tesla V100 offers the performance of 100 CPUs in a single GPU—enabling data scientists, researchers, and engineers to tackle challenges that were once impossible. The Tesla V100 comes in two form factors:

  • Tesla V100 for NVIDIA NVLink (SXM2): Ultimate performance for deep learning
  • Tesla V100 for PCIe: Highest versatility for all workloads

With 640 Tensor Cores, Tesla V100 is the world’s first GPU to break the 100 teraflops (TFLOPS) barrier of deep learning performance. The next generation of NVIDIA NVLink high-speed interconnect technology connects multiple V100 GPUs at up to 300 GB/s to create the world’s most powerful computing servers. AI models that would consume weeks of computing resources on previous systems can now be trained in a few days. With this dramatic reduction in training time, a whole new world of problems will now be solvable with AI.

Tesla V100 Specifications:

  • 5,120 CUDA cores
  • 640 New Tensor Cores
  • 7.8 TFLOPS double-precision performance with NVIDIA GPU Boost
  • 15.7 TFLOPS single-precision performance with NVIDIA GPU Boost
  • 125 TFLOPS mixed-precision deep learning performance with NVIDIA GPU Boost
  • 300 GB/s bi-directional interconnect bandwidth with NVIDIA NVLink
  • 900 GB/s memory bandwidth with CoWoS HBM2 Stacked Memory
  • 16 GB of CoWoS HBM2 Stacked Memory
  • 300 Watt

About Exxact Corporation

Exxact develops and manufactures innovative computing platforms and solutions that include workstation, server, cluster, and storage products developed for Life Sciences, HPC, Big Data, Cloud, Visualization, Video Wall, and AV applications. With a full range of engineering and logistics services, including consultancy, initial solution validation, manufacturing, implementation, and support, Exxact enables their customers to solve complex computing challenges, meet product development deadlines, improve resource utilization, reduce energy consumption, and maintain a competitive edge. Visit Exxact Corporation at www.exxactcorp.com.

Source: Exxact Corporation

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AMAX Deep Learning Solutions Upgraded with NVIDIA Tesla V100 GPU Accelerators

Thu, 09/28/2017 - 09:09

FREMONT, Calif., Sept. 28, 2017 — AMAX, a provider of Deep Learning, HPC, Cloud/IaaS servers and appliances, today announced that its GPU solutions, including Deep Learning platforms, are now available with the latest NVIDIA Tesla V100 GPU accelerator. Solutions featuring the V100 GPUs are expected to begin shipping in Q4 2017.

Powered by the new NVIDIA Volta architecture, AMAX’s V100-based computing solutions are the most powerful GPU solutions on the market to accelerate HPC, Deep Learning, and data analytic workloads. The solutions combine the latest Intel Xeon Scalable Processor series with Tesla V100 GPUs to enable 6x the Tensor FLOPS for DL inference when compared to the previous generation NVIDIA Pascal GPUs.

“We are thrilled about the biggest breakthrough we’ve ever seen on data center GPUs,” said James Huang, Product Marketing Manager, AMAX. “This will deliver the most dramatic performance gains and cost savings opportunities for HPC and the AI industry that we cannot wait to see.”

NVIDIA Tesla V100 GPU accelerators are the most advanced data center GPUs ever built to accelerate AI, HPC and graphics applications. Equipped with 640 Tensor Cores, a single V100 GPU offers the performance of up to 100 CPUs, enabling data scientists, researchers, and engineers to tackle challenges that were once thought to be impossible. The V100 features six major technology breakthroughs:

  • New Volta Architecture: By pairing CUDA cores and Tensor Cores within a unified architecture, a single server with Tesla V100 GPUs can replace hundreds of commodity CPU servers for traditional HPC and Deep Learning.
  • Tensor Core: Equipped with 640 Tensor Cores, Tesla V100 delivers 125 TeraFLOPS of deep learning performance. That’s 12X Tensor FLOPS for Deep Learning training, and 6X Tensor FLOPS for DL inference when compared to NVIDIA Pascal GPUs.
  • Next-Generation NVIDIA NVLink Interconnect Technology: NVLink in Tesla V100 delivers 2X higher throughput compared to the previous generation. Up to eight Tesla V100 accelerators can be interconnected at up to 300 GB/s to unleash the highest application performance possible on a single server.
  • Maximum Efficiency Mode: The new maximum efficiency mode allows data centers to achieve up to 40% higher compute capacity per rack within the existing power budget. In this mode, Tesla V100 runs at peak processing efficiency, providing up to 80 percent of the performance at half the power consumption.
  • HBM2: With a combination of improved raw bandwidth of 900 GB/s and higher DRAM utilization efficiency at 95 percent, Tesla V100 delivers 1.5X higher memory bandwidth over Pascal GPUs as measured on STREAM benchmark.
  • Programmability: Tesla V100 is architected from the ground up to simplify programmability. Its new independent thread scheduling enables finer-grain synchronization and improves GPU utilization by sharing resources among small jobs.

AMAX solutions that will feature the V100 include:

  • MATRIX DL-in-a-Box Solutions — The MATRIX Deep-Learning-in-a-Box solutions provide everything a data scientist needs for Deep Learning development. Powered by Bitfusion Flex, the product line encompasses powerful dev workstations, high-compute density servers, and rackscale clusters featuring pre-installed Docker containers with the latest DL frameworks, and GPU virtualization technology to attach local and remote GPUs. The MATRIX solutions can be used as standalone platforms or combined to create the perfect infrastructure for on-premise AI clouds or elastic DL-as-a-Service platforms.
  • [SMART]Rack AI — [SMART]Rack AI is a turnkey Machine Learning cluster for training and inference at scale. The solution features up to 96x NVIDIA® Tesla® GPU accelerators to deliver up to 1344 TFLOPs of compute power when populated with Tesla V100 PCle cards. Delivered plug-and-play, the solution also features an All-Flash data repository, 25G high-speed networking, [SMART]DC Data Center Manager, an In-Rack Battery for graceful shutdown during a power loss scenario.
  • ServMax G480 — The G480 is a robust 4U 8x GPU platform for HPC and Deep Learning workloads, delivering 56 TFLOPs of double precision or 112 TFLOPs of single precision when populated with Tesla V100 PCle cards.

As an Elite member of the NVIDIA Partner Network Program, AMAX is stringent in providing cutting-edge technologies, delivering enhanced, energy-efficient performance for the Deep Learning and HPC industries featuring NVIDIA Tesla V100, P100, P40 GPU accelerators, and NVIDIA DGX systems. AMAX is now accepting pre-orders, quotes and consultations for the Tesla V100-based systems. To learn more about AMAX and GPU solutions, please visit www.amax.com or contact AMAX.

About AMAX

AMAX is an award-winning leader in application-tailored data center, HPC and Deep Learning solutions designed towards highest efficiency and optimal performance. Recognized by several industry awards, including First Place at ImageNet Large Scale Visual Recognition Challenge, AMAX aims to provide cutting-edge solutions to meet specific customer requirements. Whether you are a Fortune 1000 company seeking significant cost savings through better efficiency for your global data centers, or you’re a software startup seeking an experienced manufacturing partner to design and launch your flagship product, AMAX is your trusted solutions provider, delivering the results you need to meet your specific metrics for success. To learn more or request a quote, contact AMAX.

Source: AMAX

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US Coalesces Plans for First Exascale Supercomputer: Aurora in 2021

Wed, 09/27/2017 - 17:34

At the Advanced Scientific Computing Advisory Committee (ASCAC) meeting, in Arlington, Va., yesterday (Sept. 26), it was revealed that the “Aurora” supercomputer is on track to be the United States’ first exascale system. Aurora, originally named as the third pillar of the CORAL “pre-exascale” project, will still be built by Intel and Cray for Argonne National Laboratory, but the delivery date has shifted from 2018 to 2021 and target capability has been expanded from 180 petaflops to 1,000 petaflops (1 exaflop).

The fate of the Argonne Aurora “CORAL” supercomputer has been in limbo since the system failed to make it into the U.S. DOE budget request, while the same budget proposal called for an exascale machine “of novel architecture” to be deployed at Argonne in 2021. Until now, the only official word from the U.S. Exascale Computing Project was that Aurora was being “reviewed for changes and would go forward under a different timeline.”

Officially, the contract has been “extended,” and not cancelled, but the fact remains that the goal of the Collaboration of Oak Ridge, Argonne, and Lawrence Livermore (CORAL) initiative to stand up two distinct pre-exascale architectures was not met.

According to sources we spoke with, a number of people at the DOE are not pleased with the Intel/Cray (Intel is the prime contractor, Cray is the subcontractor) partnership. It’s understood that the two companies could not deliver on the 180-200 petaflops system by next year, as the original contract called for. Now Intel/Cray will push forward with an exascale system that is some 50x larger than any they have stood up.

It’s our understanding that the cancellation of Aurora is not a DOE budgetary measure as has been speculated, and that the DOE and Argonne wanted Aurora. Although it was referred to as an “interim,” or “pre-exascale” machine, the scientific and research community was counting on that system, was eager to begin using it, and they regarded it as a valuable system in its own right. The non-delivery is regarded as disruptive to the scientific/research communities.

Another question we have is that since Intel/Cray failed to deliver Aurora, and have moved on to a larger exascale system contract, why hasn’t their original CORAL contract been cancelled and put out again to bid? With increased global competitiveness, it seems that the DOE stakeholders did not want to further delay the non-IBM/Nvidia side of the exascale track. Conceivably, they could have done a rebid for the Aurora system, but that would leave them with an even bigger gap if they had to spin up a new vendor/system supplier to replace Intel and Cray. Starting the bidding process over again would delay progress toward exascale – and it might even have been the death knell for exascale by 2021, but Intel and Cray now have a giant performance leap to make and three years to do it. Will they stay on the same Phi-based technology path with Knights Hill or come up with something more “novel,” like the co-packaged Xeon/FPGA processor that Intel is working on and which could provide further efficiencies to meet strict exascale power targets.

These events beg the question regarding the IBM-led effort and whether IBM/Nvidia/Mellanox are looking very good by comparison. The other CORAL thrusts — Summit at Oak Ridge and Sierra at Lawrence Livermore — are on track, although it remains to be seen whether one, both or neither of these systems will make the cut for the November Top500 list.

We reached out to representatives from Cray, Intel and the Exascale Computing Project (ECP) seeking official comment on the revised Aurora contract. Cray declined to comment and we did not hear back from Intel or ECP by press time. We will update the story as we learn more.

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LBNL-led Effort Receives $3M to Advance Quantum Computing

Wed, 09/27/2017 - 13:43

Two teams led by Lawrence Berkeley National Laboratory researchers have received $3 million from the Department of Energy to advance quantum computing software and hardware. It’s an ambitious five year-project in which the hardware team hopes to eventually demonstrate a 64-qubit processor with full control.

LBNL has been exploring quantum computing for some time. Indeed, using Laboratory Directed Research and Development (LDRD) funding, LBNL researchers developed quantum chemistry and optimization algorithms, as well as prototype superconducting quantum processors. Recently, they proved the viability of their work by using these algorithms on a quantum processor comprising two superconducting transmon quantum bits to successfully solve the chemical problem of calculating the complete energy spectrum of a hydrogen molecule.

The new DOE grant will extend that research. One team will receive $1.5 million over three years to develop novel algorithms, compiling techniques and scheduling tools that will enable near-term quantum computing platforms to be used for scientific discovery in the chemical sciences. The other team will work closely with these researchers to design prototype four- and eight-qubit processors to compute these new algorithms. This project will last five years and the researchers will receive $1.5 million for their first year of work. An article describing the new project was posted yesterday on the LBNL web site. This work is supported by the DOE Office of Science.

“Someday, universal quantum computers will be able to solve a wide range of problems, from molecular design to machine learning and cybersecurity, but we’re a long way off from that. So, the question we are currently asking is whether there are specific problems that we can solve with more specialized quantum computers,” says Irfan Siddiqi, Berkeley Lab Scientist and Founding Director of the Center for Quantum Coherent Science at UC Berkeley. This work is supported by the DOE Office of Science.

“Computational approaches are common across most scientific projects at Berkeley Lab. As Moore’s Law is slowing down, novel computing architectures, system, and techniques have become a priority initiative at Berkeley Lab,” says Horst Simon, Berkeley Lab’s Deputy Director. “We recognized early how quantum simulation could provide an effective approach to some of the most challenging computational problems in science, and I am pleased to see recognition of our LDRD initiative through this first direct funding. Quantum information science will become an increasingly important element of our research enterprise across many disciplines.”

Link to LBNL article: https://cs.lbl.gov/news-media/news/2017/a-quantum-computer-to-tackle-fundamental-science-problems/

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ARCHER, EPCC Announce Winners of ARCHER Supercomputing Competition

Wed, 09/27/2017 - 10:38

Sept. 27, 2017 — EPCC, University of Edinburgh and the Engineering and Physical Sciences Research Council (EPSRC) are delighted to announce the 10 winners of the recent ARCHER Best-Use Travel Competition:

  • Tai Duc Bui, Department of Chemical Engineering at University College London;
  • Nguyen Anh Koah Doan, Zhi Chen & Ivan Langella, Department of Engineering at the University of Cambridge;
  • Alex Ganose, Department of Chemistry at University College London;
  • Chiara Gattinoni, Tribiology group, Department of Mechanical Engineering at Imperial College London and Materials Theory at ETH Zürich;
  • Thomas Mellan, Thomas Young Centre for the Theory and Simulation of Materials at Imperial College London;
  • Michael Ruggiero, Department of Chemical Engineering and Biotechnology at the University of Cambridge;
  • Nathan Sime, Department of Engineering at the University of Cambridge;
  • Gabriele Sosso, Martin Fitzner & Philipp Pedevilla Department of Physics & Astronomy at University College London;
  • Guido von Rudorff, Department of Physics & Astronomy at University College London;
  • Zhong-Nan Wang, Department of Engineering at the University of Cambridge.

The winning entries covered a broad range of topics, including:

  • helping to prevent pipeline blockages in the oil and gas industry;
  • improving the performance of solar [power] by studying photovoltaic panel materials;
  • and simulating combustion engines in order to improve efficiency and to reduce environmental impact.

The competition will facilitate these early career researchers, who are all either Ph.D. candidates or Postdoctoral researchers, to build and develop their international network. ARCHER and EPSRC both recognise the importance of enabling young researchers to build their personal network to help build collaborations and skills. ARCHER Computational Science and Engineering Service Deputy Director Lorna Smith said “We are really pleased to have had the opportunity to help early career researchers develop and enhance their science through international collaboration”

The competition aimed to identify the best scientific use of ARCHER, the UK’s national supercomputing facility, within the arena of the engineering and physical sciences. The winners will be using their £3000 awards to build research collaborations between the UK and US and will be visiting research groups at US institutions to further their research portfolios.

The competition was run by ARCHER on behalf of EPSRC which funds the supercomputer in partnership with the Natural Environment Research Council (NERC).

Dr. Eddie Clarke, EPSRC’s Contract Manager for ARCHER believes that identifying the next generation of experts and helping them develop the skills to thrive in academia is key to forwarding the advancement of the UK research community: “As we see the increasing need for high performance computing to tackle today’s complex scientific questions, we recognise the need to encourage today’s young researchers to bring their skills to the world. The winners of these awards have shown ability, enthusiasm and real skill in their research and these prizes will help them work together with partners overseas to benefit science in the UK.”

The Awards will be presented at an evening reception in London on 28th September. The winners will come together once again in 2018 to share with the supercomputing community the impact of the award they received.

ARCHER provides high performance computing support for research and industry projects in the UK.

Source: University of Edinburgh

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Nvidia, Partners Announce Several V100 Servers

Wed, 09/27/2017 - 10:13

Here come the Volta 100-based servers. Nvidia today announced an impressive line-up of servers from major partners – Dell EMC, Hewlett Packard Enterprise, IBM, and Supermicro – all featuring Nvidia’s new V100 GPUs. Availability information was not immediately clear but with SC17 approaching in November it’s likely at least a few of the new servers will be on display.

The V100, of course, is Nvidia’s latest and most powerful GPU. It began shipping in quantity only recently. It is literally a whale of a chip with more than “21 billion transistors, as well as 640 Tensor Cores, the latest NVLink high-speed interconnect technology, and 900 GB/sec HBM2 DRAM to achieve 50 percent more memory bandwidth than previous generation GPUs.”

The new servers include:

  • Dell EMC – The PowerEdge R740 supporting up to three V100 GPUs for PCIe, the PowerEdge R740XD supporting up to three V100 GPUs for PCIe, and the PowerEdge C4130 supporting up to four V100 GPUs for PCIe or four V100 GPUs for NVIDIA NVLink interconnect technology in an SXM2 form factor.
  • HPE – HPE Apollo 6500 supporting up to eight V100 GPUs for PCIe and HPE ProLiant DL380 systems supporting up to three V100 GPUs for PCIe.
  • IBM – The ‘next generation’ of IBM Power Systems servers based on the POWER9 processor will incorporate multiple V100 GPUs and take advantage of the latest generation NVLink interconnect technology — ‘featuring fast GPU-to-GPU interconnects and an industry-unique OpenPOWER CPU-to-GPU design for maximum throughput.’
  • Supermicro – Products supporting the new Volta GPUs include a 7048GR-TR workstation for all-around high-performance GPU computing, 4028GR-TXRT, 4028GR-TRT and 4028GR-TR2 servers designed to handle the most demanding deep learning applications, and 1028GQ-TRT servers built for applications such as advanced analytics.

Nvidia says the V100 GPU can deliver the equivalent performance of 100 CPUs for many data intensive workloads. The variety of configurations announced by the major systems vendors should certainly accommodate a wide variety of needs and applications.

“Volta systems built by our partners will ensure that enterprises around the world can access the technology they need to accelerate their AI research and deliver powerful new AI products and services,” said Ian Buck, vice president and general manager of Accelerated Computing at Nvidia, in the official announcement.

IBM’s Brad McCredie

The IBM announcement is notable for its intended use of IBM’s Power9 chip. Brad McCredie, vice president and IBM Fellow, Cognitive Systems Development at IBM, is quoted saying, “IBM’s upcoming POWER9 servers will support NVIDIA’s Volta GPU, and will be the only one to support the latest generation of NVLink and PCIe 4.0, which will deliver maximum throughput.”

McCredie posted a blog coinciding with the announcement (Proposition: No speed limit on NVIDIA Volta with rise of AI). In it he took a shot at Intel – “Intel-based systems seem to be designed for yesterday’s era of architecture: defined by determinative code, not for free-flowing data, streaming sensors and always-on algorithms” – adding, “Servers with POWER9 and Volta, with its second-generation NVIDIA NVLINK, PCI-Express 4, and Memory Coherence technologies, and unprecedented internal bandwidth, will blow people away.”

The first IBM Power9 chips as well as new acceleration technologies will be used in the U.S. Department of Energy Summit Supercomputer at the Oak Ridge National Laboratory and the Sierra Supercomputer at the Lawrence Livermore National Laboratory. There’s been anticipation that one or both of the machines may be ready in time to break into the next Top500.

Other testimonial quotes included in Nvidia’s release include:

“One of the core principles for Dell EMC is to deliver differentiated solutions to our customers so that they can leverage the most advanced technology for a competitive advantage. To that end, we are proud of the work we do with partners like NVIDIA to build PowerEdge servers ideal for compute-intensive workloads including data analytics, high-performance computing, machine learning and AI.” – Armughan Ahmad, senior vice president and general manager of Hybrid Cloud and Ready Solutions at Dell EMC

“As deep learning continues to become more pervasive, technology advancements across systems and accelerators need to evolve in order to gain intelligence from large datasets faster than ever before. The HPE Apollo 6500 and HPE ProLiant DL380 systems combine the industry-leading GPU performance of NVIDIA Tesla V100 GPU accelerators and Volta architecture with HPE unique innovations in system design and manageability to deliver unprecedented levels of performance, scale and efficiency for high performance computing and artificial intelligence applications.” – Bill Mannel, vice president and general manager of High Performance Computing and Artificial Intelligence at Hewlett Packard Enterprise

“Supermicro designs the most application-optimized GPU systems and offers the widest selection of GPU-optimized servers and workstations in the industry. Our high performance computing solutions enable deep learning, engineering and scientific fields to scale out their compute clusters to accelerate their most demanding workloads and achieve fastest time-to-results with maximum performance per watt, per square foot and per dollar. With our latest innovations incorporating the new NVIDIA V100 PCI-E and V100 SXM2 GPUs in performance-optimized 1U and 4U architectures with next-generation NVLink, our customers can accelerate their applications and innovations to help solve the world’s most complex and challenging problems.” – Charles Liang, president and CEO of Supermicro

Link to Nvidia release: http://www.marketwired.com/press-release/worlds-largest-server-companies-announce-nvidia-volta-systems-supercharged-for-ai-nasdaq-nvda-2235220.htm

Link to IBM blog: https://www.ibm.com/blogs/systems/proposition-no-speed-limit-on-nvidia-volta-with-rise-of-ai/

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World’s Largest Server Companies Announce NVIDIA Volta Systems Supercharged for AI

Wed, 09/27/2017 - 09:09

SANTA CLARA, Calif., Sept. 27, 2017 — NVIDIA (NASDAQ: NVDA) and its systems partners Dell EMC, Hewlett Packard Enterprise, IBM and Supermicro today unveiled more than 10 servers featuring NVIDIA Volta architecture-based Tesla V100 GPU accelerators — the world’s most advanced GPUs for AI and other compute-intensive workloads.

NVIDIA V100 GPUs, with more than 120 teraflops of deep learning performance per GPU, are uniquely designed to deliver the computing performance required for AI deep learning training and inferencing, high performance computing, accelerated analytics and other demanding workloads. A single Volta GPU offers the equivalent performance of 100 CPUs, enabling data scientists, researchers and engineers to tackle challenges that were once impossible.

Seizing on the AI computing capabilities offered by NVIDIA’s latest GPUs, Dell EMC, HPE, IBM and Supermicro are bringing to the global market a broad range of multi-V100 GPU systems in a variety of configurations.

“Volta systems built by our partners will ensure that enterprises around the world can access the technology they need to accelerate their AI research and deliver powerful new AI products and services,” said Ian Buck, vice president and general manager of Accelerated Computing at NVIDIA.

V100-based systems announced include:

  • Dell EMC — The PowerEdge R740 supporting up to three V100 GPUs for PCIe, the PowerEdge R740XD supporting up to three V100 GPUs for PCIe, and the PowerEdge C4130 supporting up to four V100 GPUs for PCIe or four V100 GPUs for NVIDIA NVLink interconnect technology in an SXM2 form factor.
  • HPE — HPE Apollo 6500 supporting up to eight V100 GPUs for PCIe and HPE ProLiant DL380 systems supporting up to three V100 GPUs for PCIe.
  • IBM — The next generation of IBM Power Systems servers based on the POWER9 processor will incorporate multiple V100 GPUs and take advantage of the latest generation NVLink interconnect technology — featuring fast GPU-to-GPU interconnects and an industry-unique OpenPOWER CPU-to-GPU design for maximum throughput.
  • Supermicro — Products supporting the new Volta GPUs include a 7048GR-TR workstation for all-around high-performance GPU computing, 4028GR-TXRT, 4028GR-TRT and 4028GR-TR2 servers designed to handle the most demanding deep learning applications, and 1028GQ-TRT servers built for applications such as advanced analytics.

These partner systems complement an announcement yesterday by China’s leading original equipment manufacturers — including Inspur, Lenovo and Huawei — that they are using the Volta architecture for accelerated systems for hyperscale data centers.

Additional NVIDIA V100 Details

Each NVIDIA V100 GPU features over 21 billion transistors, as well as 640 Tensor Cores, the latest NVLink high-speed interconnect technology, and 900 GB/sec HBM2 DRAM to achieve 50 percent more memory bandwidth than previous generation GPUs.

V100 GPUs are supported by NVIDIA Volta-optimized software, including CUDA 9.0 and the newly updated deep learning SDK, including TensorRT 3DeepStream SDK and cuDNN 7 as well as all major AI frameworks. Additionally, hundreds of thousands of GPU-accelerated applications are available for accelerating a variety of data-intensive workloads, including AI training and inferencing, high performance computing, graphics and advanced data analytics.

About NVIDIA

NVIDIA‘s (NASDAQ: NVDA) invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. More information at http://nvidianews.nvidia.com/.

Source: NVIDIA

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AMAX.AI Launches [SMART]Rack AI Machine Learning Cluster

Wed, 09/27/2017 - 08:50

FREMONT, Calif., Sept. 27, 2017 — AMAX.AI, a division of AMAX Information Technologies, Inc., specializing in high-performance platforms for AI and Deep Learning development, will be launching the [SMART]Rack AI Machine Learning cluster at the AI Summit 2017 (Booth #G27), to be held in the Regency Center, San Francisco, California on Sept. 27th and 28th.

The [SMART]Rack AI solution is an extension of AMAX.AI’s MATRIX GPU Cloud product line which includes powerful dev workstations, high-compute density servers and now a turnkey Machine Learning cluster in [SMART]Rack AI. The all-inclusive rackscale platform is maximized for performance featuring up to 96x NVIDIA Tesla P40, P100 or V100 GPU cards, providing well over 1 PetaFLOP of compute power per rack. The solution is fully-loaded with features designed to accelerate compute as well as data-transfer performance while offering the ultimate in manageability. Solution components include: an All-Flash storage appliance for an ultra-fast in-rack data repository; 25G high-speed network; [SMART]DC HPC-optimized DCIM to remotely monitor, manage and orchestrate GPU-based Machine Learning hardware where real-time temperature, power and system health monitoring are critical for uninterrupted operation; and an in-rack battery for graceful shutdowns in the event of a power loss scenario. The [SMART]Rack AI can serve as a powerful standalone platform or as a scalable Machine-Learning-at-scale building block, and is the perfect platform in which to build on-premise AI Cloud and Deep-Learning-as-a-Service infrastructure.

“The [SMART]Rack AI is revolutionary to Deep Learning data centers,” said Dr. Rene Meyer, VP of Technology, AMAX. “Because it not only provides the most powerful application-based computing power, but it expedites DL model training cycles by improving efficiency and manageability through integrated management, network, battery and cooling all in one enclosure.”

The MATRIX product line also features powerful DL dev workstations ideal for start-ups, incubators and individual researchers to set up Deep Learning labs, and highly-compute dense yet ultra-compact Machine Learning servers that can easily be scaled within a rack to increase compute power on demand.

All MATRIX solutions come pre-loaded with an end-to-end Deep Learning software, powered by Bitfusion Flex, geared towards accelerating GPU development while dynamically managing GPU resource and workflow management. The software features preloaded environments containing the latest frameworks to quickly begin building models for training within minutes, and GPU over Fabrics technology to enable the sharing & scaling of large numbers of local and remote GPUs across any MATRIX systems for multi-tenancy and highly-customizable self-service features.

AMAX will be holding live demos of the MATRIX GPU Cloud solutions during exhibition hours at the AI Summit 2017. To learn more about fast-tracking AI with DL-in-a-Box Solutions, please visit Booth #G27 or schedule a demo here.

About AMAX

AMAX AI is a division of AMAX Information Technologies, Inc., specializing in award-winning high-performance platforms for AI and Deep Learning development. As a thought leader and early innovator in the burgeoning market for Deep Learning technology, AMAX AI works with cutting-edge startups, research universities and global corporations to give its customers access to early innovations and game-changing DL technology.  From high-compute density GPU servers and supercharged dev workstations, to DGX supercomputers and turnkey rackscale platforms used to power on-premise AI Clouds or DL-as-a-Service, AMAX AI enables companies to build out the Deep Learning infrastructures they need to handle the rigors of development, training, and inference at any scale. To learn more, please visit www.amax.ai.

Source: AMAX

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Supermicro Introduces Portfolio of GPU Optimized systems for NVIDIA Tesla V100 GPUs

Wed, 09/27/2017 - 08:41

SAN JOSE, California, Sept. 27, 2017 — Super Micro Computer, Inc. (NASDAQ: SMCI), a leader in enterprise computing, storage, and networking solutions and green computing technology, today announced support for NVIDIA Tesla V100 PCI-E and V100 SXM2 GPUs on its industry leading portfolio of GPU server platforms.

For maximum acceleration of highly parallel applications like artificial intelligence (AI), deep learning, autonomous vehicle systems, energy and engineering/science, Supermicro’s new 4U system with next-generation NVIDIA NVLink is optimized for overall performance.  The SuperServer 4028GR-TXRT supports eight NVIDIA Tesla V100 SXM2 GPU accelerators with maximum GPU-to-GPU bandwidth for important HPC clusters and hyper-scale workloads.  Incorporating the latest NVIDIA NVLink GPU interconnect technology with over five times the bandwidth of PCI-E 3.0, this system features an independent GPU and CPU thermal zoning design, which ensures uncompromised performance and stability under the most demanding workloads.

Similarly, the performance optimized 4U SuperServer 4028GR-TRT2 system can support up to 10 PCI-E Tesla V100 accelerators with Supermicro’s innovative and GPU optimized single root complex PCI-E design, which dramatically improves GPU peer-to-peer communication performance.  For even greater density, the SuperServer 1028GQ-TRT supports up to four PCI-E Tesla V100 GPU accelerators in only 1U of rack space.  Ideal for media, entertainment, medical imaging, and rendering applications, the powerful 7049GP-TRT workstation supports up to four NVIDIA Tesla V100 GPU accelerators.

“Supermicro designs the most application-optimized GPU systems and offers the widest selection of GPU-optimized servers and workstations in the industry,” said Charles Liang, President and CEO of Supermicro. “Our high performance computing solutions enable deep learning, engineering and scientific fields to scale out their compute clusters to accelerate their most demanding workloads and achieve fastest time-to-results with maximum performance per watt, per square foot and per dollar. With our latest innovations incorporating the new NVIDIA V100 PCI-E and V100 SXM2 GPUs in performance-optimized 1U and 4U systems with next-generation NVLink, our customers can accelerate their applications and innovations to help solve the world’s most complex and challenging problems.”

“Supermicro’s new high-density servers are optimized to fully leverage the new NVIDIA Tesla V100 data center GPUs to provide enterprise and HPC customers with an entirely new level of computing efficiency,” said Ian Buck, vice president and general manager of the Accelerated Computing Group at NVIDIA. “The new SuperServers deliver dramatically higher throughput for compute-intensive data analytics, deep learning and scientific applications while minimizing power consumption.”

With the convergence of Big Data Analytics, the latest NVIDIA GPU architectures, and improved Machine Learning algorithms, Deep Learning applications require the processing power of multiple GPUs that must communicate efficiently and effectively to expand the GPU network.  Supermicro’s single-root GPU system allows multiple GPUs to communicate efficiently to minimize latency and maximize throughput as measured by the NCCL P2PBandwidthTest.

About Super Micro Computer, Inc. (NASDAQ: SMCI)

Supermicro (NASDAQ: SMCI), the leading innovator in high-performance, high-efficiency server technology is a premier provider of advanced Server Building Block Solutions for Data Center, Cloud Computing, Enterprise IT, Hadoop/Big Data, HPC and Embedded Systems worldwide. Supermicro is committed to protecting the environment through its “We Keep IT Green” initiative and provides customers with the most energy-efficient, environmentally-friendly solutions available on the market.

Source: Supermicro

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BOXX Sponsors SOLIDWORKS 2018 Launch with Innovation, Presentation, and More

Tue, 09/26/2017 - 12:12

AUSTIN, Texas, Sept. 26, 2017 — BOXX Technologies, the leading innovator of high-performance workstations, rendering systems, and servers, today announced their official sponsorship of SOLIDWORKS 2018. The 25th release of the engineering and product design application will be unveiled live, Sept. 26, at 10:00 am EST and available to online viewers by registering here. This year, the event will feature remarks from SOLIDWORKS CEO Gian Paolo Bassi and other key company executives, as well as presentations from industry partners like BOXX.

“As technology partners and SOLIDWORKS users ourselves, we’re proud to offer the world’s fastest SOLIDWORKS workstations and to sponsor the launch of SOLIDWORKS 2018,” said Tim Lawrence, BOXX founder and VP of Engineering. “Throughout the world, BOXX innovation and expertise deliver real ROI to SOLIDWORKS users, enabling them to bring their products to market faster and more efficiently.”

During the live event, SOLIDWORKS CEO Gian Paolo Bassi will discuss the company’s vision for product and technology strategies that will transform the way products are designed, manufactured, and supported. Key executives will provide updates on new product development initiatives, strategic partnerships, community engagement, and educational programs, as well as new SOLIDWORKS 2018 features and enhancements. The launch is rounded out by a BOXX presentation, followed by presentations from other industry partners.

A designated SOLIDWORKS Solution Partner and leading manufacturer of SOLIDWORKS-certified APEXX workstations, BOXX uses SOLIDWORKS software to design its workstation, server, and rendering system chassis. To coincide with the launch, BOXX created How to Configure Your SOLIDWORKS 2018 Workstation, an informative blog available at the SOLIDWORKS 2018 launch site, while the BOXX website includes a SOLIDWORKS Solutions page with recommended systems, a promotional video, and an overview of new SOLIDWORKS 2018 features.

“BOXX APEXX workstations enhance SOLIDWORKS user productivity by providing faster rebuilds, reduced open and save times, and overall improved interactivity with large assemblies,” said Lawrence. “When engineers and product designers upgrade to APEXX, they’ll discover why BOXX is the ideal SOLIDWORKS 2018 solution.”

For further information and pricing on BOXX SOLIDWORKS solutions, contact a sales consultant in the US at 1-877-877-2699. Learn more about BOXX systems, finance options, and how to contact worldwide resellers, by visiting www.boxx.com.

About BOXX Technologies

BOXX is a leading innovator of high-performance computer workstations, rendering systems, and servers for engineering, product design, architecture, visual effects, animation, deep learning, and more. For 21 years, BOXX has combined record-setting performance, speed, and reliability with unparalleled industry knowledge to become the trusted choice of creative professionals worldwide. For more information, visit www.boxx.com.

Source: BOXX

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Wondering How AI is Doing Versus Doctors?

Tue, 09/26/2017 - 10:54

With all the noise around AI’s potential in medicine, you may be wondering how well it is actually performing. No one knows the real answer – for one thing it is a moving target – but the IEEE Spectrum is attempting to keep a rough scorecard using an interactive infographic, the latest published today.

Not surprisingly the answer to AI’s medical acumen varies by types of diagnosis and action taken. The IEEE effort tracked progress by date. As of August 2017, the most recent milestone, AI was tied with human doctors in diagnosing brain cancer but was not as effective coming up with the preferred treatment. Earlier this year AI was deemed better at diagnosing heart attacks, strokes, and autism. The range of conditions looked at is still quite modest.

The interactive scorecard is a quick look at some interesting areas of work. AI was deemed somewhat better at diagnosing Alzheimer’s as far back as June 2016 and AI-controlled robotic surgery was somewhat better than human surgeons on select procedures as of May 2016. No doubt there are many (conflicting) views on AI’s progress in medicine but this is an interesting, quick take.

Link to IEEE AI vs Doctors interactive infographic: https://spectrum.ieee.org/static/ai-vs-doctors

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Biggest Realm of Panasas ActiveStor Worldwide Deployed at Science and Technology Facilities Council

Tue, 09/26/2017 - 09:31

SUNNYVALE, Calif., Sept. 26, 2017 — Panasas Inc., the leader in performance scale-out network-attached storage (NAS), today announced that the Science and Technology Facilities Council’s (SFTC) Rutherford Appleton Laboratory (RAL)in the UK has expanded its JASMIN super-data-cluster with an additional 1.6 petabytes (PB) of Panasas ActiveStor®storage, bringing total storage capacity to 20PB. This expansion required the formation of the largest realm of Panasas storage worldwide, which is managed by a single systems administrator. Thousands of users worldwide find, manipulate and analyze data held on JASMIN, which processes an average of 1-3PB of data every day.

STFC and the UK’s Natural Environment Research Council (NERC) pioneered climate data analysis at petabyte scale with the JASMIN infrastructure. JASMIN is a highly flexible system combining petabytes of high-performance storage with batch and cloud computing over terabit-bandwidth networking to support data analysis at scale for all UK environmental science communities and their worldwide collaborators.

JASMIN underlies many environmental scientific efforts, including the World Climate Research Programme (WCRP) global model intercomparison project (CMIP5,6) which feeds into the Intergovernmental Panel on Climate Change (IPCC) reports, and programs such as the Global Surface Displacement Monitoring program, which collects data from space on a global scale to monitor and model earthquakes, volcanoes, tectonics and the retreat of ice.

“We are proud of our long-term partnership with RAL and STFC, and of our ability to facilitate research that protects the lives and livelihood of all who inhabit the planet,” said Faye Pairman, chief executive officer at Panasas. “We remain committed to meeting STFC’s needs for affordable storage solutions that deliver performance, reliability and manageability at any scale, without compromise.”

ActiveStor accelerates workflows and drives time-to-results with an easily-managed storage system that seamlessly scales to immediately contribute more storage capacity and processing power to any number of computing clients across the entire system. ActiveStor is delivered as a fully integrated clustered NAS appliance solution that incorporates flash and SATA storage nodes and combines parallel data flow and direct data access technology to boost performance, increase data availability, and eliminate hotspots in a single namespace environment.

About Panasas

Panasas is the performance scale-out NAS leader for unstructured data, driving industry and research innovation by accelerating workflows and simplifying data management. Panasas ActiveStor appliances leverage the patented PanFS storage operating system and DirectFlow protocol to deliver performance and reliability at scale from an appliance that is as easy to manage as it is fast to deploy. Panasas storage is optimized for the most demanding workloads in life sciences, manufacturing, media and entertainment, energy, government as well as education environments, and has been deployed in more than 50 countries worldwide. For more information, visit www.panasas.com.

About STFC

The Science and Technology Facilities Council is keeping the UK at the forefront of international science and expertise in materials science, space and ground-based astronomy technologies, laser science and microelectronics, tackling some of the most significant challenges facing society such as meeting our future energy needs, monitoring and understanding climate change, and global security. The Council has a broad science portfolio and works with the academic and industrial communities to share its wafer-scale manufacturing, particle and nuclear physics, alternative energy production, radio communications and radar.

Source: Panasas

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Bright Computing Announces Integration with IBM Power Systems

Tue, 09/26/2017 - 09:02

SAN JOSE, Calif., Sept. 26, 2017 — Bright Computing, a leader in cluster and cloud infrastructure automation software, today announced that Bright Cluster Manager 8.0 now integrates with IBM Power Systems.

IBM Power Systems high performance computing servers are deployed in many of the largest clusters around the world. Configurable into highly scalable Linux clusters, Power Systems offer extreme performance for demanding workloads such as genomics, finance, computational chemistry, oil and gas exploration, and high-performance data analytics. IBM Power servers are built for modern data solutions and promote fast time to insights with solution-specific hardware accelerators, scaling-out as the data requirement grows.

Unveiled in May 2017, Bright Cluster Manager 8.0 delivers exciting new features for automation and ease-of-use for Linux-based clusters and public, private and hybrid clouds. Feature highlights include a new and highly intuitive web-based user interface, integration with Apache Mesos and Marathon, support for OpenStack Newton, and for the first time, support for IBM Power Systems servers.

Martijn de Vries, CTO at Bright Computing, commented; “At Bright, we pride ourselves on an aggressive development strategy to maintain our position as a leading provider of infrastructure management technology. Our customers are increasingly looking at POWER8, and are therefore we are very happy to be able to offer this valuable integration as part of Bright Cluster Manager 8.0.”

“The integration of Bright Cluster Manager 8.0 with IBM Power Systems has created an important new option for users running complex workloads involving high-performance data analytics,” said Sumit Gupta, VP, HPC, AI & Machine Learning, IBM Cognitive Systems. “Bright Computing’s emphasis on ease-of-use for Linux-based clusters within public, private and hybrid cloud environments speaks to its understanding that while data is becoming more complicated, the management of its workloads must remain accessible to a changing workforce.”

About Bright Computing

Bright Computing is a leading provider of hardware-agnostic cluster and cloud management software in the world. Bright Cluster Manager, Bright Cluster Manager for Big Data, and Bright OpenStack provide a unified approach to installing, provisioning, configuring, managing, and monitoring HPC clusters, big data clusters, and OpenStack clouds. Bright’s products are currently deployed in more than 650 data centers around the world. Bright Computing’s customer base includes global academic, governmental, financial, healthcare, manufacturing, oil/gas/energy, and pharmaceutical organizations such as Boeing, Intel, NASA, Stanford University, and St. Jude Children’s Research Hospital. Bright partners with Amazon, Cray, Dell, Intel, Nvidia, SGI, and other leading vendors to deliver powerful, integrated solutions for managing advanced IT infrastructure such as high-performance computing clusters, big data clusters, and OpenStack-based private clouds.

Source: Bright Computing

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Nimbix Announces High Speed Cloud Storage for AI and Deep Learning Workflows

Tue, 09/26/2017 - 08:23

DALLAS, Sept. 26, 2017 — Nimbix, Inc. today announced the immediate availability of a new high-performance storage platform in the Nimbix Cloud specifically designed for the demands of artificial intelligence and deep learning applications and workflows. The new premium JARVICE Vault is an all solid-state elastic file system which enables users to achieve tens of thousands of IO operations per second (IOPS) to feed ultra-fast GPU systems for AI and deep learning frameworks. The distributed file system also provides seamless access to data from large clusters of interconnected, bare-metal GPUs that work together to provide faster time to results.

“As enterprises, researchers and startups begin to invest in GPU-accelerated artificial intelligence technologies and workflows, they are realizing that data is a big part of this challenge,” said Steve Hebert, CEO of Nimbix. “With the new storage platform, we are helping our customers achieve performance that breaks through the bottlenecks of commodity or traditional platforms and does so with a turnkey deep learning cloud offering.”

The high-performance data storage vaults provide persistent data storage that connects dynamically to the Nimbix Cloud computing platform, which runs container native high-performance applications and workflows. The workflows deploy on bare-metal GPU systems interconnected with 56Gbps Infiniband networks, delivering performance levels required to provide real-time insights to enterprises.

The new fully encrypted JARVICE Vaults are available now and offered as a monthly subscription on a per terabyte per month basis. Contact Nimbix at https://www.nimbix.net/contact-us for pricing details and performance options.

About Nimbix

Nimbix is the leading provider of purpose-built cloud computing for machine learning, AI and HPC applications. Powered by JARVICE, the Nimbix Cloud provides high-performance software as a service, dramatically speeding up data processing for Energy, Life Sciences, Manufacturing, Media and Analytics applications. Nimbix delivers unique accelerated high-performance systems and applications from its world-class data centers as a pay-per-use service.

Source: Nimbix

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Cray Completes ClusterStor Deal, Sunsets Sonexion Brand

Mon, 09/25/2017 - 16:51

Having today completed the transaction and strategic partnership with Seagate announced back in July, Cray is now home to the ClusterStor line and will be sunsetting the Sonexion brand. This is not an acquisition; the ClusterStor assets are transferring from Seagate to Cray (minus the Seagate ClusterStor IBM Spectrum Scale product) and Cray is taking over support and maintenance for the entire ClusterStor base.

Cray is adding approximately 130 Seagate employees and all of the ClusterStor customers, said John Howarth, vice president of storage at Cray. Through its (now discontinued) Sonexion brand, the supercomputing company had roughly 50 percent of the ClusterStor install base, “plus or minus 10 points,” said Howarth.

Today Cray officially takes over development, support, manufacturing and sales of the all the Lustre-based ClusterStor products — ClusterStor L300, the next-generation ClusterStor L300N and the ClusterStor SL220. The G-series Spectrum Scale products will not be part of the transferred assets.

“IBM is changing their model so they declined to allow us to do that,” Howarth told HPCwire. “It’s disappointing because it’s a finished product and it’s always good to get a new finished product, but life will go on without it.” Cray will provide support for existing ClusterStor Spectrum Scale (formerly GPFS) installations.

“The nice thing is we’re getting brand new products,” said Howarth. “The Seagate L300N is just going to GA right now, so we’re getting a brand new fresh set of products. The first thing we’re going to do with the Seagate team when they all get on board on Monday [Sept. 25] is sit down and look hard at where we’re at and then we’re going to decide, do we do another turn of the crank on the current architecture or do we go and build next generation architectures and move forward that way.”

Cray has a four year supply agreement with Seagate to procure the drives, containers, controllers and other technology components that make up ClusterStor, “at good prices,” according to Howarth.

Howarth said that with some 90 engineers coming into the storage group, they have the critical mass to develop some new products, and he expects flash to factor in prominently.

“Flash has already moved in pretty heavily into the commercial world; we think it’s now time for it to start happening in HPC,” he shared.

“The ClusterStor Nytro product is really a first step at that. We’ve got DataWarp, IME from DDN, and in terms of a mainstream product, the ClusterStor 300N is probably the first pretty standard HPC product that will make heavy use of flash.

“We think over the next three to five years flash is going to be pretty mainstream. Three or four years from now, very few acquisitions will have servers talking directly to hard drives, maybe doing back store, but they’re too slow.”

Under Cray, Segate’s Nytro I/O manager will go forward as 300NXD. The software has caching and prefetch capability for Lustre to improve small file handling. “Lustre is a great file system if you’re doing a terabyte per second of very large files, but if you’re trying to write 500 million little tiny files, you can’t do it any worse than with Lustre,” Howarth said, pointing out Lustre’s well-known pain point. “It does not do small files well and its metadata operations get swamped.”

“Nytro software,” he explained, “writes the small writes to SSDs and then it bundles them in the background and writes them out as single big writes to the back-end Lustre file system so it’s a huge improvement in the application profile of the ClusterStor and Lustre and it will make it much easier for customers to manage their systems and they will spend a lot less time worrying about what kind of I/O is my system doing.”

The L300N product provides 16 GB/sec per scalable storage unit (SSU) and 112 GB/sec per rack, which Howarth deems “industry-leading in terms of performance on a consistent basis.”

Improving ClusterStor robustness will continue to be a focus at Cray. “One of the things we did in partnership with Seagate to help improve the robustness was as we ran these great big systems through our build systems,” Howarth said. “We hooked the Sonexion up to it and we drove it flat out in order to try to find the problems. Because it’s one thing trying to find issues with a small system, it’s another thing when it’s running at 99.9 percent capability and you start breaking things on it. If you talk to any customers of Cray’s and Seagate’s they will tell you that over the last couple of years they’ve seen a marked improvement in the robustness of the system and so our intention is to continue that work.

“Cray is good at building big systems that work and so we can intend to install that discipline in the Seagate employees that are coming over so that we’ll be doing more betas, we’ll be doing more testing, we want to get on regular cadence for maintenance releases and things like that. These are [best practices] Cray has built over the years that we want to impart on the ClusterStor customers to make their lives better.”

Cray also has more than 20 ClusterStor partners and resellers and that it will support with “a comprehensive service toolkit, shorter escalation path to development, and a single knowledge base.”

“We’re working hard to get the channel folks on board and make sure the people that were reselling ClusterStor feel comfortable and that we’ll be a good partner for them like Seagate was,” said Howarth.

On Cray’s most recent earnings call, CEO Peter Ungaro observed that the HPC storage market is outperforming the overall supercomputing market.

According to market analyst Hyperion Research’s latest numbers, global HPC external storage revenues will grow 7.8 percent over the 2016-2021 timeframe to $6.3 billion, while HPC server sales, by comparison, will grow 5.8 percent to $14.8 billion.

“Storage is the fastest-growing part of the expanding HPC market and [with ClusterStor] Cray is positioned to be an even more important player in the storage market,” said Steve Conway, senior vice president of research at Hyperion.

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CENATE Names New Director

Mon, 09/25/2017 - 13:09

RICHLAND, Wash., Sept. 25, 2017 — Two years ago, the Department of Energy’s Pacific Northwest National Laboratory established a proving ground in Richland for the next step in supercomputing development. Called the Center for Advanced Technology Evaluation, CENATE’s participating researchers have been deploying testbeds and methods that can analyze and verify new technologies such as processors, types of memory, and networks. CENATE will provide insight into the impact this next generation of high-performing computers will have on DOE’s research community.

Now, CENATE has announced a new director, computer scientist Kevin Barker. Barker has extensive experience developing tools and techniques to model performance of extreme scale hardware and software. He has also developed applications for parallel computing. Barker came to PNNL seven years ago from Los Alamos National Laboratory.

“The goal of CENATE is to evaluate innovative and transformational technologies that will enable future DOE leadership class computing systems to accelerate scientific discovery,” said PNNL’s Laboratory Director Steven Ashby. “We will partner with major computing companies and leading researchers to co-design and test the leading-edge components and systems that will ultimately be used in future supercomputing platforms.”

Those leadership class supercomputers now, such as Oak Ridge National Laboratory’s Titan, are petascale systems that can perform a quadrillion — or a million billion — operations per second and handle petabytes of data. The next step is exascale, or machines that can perform one quintillion — or a billion billion — calculations per second. These exascale systems represent a one-hundred to one-thousand times increase in performance and data handling capability over today’s largest systems.

“With CENATE, its opportunities are also its challenges,” Barker said. “We want to look further out at the evolution of computers, beyond technologies that are already widely available in the marketplace. We want prototypes, systems that aren’t commercially available yet, as well as promising emerging technologies, to evaluate and guide their development.”

In its first two years, CENATE has already worked with advanced systems in close collaborations with IBM, Micron, Data Vortex, and NVIDIA, providing design, measurement, instrumentation, and analysis. In one effort, CENATE’s work with Data Vortex helped shape the third version of Data Vortex’s computer, which has an internal network designed in such a way as to make it congestion-free. Last year, editors at the trade magazine HPCwire named PNNL’s CENATE partnerships the “Best HPC Collaboration Between Government & Industry.”

CENATE is taking the opportunity that bringing in new leadership affords to refine its processes at the same time.

“We want to have more strategic interaction with the research community at large,” said Barker. “Up to now, we’ve procured systems and then invited researchers to come test them. Now we want to solicit input and foster collaborations from the community. ‘Is there something you want to do but can’t because you don’t have the right machine?'”

Barker replaces former PNNL computer scientist Adolfy Hoisie.

Source: PNNL

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