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Lawrence Livermore National Lab has deployed a 170-node HPC cluster from Penguin Computing. Based on AMD EPYC processors and Radeon Instinct GPUs, the new Corona cluster will be used to support the NNSA Advanced Simulation and Computing (ASC) program in an unclassified site dedicated to partnerships with American industry.

In searching for a commercial processor that could handle the demands of HPC and data analytics, Matt Leininger, Deputy for Advanced Technology Projects, LLNL, said several factors influence the choice of CPU including single-core performance, the number of cores, and the memory performance per socket. All these factors drove LLNL to seriously consider the EPYC processor.

The lab’s latest HPC cluster deployment—named Corona—is built with AMD EPYC CPUs and Radeon Instinct MI25 GPUs. 'We are excited to have these high-end products and to apply them to our challenging HPC simulations,' said Leininger.

Simulations requiring 100’s of petaFLOPS (quadrillions of floating-point operations per second) speed are run on the largest supercomputers at LLNL, which are among the fastest in the world. Supporting the larger systems are the Commodity Technology Systems (CTS), what Leininger calls 'everyday workhorses' serving the LLNL user community.

The new Corona cluster will bring new levels of machine learning capabilities to the CTS resources. The integration of HPC simulation and machine learning into a cognitive simulation capability is an active area of research at LLNL.

'Coupling large scale deep learning with our traditional scientific simulation workload will allow us to dramatically increase scientific output and utilise our HPC resources more efficiently,' said LLNL Informatics Group leader and computer scientist Brian Van Essen. 'These new Deep Learning enabled HPC systems are critical as we develop new machine learning algorithms and architectures that are optimised for scientific computing.'

The Corona HPC cluster is powered by AMD EPYC CPUs, peaks at 383 teraFLOPS from 170 nodes, and has room to expand to a total of 300 to 400 nodes. Each node contains a two-socket EPYC 7401 processor, with 256GB RAM and a 1.6TB solid state drive (SSD). Half of the nodes also are equipped with four AMD Radeon Instinct MI25 GPUs.

The computing platform is Penguin Computing’s XO1114GT platform, with nodes connected by Mellanox HDR InfiniBand networking technology.

'We have folks thinking about what they can pull off on this machine that they couldn’t have done before,' Leininger said.

CPU/GPU Powering Machine Learning in HPC

'We’ve been working to understand how to enable HPC simulation using GPUs and also using machine learning in combination with HPC to solve some of our most challenging scientific problems,” Leininger said. “Even as we do more of our computing on GPUs, many of our codes have serial aspects that need really good single core performance. That lines up well with AMD EPYC.'

The EPYC processor-based Corona cluster will help LLNL use machine learning to conduct its simulations more efficiently with an active-learning approach, called Cognitive Simulation, that can be used to optimise solutions with a significant reduction in compute requirements. Leininger explained that multi-physics simulations, which include a significant number of modelling and calculations around hydrodynamic and materials problems important to NNSA, are the lab’s most complicated. These analytic simulations produce a range of parameter space results that are used to construct error bars which depict uncertainty levels that must be understood and reduced.

'We are looking to use some machine learning techniques where the machine would figure out how much of the parameter space we really need to explore or what part of it we need to explore more than others,' Van Essen said.

Using EPYC-powered servers with the Radeon Instinct MI25 for machine learning, LLNL will be able to determine exactly where to explore further in order to detect what component is driving the majority of the error bars and significantly reduce time on task to achieve better science.

This article was originally published on insideHPC.com and appears here as part of a cross-publishing agreement. 

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The American College of Radiology (ACR) Data Science Institute (DSI) has launched its ACR AI-LAB software platform securing GE Healthcare as a key collaborator.

GE Healthcare announced that its Edison AI platform, first started back in November 2018, will integrate with ACR AI-LAB, giving ACR members and other industry professional’s access to certain Edison-powered AI services.

One of the key features of Edison is that data can be traced throughout the development of an algorithm, which GE Healthcare says ‘could radically simplify the ACR community’s ability to create compliant AI applications.’

‘Edison provides clinicians with an integrated digital platform, combining diverse data sets from across modalities, vendors, healthcare networks and life sciences settings,’ Kieran Murphy, president and CEO of GE Healthcare, said in a prepared statement. ‘Algorithms built on Edison by our ACR colleagues will include the latest data processing technologies to enable clinicians to make faster, more informed decisions to improve patient outcomes.’

‘ACR has been collaborating with industry, government and others throughout healthcare to promote a thriving AI ecosystem targeted towards patient and clinician needs,’ Keith Dreyer, PhD, ACR DSI chief science officer, said in the same statement. ‘Standards, clinical pathways, education and tools are all part of harnessing the potential of AI, and ACR AI-LAB is an important step in that journey. ACR welcomes GE Healthcare’s announcement to integrate with ACR AI-LAB, furthering our mutual goals of improved patient outcomes.’

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The latest release of Matereality Version 12 software can be used in conjunction with eLim, a new bolt-on for companies to manage and operate their test labs. eLim is a web-based software where engineers in the enterprise can browse test catalogues and submit clearly defined test orders that can be carried out by the lab technicians without ambiguity.

Combined with features to schedule and track the progress of lab work, eLim leverages all the capability of the Matereality software from test data capture, to data analysis, to report creation and delivery - all on a single platform. eLim can be bolted on to Matereality material data management software to digitalise and streamline the materials and processes side of the enterprise. Diverse teams of technical staff can collaborate seamlessly while using personalised environments and toolsets that have been purposed specifically for their daily tasks.

‘Digitalisation is being applied to all aspects of enterprises today. Enormous benefits in operational efficiency, productivity and accuracy can be achieved by going fully digital, where a complete infrastructure exists to handle all the data that emanates from daily tasks,’ says Hubert Lobo, president of Matereality. The handling of technical information is one of the last frontiers of digitalisation because of the complexity and diversity of the information that must be captured. Matereality's patented software creates a digital bridge from labs to databases to product development, facilitating challenging tasks with proven, field-tested reliability. Systems such as these can be used to operate and improve manufacturing, testing, design and simulation, and product development.

Lab information management systems (LIMS) have been in use for a few decades, but in the absence of a bridge between lab software and enterprise material databases, both systems get underutilised. eLim is built on the practical understanding of running lab operations from DatapointLabs, a world leader in the testing of materials. The Matereality software remains strongly tied to simulation and product development teams because of the ability to convert data to simulation-ready material files and connectivity to all major simulation and design (CAD/CAE) codes.

Applus+ Software, which is developed by Applus+ DatapointLabs Technical Center for Materials, includes the Matereality, eLim, and PicSci brands, representing digitalisation infrastructures for materials & processes, test labs, and R&D labs. All infrastructures utilise a common platform that allows for highly integrated operations on a robust environment within the enterprise or on the cloud.

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ACD/Labs has announced the launch of a new web-based application in support of high throughput (HT) experimentation. Katalyst D2D offers a single interface for high throughput experimentation and parallel synthesis. Katalyst supports the ‘lab of the future’ through the digitisation of laboratory tasks, integration with existing informatics systems, lab automation hardware, analytical instrumentation, and automated execution.

‘Katalyst D2D was designed to improve productivity, provide conclusive scientific insights, and facilitate decision making among increasing regulatory concerns,’ said Andrew Anderson, vice president of Innovation and Informatics Strategy, ACD/Labs. ‘As we celebrate our 25th year in business, we will continue to align our technological expertise with our customers' needs. Katalyst D2D is a testament to our commitment to bring innovation to the forefront.’

Designed to help ensure data integrity in high throughput experimentation (for reaction optimisation, process development, catalyst screening, and scale-up), Katalyst D2D's digital environment eliminates the manual transcription currently necessary between systems, as well as the painstaking process of gathering and interpreting associated analytical data.

By streamlining HT workflows, organizations are able to optimize laboratory efficiency, the analysis of array-based chemistry, and the return on investment in HT robotic equipment.

Katalyst D2D provides A single interface for high throughput experimentation. Integration with third party systems eliminates manual transcription and offers a convenient, consolidated user interface.

The software can also be used for multi-technique, vendor-agnostic high throughput analysis made possible by the ACD/Spectrus Platform. Katalyst D2D integrates with analytical instrumentation to support the execution of experiments, followed by the processing and analysis of HT data. Users can easily compare chromatograms, mass spectra, and other analytical data connected directly with the array for fast, confident decisions.

The software is deployed as a fully web-based client that meets the informatics requirements of the modern laboratory through convenient user access, facile deployment and support for IT.

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CERN has announced a new facility for scientific education and outreach called the Science Gateway. The purpose of the project is to create a hub of scientific education and culture to inspire younger generations. The Science Gateway will include inspirational exhibition spaces, laboratories for hands-on scientific experiments for children and students from primary to high-school level, and a large amphitheatre to host science events for experts and non-experts alike.

With a footprint of 7000 square metres, the Science Gateway building will offer a variety of spaces and activities, including exhibitions explaining the secrets of nature, from the very small (elementary particles) to the very large (the structure and evolution of the universe). The exhibitions will also feature CERN’s accelerators, experiments and computing, how scientists use them in their exploration and how CERN technologies benefit society.

Hands-on experimentation will be a key ingredient in the Science Gateway’s educational programme, allowing visitors to get first-hand experience of what it’s like to be a scientist. The immersive activities available in the Science Gateway will foster critical thinking, evidence-based assessment and use of the scientific method, important tools in all walks of life.

‘The Science Gateway will enable CERN to expand significantly its education and outreach offering for the general public, in particular the younger generations. We will be able to share with everybody the fascination of exploring and learning how matter and the universe work, the advanced technologies we need to develop in order to build our ambitious instruments and their impact on society, and how science can influence our daily life,’ says CERN Director-General Fabiola Gianotti. ‘I am deeply grateful to the donors for their crucial support in the fulfilment of this beautiful project.’

The overall cost of the Science Gateway is estimated at 79 million Swiss Francs (£60,521,226) entirely funded through donations. As of today, 57 million Swiss Francs have been already secured, allowing construction to start on schedule, thanks in particular to a very generous contribution of 45 million Swiss Francs from the FCA Foundation, the charitable arm of Fiat Chrysler Automobiles (FCA), which will support the project as it advances through the construction phases. Other donors include a private foundation in Geneva and Loterie Romande, which distributes its profits to public utility projects in various areas including research, culture and social welfare. CERN is looking for additional donations in order to cover the full cost of the project.

John Elkann, Chairman of FCA and the FCA Foundation, said: ‘The new Science Gateway will satisfy the curiosity of 300,000 visitors every year – including many researchers and students, but also children and their families – providing them with access to tools that will help them understand the world and improve their lives, whatever career paths they eventually choose. At FCA we’re delighted to be supporting this project as part of our social responsibility which also allows us to honour the memory of Sergio Marchionne: in an open and stimulating setting, it will teach us how we can work successfully together, even though we may have diverse cultures and perspectives, to discover the answers to today’s big questions and to those of tomorrow.’

As part of the educational portfolio of the Science Gateway, CERN and FCA Foundation will develop a programme for schools, with the advice of Fondazione Agnelli - Fondazione Agnelli is an independent, non-profit research organisation in the fields of human and social sciences, established in 1966 and named after founder of Fiat, the Senator Giovanni Agnelli. The main goal will be to transmit concepts of science and technology in an engaging way, in order to encourage students to pursue careers in STEM (Science, Technology, Engineering and Mathematics). According to the approach of enquiry-based learning, students will be involved in hands-on educational modules and experiments in physics. Special kits will be delivered to classes, containing all necessary materials and instructions to run modules throughout the school year. As a follow-up, classes will be invited to take part in a contest, with the winners awarded a 2-3 day visit to the Science Gateway and CERN. There will be an initial period of experimentation, with a pilot programme in Italy focusing on junior high schools and involving up to 550,000 students. After the pilot, CERN plans to extend this initiative to all its Member States.

The Science Gateway will be hosted in a new, iconic building, designed by world-renowned architects Renzo Piano Building Workshop, on CERN’s Meyrin site adjacent to another of CERN’s iconic buildings, the Globe of Science and Innovation. The vision for the Science Gateway is inspired by the fragmentation and curiosity already intrinsic to the nature of the CERN site and buildings, so it is made up of multiple elements, embedded in a green forest and interconnected by a bridge spanning the main road leading to Geneva. 

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A project carried out at the National University of Ireland Galway and Eindhoven University of Technology (TU/e) and KU Leuven has been exploring the role of aerodynamic science in Paralympic cycling.

Dr Eoghan Clifford, National University of Ireland Galway, a 4-time world champion and current Paralympic Champion has joined forces with Professor Bert Blocken, Eindhoven University of Technology (TU/e) and KU Leuven, to make use of simulation technology to increase the performance of Paralympic cycling teams.

Surprised by the scarcity of scientific research performed on Paracycling where many fundamental insights are lacking, Dr Clifford and Professor Blocken initiated the first open scientific research project ever in Paralympic cycling.

Dr Eoghan Clifford, College of Engineering and Informatics, NUI Galway, said: ‘This has been one of the most exciting and challenging projects I have worked on. The extensive experimental and computational modelling work was unprecedented for Paralympic cycling and indeed for most sports. The work will fundamentally impact Paralympic cycling and will cause teams and engineers to rethink their approach to aerodynamics. This work also opens the door for world-class Paralympic athletes to have the same expertise and equipment available to them as other professional athletes. At the world championships and Paralympics where tenths of seconds can decide medals this work can unlock that vital time!’

The project team consisting of Dr Paul Manion, Dr Yasin Toparlar, Dr Thomas Andrianne, Dr Magdalena Hajdukiewicz, Dr Eoghan Clifford and Professor Bert Blocken combined computer simulation (CFD) with Ansys software on Irish and Dutch supercomputers with wind tunnel testing in the facilities of Eindhoven University of Technology and the University of Liège. The investigation focused on both tandem cycling and H1-H4 handcycling.

This investigation resulted in four key new findings. Applying these findings in races would yield significant gains in terms of time. This research resulted in four key new findings that are generally not what Paracyclists would expect:

The typical time-trial setup with a time-trial handlebar for the pilot and the stoker does not provide the lowest aerodynamic resistance. The stoker holding the seatpost of the tandem bicycle (frame-clench setup) provides a gain of 8.1 s over a 10 km race.

The most aerodynamic race setup of the tandem cyclists is not the one where pilot and stoker bodies are closest to the horizontal. The pilot being slightly more upright gives a benefit of 6.5 s over 10 km.

The most aerodynamic wheel choice for a H1-H4 handcycle is not disk wheels at the rear, as commonly accepted, but two spoked wheels at the rear, because disk wheels would channel the flow between these wheels and create extra suction (drag) on the cyclist body. Spoked wheels at the rear and a single disk wheel at the front would save 16 s on 10 km.

For downhill handcycling, athletes tend to adopt the so-called 6 o’clock position, with the hands in the lowest position and the arms tucked against the body. The 9 o’clock position with hands farthest upstream has a 4.3% lower drag, which gives a gain of 0.8 s over a 500 m descent.

As a 4-time Paracycling world champion and current Paralympic champion Dr Eoghan Clifford has corroborated these findings with the research team and high performance coaches have tested athletes and used the findings to guide these athletes towards better performances.

Professor Bert Blocken, Eindhoven University of Technology & KU Leuven, said:I am passionate about sports aerodynamics because it really pushes the boundaries of computer simulation and wind tunnel testing. In most topics on aerodynamics, accuracies of 5-10 per cent are considered sufficient. In sports aerodynamics however, tenths or even hundredths of percentages can be decisive. This first extensive open project in Paralympic cycling reveals new insights to obtain such gains in these competitions.’

Thierry Marchal, global industry director sports and healthcare, ANSYS, added: ‘As the engineering simulation leader, ANSYS is keen to assist the sport community improving safety and performance of athletes by adopting a technology traditionally used in the aerospace and automotive industries. Elite sport is an ideal window to illustrate the impact of pervasive simulation across all industries.’

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Intel has recently announced a new range of FPGA’s known as Intel Agilex which are aimed at data-centric applications. The new product family has been designed to solve challenges across embedded, network and datacentre markets.

‘The race to solve data-centric problems requires agile and flexible solutions which can move store and process data efficiently. Intel Agilex FPGAs deliver customised connectivity and acceleration while delivering much needed improvements in performance and power1, 2 for diverse workloads,’ said Dan McNamara, Intel senior vice president, Programmable Solutions Group.

Customers need solutions that can aggregate and process increasing amounts of data traffic to enable transformative applications in the emerging, data-driven industries like edge computing, networking and cloud. Whether it’s through edge analytics for low-latency processing, virtualised network functions to improve performance or datacentre acceleration for greater efficiency, FPGAs are built to deliver customised solutions for applications from the edge to the cloud.

Advances in artificial intelligence (AI) analytics at the edge, network and the cloud are compelling hardware systems to cope with evolving standards, support varying AI workloads, and integrate multiple functions. Intel Agilex FPGAs provide the flexibility and agility required to meet these challenges and deliver gains in performance and power1,2.

The Intel Agilex family combines FPGA fabric built on Intel’s 10nm process with innovative heterogeneous 3D SiP technology. This provides the capability to integrate analog, memory, custom computing, custom I/O, and Intel eASIC device tiles into a single package with the FPGA fabric. Intel delivers a custom logic continuum with reusable IPs through a migration path from FPGA to structured ASIC. One API provides a software-friendly heterogeneous programming environment, enabling software developers to easily access the benefits of FPGA for acceleration. 

The Intel Agilex FPGA provides new capabilities to help accelerate the solutions of tomorrow. These innovations include:

  1. Compute Express Link:  Industry’s first FPGA to support Compute Express Link, a cache and memory coherent interconnect to future Intel Xeon Scalable processors.
  2. 2nd Generation HyperFlex Architecture: Up to 40 percent higher performance, or up to 40 percent lower total power2 compared with Intel Stratix 10 FPGAs.1
  3. DSP Innovation: Only FPGA supporting hardened BFLOAT16 and up to 40 teraflops of digital signal processor (DSP) performance (FP16).3
  4. Peripheral component interconnect express (PCIe) Gen 5: Higher bandwidth compared with PCIe Gen 4.
  5. Transceiver Data Rates: Support up to 112 Gbps data rates.
  6. Advanced memory support: DDR5, HBM, Intel Optane DC persistent memory support.

Further details on Intel Agilex performance, power, and software support numbers:

1 Up to 40 per cent higher performance compared to Intel Stratix 10 FPGAs

Derived from benchmarking an example design suite comparing maximum clock speed (Fmax) achieved in Intel Stratix 10 devices with the Fmax achieved in Intel Agilex devices, using Intel Quartus Prime Software. On average, designs running in the fastest speed grade of Intel Agilex FPGAs achieve a 40 per cent improvement in Fmax compared to the same designs running in the most popular speed grade of Stratix 10 devices (-2 speed grade), tested February 2019.

2 Up to 40 per cent lower total power compared to Intel Stratix 10 FPGAs

Derived from benchmarking an example design suite comparing total power estimates of each design running in Intel Stratix 10 FPGAs compared to the total power consumed by the same design running in Intel Agilex FPGAs. Power estimates of Intel Stratix 10 FPGA designs are obtained from Intel Stratix 10 Early Power Estimator; power estimates for Intel Agilex FPGA designs are obtained using internal Intel analysis and architecture simulation and modeling, tested February 2019.

3 Up to 40 TFLOPs of DSP Performance (FP16 Configuration)

Each Intel Agilex DSP block can perform two FP16 floating-point operations (FLOPs) per clock cycle. Total FLOPs for FP16 configuration is derived by multiplying 2x the maximum number of DSP blocks to be offered in a single Intel Agilex FPGA by the maximum clock frequency that will be specified for that block.

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OnScale, a provider of Cloud-enabled engineering simulation software, has announced $10M in Series A funding led by Intel Capital and Gradient Ventures, Google’s AI-focused venture capital fund. Additional investors include Thornton Tomasetti, Stage 2 Capital, Cultivation Capital, and CampbellKlein.

The company will use the new investment to drive global expansion, respond to increasing demand, and accelerate development of its Computer-Aided Engineering (CAE) software.

OnScale CAE tools are based on proprietary multiphysics solvers that were developed and validated over 30 years by one of the largest engineering consulting firms in the world for DARPA, the US Department of Defense (DOD), and large commercial customers.

The CAE solvers were architected for highly parallel mainframe computers to handle very large engineering simulation problems and are a perfect fit for modern cloud-based, high-performance computing. OnScale was spun out of Thornton Tomasetti in 2017 and is led by Chief Executive Officer Ian Campbell.

‘As technology systems become more complex, next-generation computer-aided engineering software will become integral to design and deployment,’ said Dave Flanagan, vice president and senior managing director at Intel Capital. ‘OnScale’s highly scalable CAE solution leverages the power of the cloud and advanced multiphysics to model highly complex systems, helping customers solve the toughest design challenges.’

‘Leaps in technology require paradigm shifts in engineering, and the combination of world-class multiphysics solvers, AI, and highly scalable cloud-based HPC provide an opportunity for such a paradigm shift in how we create world-changing technologies. That is why we’re excited to welcome OnScale and its team of software experts to the Gradient portfolio.’ said Zach Bratun, partner, Gradient Ventures.

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Siemens has launched an initiative to enable fast ramp-up and reconfiguration of production facilities together with partner companies from the mechanical engineering, automotive, robotics and information technology industries.

Companies can still register and present their proposals on May 23. Prototypes will be tested at the ARENA2036 innovation factory in mid-October. As part of the ‘Fast Ramp-Up Challenge’ competition, production cells from several companies are to be set up within just two days using MindSphere, the open cloud-based operating system for the Internet of Things (IoT) from Siemens.

The fast ramp-up of production facilities is becoming increasingly important across all industries. Companies in the automotive and supply industry are facing major challenges: More and more variants of different automobile models are entering the market with increasingly short product runtimes. The ramp-up and reconfiguration of production lines cause plant shutdowns which represents a further challenge for machine builders and plant manufacturers.

Together with other companies and institutes, Siemens has therefore launched an initiative to quickly ramp-up and reconfigure production lines. The companies already involved include Bär, Balluff, BayernLB, BoldlyGo, Chiron, Dataahead, Deutsche Leasing, Festo, Fraunhofer Institute, Heller, iba, Kampf, Kolbus, KUKA, MAG, maincubes, N+P Industrial Design, Rittal & German Edge Cloud, seioTec, Sick, Spinpartners and Wittenstein. After joint preparatory work, the scheme is now in its consolidation phase until the ‘Pitch Day’ on May 23.

Additional companies can still participate and information is available at mindsphere-openspace.df.de@siemens.com. Prototypes will then be set up at the ARENA2036 innovation factory in Stuttgart in mid-October. The ‘Fast Ramp-Up Challenge’ pilot project has set itself a record-breaking goal: Setting up joint production cells from several companies in just two days.

The open, cloud-based IoT operating system MindSphere developed by Siemens will be used as the enabler. It connects products, plants, systems, and machines in production. The aim of the Fast Ramp-Up Challenge is to develop transparent processes and enable employees. Many companies taking part in the initiative are already associates of MindSphere World e.V.: As members of the forum and users of MindSphere, they are involved in the advancement of the IoT operating system and the joint development of new approaches in the areas of technology and business processes. ARENA2036 is a flexible research facility based at the University of Stuttgart for the hardware-based knowledge factory of the future.

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Siemens has launched an initiative to enable fast ramp-up and reconfiguration of production facilities together with partner companies from the mechanical engineering, automotive, robotics and information technology industries.

Companies can still register and present their proposals on May 23. Prototypes will be tested at the ARENA2036 innovation factory in mid-October. As part of the ‘Fast Ramp-Up Challenge’ competition, production cells from several companies are to be set up within just two days using MindSphere, the open cloud-based operating system for the Internet of Things (IoT) from Siemens.

The fast ramp-up of production facilities is becoming increasingly important across all industries. Companies in the automotive and supply industry are facing major challenges: More and more variants of different automobile models are entering the market with increasingly short product runtimes. The ramp-up and reconfiguration of production lines cause plant shutdowns which represents a further challenge for machine builders and plant manufacturers.

Together with other companies and institutes, Siemens has therefore launched an initiative to quickly ramp-up and reconfigure production lines. The companies already involved include Bär, Balluff, BayernLB, BoldlyGo, Chiron, Dataahead, Deutsche Leasing, Festo, Fraunhofer Institute, Heller, iba, Kampf, Kolbus, KUKA, MAG, maincubes, N+P Industrial Design, Rittal & German Edge Cloud, seioTec, Sick, Spinpartners and Wittenstein. After joint preparatory work, the scheme is now in its consolidation phase until the ‘Pitch Day’ on May 23.

Additional companies can still participate and information is available at mindsphere-openspace.df.de@siemens.com. Prototypes will then be set up at the ARENA2036 innovation factory in Stuttgart in mid-October. The ‘Fast Ramp-Up Challenge’ pilot project has set itself a record-breaking goal: Setting up joint production cells from several companies in just two days.

The open, cloud-based IoT operating system MindSphere developed by Siemens will be used as the enabler. It connects products, plants, systems, and machines in production. The aim of the Fast Ramp-Up Challenge is to develop transparent processes and enable employees. Many companies taking part in the initiative are already associates of MindSphere World e.V.: As members of the forum and users of MindSphere, they are involved in the advancement of the IoT operating system and the joint development of new approaches in the areas of technology and business processes. ARENA2036 is a flexible research facility based at the University of Stuttgart for the hardware-based knowledge factory of the future.

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