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# Supercomputers

15.10.2021
21:21 Supercomputers Mimic Brain Activity, Hunt for COVID Treatments

Data scientists are using a technique known as deep learning, computer algorithms patterned on the brain's signaling networks, to identify combinations of medicines to treat infectious disease.

14.10.2021
23:04 Updated Exascale system for Earth simulations is faster than its predecessor

A new version of the Energy Exascale Earth System Model (E3SM) is two times faster than its earlier version released in 2018.

04.10.2021
22:04 Supercomputers reveal how X chromosomes fold, deactivate

Using supercomputer-driven dynamic modeling based on experimental data, researchers can now probe the process that turns off one X chromosome in female mammal embryos. This new capability is helping biologists understand the role of RNA and the chromosome's structure in the X inactivation process, leading to a deeper understanding of gene expression and opening new pathways to drug treatments for gene-based disorders and diseases.

03:54 PICSAR-QED: a Monte Carlo module to simulate Strong-Field Quantum Electrodynamics in Particle-In-Cell codes for exascale architectures. (arXiv:2110.00256v1 [physics.plasm-ph])

Physical scenarios where the electromagnetic fields are so strong that Quantum ElectroDynamics (QED) plays a substantial role are one of the frontiers of contemporary plasma physics research. Investigating those scenarios requires state-of-the-art Particle-In-Cell (PIC) codes able to run on top high-performance computing machines and, at the same time, able to simulate strong-field QED processes. This work presents the PICSAR-QED library, an open-source, portable implementation of a Monte Carlo module designed to provide modern PIC codes with the capability to simulate such processes, and optimized for high-performance computing. Detailed tests and benchmarks are carried out to validate the physical models in PICSAR-QED, to study how numerical parameters affect such models, and to demonstrate its capability to run on different architectures (CPUs and GPUs). Its integration with WarpX, a state-of-the-art PIC code designed to deliver scalable performance on upcoming exascale

01.10.2021
05:10 Toward Performance-Portable PETSc for GPU-based Exascale Systems. (arXiv:2011.00715v2 [cs.MS] UPDATED)

The Portable Extensible Toolkit for Scientific computation (PETSc) library delivers scalable solvers for nonlinear time-dependent differential and algebraic equations and for numerical optimization.The PETSc design for performance portability addresses fundamental GPU accelerator challenges and stresses flexibility and extensibility by separating the programming model used by the application from that used by the library, and it enables application developers to use their preferred programming model, such as Kokkos, RAJA, SYCL, HIP, CUDA, or OpenCL, on upcoming exascale systems. A blueprint for using GPUs from PETSc-based codes is provided, and case studies emphasize the flexibility and high performance achieved on current GPU-based systems.

24.09.2021
08:24 Preparing for exascale: Argonne’s Aurora supercomputer to drive brain map construction

21.09.2021
18:16 Cell's energy secrets revealed with supercomputers

It takes two to tango, as the saying goes.

11:05 Enabling particle applications for exascale computing platforms. (arXiv:2109.09056v1 [cs.DC])

The Exascale Computing Project (ECP) is invested in co-design to assure that key applications are ready for exascale computing. Within ECP, the Co-design Center for Particle Applications (CoPA) is addressing challenges faced by particle-based applications across four sub-motifs: short-range particle-particle interactions (e.g., those which often dominate molecular dynamics (MD) and smoothed particle hydrodynamics (SPH) methods), long-range particle-particle interactions (e.g., electrostatic MD and gravitational N-body), particle-in-cell (PIC) methods, and linear-scaling electronic structure and quantum molecular dynamics (QMD) algorithms. Our crosscutting co-designed technologies fall into two categories: proxy applications (or apps) and libraries. Proxy apps are vehicles used to evaluate the viability of incorporating various types of algorithms, data structures, and architecture-specific optimizations and the associated trade-offs; examples include ExaMiniMD, CabanaMD, CabanaPIC, and

04:01 Pawsey unwraps first stage of AU$48m Setonix HPE research supercomputer Stage 1 of the unveiling of the HPE Cray EX supercomputer will be used by researchers to 'fine tune' the supercomputer before it's fully operational next year. 14.09.2021 08:39 GPU Algorithms for Efficient Exascale Discretizations. (arXiv:2109.05072v1 [cs.DC]) In this paper we describe the research and development activities in the Center for Efficient Exascale Discretization within the US Exascale Computing Project, targeting state-of-the-art high-order finite-element algorithms for high-order applications on GPU-accelerated platforms. We discuss the GPU developments in several components of the CEED software stack, including the libCEED, MAGMA, MFEM, libParanumal, and Nek projects. We report performance and capability improvements in several CEED-enabled applications on both NVIDIA and AMD GPU systems. 07:35 GPU Algorithms for Efficient Exascale Discretizations. (arXiv:2109.05072v1 [cs.DC]) In this paper we describe the research and development activities in the Center for Efficient Exascale Discretization within the US Exascale Computing Project, targeting state-of-the-art high-order finite-element algorithms for high-order applications on GPU-accelerated platforms. We discuss the GPU developments in several components of the CEED software stack, including the libCEED, MAGMA, MFEM, libParanumal, and Nek projects. We report performance and capability improvements in several CEED-enabled applications on both NVIDIA and AMD GPU systems. 13.09.2021 10:56 Efficient Exascale Discretizations: High-Order Finite Element Methods. (arXiv:2109.04996v1 [cs.DC]) Efficient exploitation of exascale architectures requires rethinking of the numerical algorithms used in many large-scale applications. These architectures favor algorithms that expose ultra fine-grain parallelism and maximize the ratio of floating point operations to energy intensive data movement. One of the few viable approaches to achieve high efficiency in the area of PDE discretizations on unstructured grids is to use matrix-free/partially-assembled high-order finite element methods, since these methods can increase the accuracy and/or lower the computational time due to reduced data motion. In this paper we provide an overview of the research and development activities in the Center for Efficient Exascale Discretizations (CEED), a co-design center in the Exascale Computing Project that is focused on the development of next-generation discretization software and algorithms to enable a wide range of finite element applications to run efficiently on future hardware. CEED is a 10:56 3D Real-Time Supercomputer Monitoring. (arXiv:2109.04532v1 [cs.DC]) Supercomputers are complex systems producing vast quantities of performance data from multiple sources and of varying types. Performance data from each of the thousands of nodes in a supercomputer tracks multiple forms of storage, memory, networks, processors, and accelerators. Optimization of application performance is critical for cost effective usage of a supercomputer and requires efficient methods for effectively viewing performance data. The combination of supercomputing analytics and 3D gaming visualization enables real-time processing and visual data display of massive amounts of information that humans can process quickly with little training. Our system fully utilizes the capabilities of modern 3D gaming environments to create novel representations of computing hardware which intuitively represent the physical attributes of the supercomputer while displaying real-time alerts and component utilization. This system allows operators to quickly assess how the supercomputer is 10:02 Efficient Exascale Discretizations: High-Order Finite Element Methods. (arXiv:2109.04996v1 [cs.DC]) Efficient exploitation of exascale architectures requires rethinking of the numerical algorithms used in many large-scale applications. These architectures favor algorithms that expose ultra fine-grain parallelism and maximize the ratio of floating point operations to energy intensive data movement. One of the few viable approaches to achieve high efficiency in the area of PDE discretizations on unstructured grids is to use matrix-free/partially-assembled high-order finite element methods, since these methods can increase the accuracy and/or lower the computational time due to reduced data motion. In this paper we provide an overview of the research and development activities in the Center for Efficient Exascale Discretizations (CEED), a co-design center in the Exascale Computing Project that is focused on the development of next-generation discretization software and algorithms to enable a wide range of finite element applications to run efficiently on future hardware. CEED is a 02.09.2021 05:54 Plan-based Job Scheduling for Supercomputers with Shared Burst Buffers. (arXiv:2109.00082v1 [cs.DC]) The ever-increasing gap between compute and I/O performance in HPC platforms, together with the development of novel NVMe storage devices (NVRAM), led to the emergence of the burst buffer concept - an intermediate persistent storage layer logically positioned between random-access main memory and a parallel file system. Despite the development of real-world architectures as well as research concepts, resource and job management systems, such as Slurm, provide only marginal support for scheduling jobs with burst buffer requirements, in particular ignoring burst buffers when backfilling. We investigate the impact of burst buffer reservations on the overall efficiency of online job scheduling for common algorithms: First-Come-First-Served (FCFS) and Shortest-Job-First (SJF) EASY-backfilling. We evaluate the algorithms in a detailed simulation with I/O side effects. Our results indicate that the lack of burst buffer reservations in backfilling may significantly deteriorate scheduling. We 01.09.2021 08:35 ExaWorks: Workflows for Exascale. (arXiv:2108.13521v1 [cs.DC]) Exascale computers will offer transformative capabilities to combine data-driven and learning-based approaches with traditional simulation applications to accelerate scientific discovery and insight. These software combinations and integrations, however, are difficult to achieve due to challenges of coordination and deployment of heterogeneous software components on diverse and massive platforms. We present the ExaWorks project, which can address many of these challenges: ExaWorks is leading a co-design process to create a workflow software development Toolkit (SDK) consisting of a wide range of workflow management tools that can be composed and interoperate through common interfaces. We describe the initial set of tools and interfaces supported by the SDK, efforts to make them easier to apply to complex science challenges, and examples of their application to exemplar cases. Furthermore, we discuss how our project is working with the workflows community, large computing facilities as 07:30 Bridging the Gap between Deep Learning and Frustrated Quantum Spin System for Extreme-scale Simulations on New Generation of Sunway Supercomputer. (arXiv:2108.13830v1 [cond-mat.str-el]) Efficient numerical methods are promising tools for delivering unique insights into the fascinating properties of physics, such as the highly frustrated quantum many-body systems. However, the computational complexity of obtaining the wave functions for accurately describing the quantum states increases exponentially with respect to particle number. Here we present a novel convolutional neural network (CNN) for simulating the two-dimensional highly frustrated spin-$1/2J_1-J_2$Heisenberg model, meanwhile the simulation is performed at an extreme scale system with low cost and high scalability. By ingenious employment of transfer learning and CNN's translational invariance, we successfully investigate the quantum system with the lattice size up to$24\times24$, within 30 million cores of the new generation of Sunway supercomputer. The final achievement demonstrates the effectiveness of CNN-based representation of quantum-state and brings the state-of-the-art record up to a brand-new 31.08.2021 12:49 IBM's fastest supercomputer will be used to find better ways to produce green electricity GE has revealed more information about two research projects that were awarded compute time on the Summit supercomputer. 30.08.2021 06:58 JUWELS Booster -- A Supercomputer for Large-Scale AI Research. (arXiv:2108.11976v1 [cs.DC]) In this article, we present JUWELS Booster, a recently commissioned high-performance computing system at the J\"ulich Supercomputing Center. With its system architecture, most importantly its large number of powerful Graphics Processing Units (GPUs) and its fast interconnect via InfiniBand, it is an ideal machine for large-scale Artificial Intelligence (AI) research and applications. We detail its system architecture, parallel, distributed model training, and benchmarks indicating its outstanding performance. We exemplify its potential for research application by presenting large-scale AI research highlights from various scientific fields that require such a facility. 25.08.2021 14:09 DOE's Argonne Lab to deploy new GPU-based supercomputer Polaris Accelerated by 2,240 Nvidia A100 Tensor Core GPUs, the Polaris system will be able to achieve almost 1.4 exaflops of theoretical AI performance. 17.08.2021 20:54 Supercomputer calculates pi to a record-breaking 68.2 trillion digits Researchers are set to break the world record for the most precise value of pi, after using an advanced computer to calculate the famous constant to 68.2 trillion decimal places. 20:17 Cracking a mystery of massive black holes and quasars with supercomputer simulations Researchers address some of the questions surrounding these massive and enigmatic features of the universe by using new, high-powered simulations. 15:53 Cracking a mystery of massive black holes and quasars with supercomputer simulations At the center of galaxies, like our own Milky Way, lie massive black holes surrounded by spinning gas. Some shine brightly, with a continuous supply of fuel, while others go dormant for millions of years, only to reawaken with a serendipitous influx of gas. It remains largely a mystery how gas flows across the universe to feed these massive black holes. 16.08.2021 09:34 Scalable3-BO: Big Data meets HPC - A scalable asynchronous parallel high-dimensional Bayesian optimization framework on supercomputers. (arXiv:2108.05969v1 [cs.DC]) Bayesian optimization (BO) is a flexible and powerful framework that is suitable for computationally expensive simulation-based applications and guarantees statistical convergence to the global optimum. While remaining as one of the most popular optimization methods, its capability is hindered by the size of data, the dimensionality of the considered problem, and the nature of sequential optimization. These scalability issues are intertwined with each other and must be tackled simultaneously. In this work, we propose the Scalable$^3$-BO framework, which employs sparse GP as the underlying surrogate model to scope with Big Data and is equipped with a random embedding to efficiently optimize high-dimensional problems with low effective dimensionality. The Scalable$^3$-BO framework is further leveraged with asynchronous parallelization feature, which fully exploits the computational resource on HPC within a computational budget. As a result, the proposed Scalable$^3$-BO framework is 08:27 Scalable3-BO: Big Data meets HPC - A scalable asynchronous parallel high-dimensional Bayesian optimization framework on supercomputers. (arXiv:2108.05969v1 [cs.DC]) Bayesian optimization (BO) is a flexible and powerful framework that is suitable for computationally expensive simulation-based applications and guarantees statistical convergence to the global optimum. While remaining as one of the most popular optimization methods, its capability is hindered by the size of data, the dimensionality of the considered problem, and the nature of sequential optimization. These scalability issues are intertwined with each other and must be tackled simultaneously. In this work, we propose the Scalable$^3$-BO framework, which employs sparse GP as the underlying surrogate model to scope with Big Data and is equipped with a random embedding to efficiently optimize high-dimensional problems with low effective dimensionality. The Scalable$^3$-BO framework is further leveraged with asynchronous parallelization feature, which fully exploits the computational resource on HPC within a computational budget. As a result, the proposed Scalable$^3$-BO framework is 08:27 Scalable3-BO: Big Data meets HPC - A scalable asynchronous parallel high-dimensional Bayesian optimization framework on supercomputers. (arXiv:2108.05969v1 [cs.DC]) Bayesian optimization (BO) is a flexible and powerful framework that is suitable for computationally expensive simulation-based applications and guarantees statistical convergence to the global optimum. While remaining as one of the most popular optimization methods, its capability is hindered by the size of data, the dimensionality of the considered problem, and the nature of sequential optimization. These scalability issues are intertwined with each other and must be tackled simultaneously. In this work, we propose the Scalable$^3$-BO framework, which employs sparse GP as the underlying surrogate model to scope with Big Data and is equipped with a random embedding to efficiently optimize high-dimensional problems with low effective dimensionality. The Scalable$^3$-BO framework is further leveraged with asynchronous parallelization feature, which fully exploits the computational resource on HPC within a computational budget. As a result, the proposed Scalable$^3$-BO framework is 10.08.2021 04:37 Preparing for Performance Analysis at Exascale. (arXiv:2108.04002v1 [cs.DC]) Performance tools for forthcoming heterogeneous exascale platforms must address two principal challenges when analyzing execution measurements. First, measurement of extreme-scale executions generates large volumes of performance data. Second, performance metrics for heterogeneous applications are significantly sparse across code regions. To address these challenges, we developed a novel "streaming aggregation" approach to post-mortem analysis that employs both shared and distributed memory parallelism to aggregate sparse performance measurements from every rank, thread and GPU stream of a large-scale application execution. Analysis results are stored in a pair of sparse formats designed for efficient access to related data elements, supporting responsive interactive presentation and scalable data analytics. Empirical analysis shows that our implementation of this approach in HPCToolkit effectively processes measurement data from thousands of threads using a fraction of the compute 02.08.2021 13:22 Supercomputers are becoming another cloud service. Here's what it means Designing for the usual cloud workloads isn't the same as designing for high performance computing: Azure is trying to achieve both. 30.07.2021 11:48 Supercomputer-Generated Models Provide Better Understanding of Esophageal Disorders Gastroesophageal reflux disease, more commonly known as GERD, impacts around 20 percent of U.S. citizens, according to the 22.07.2021 07:58 Preparing for exascale: Argonne’s Aurora to accelerate discoveries in particle physics at CERN Argonne researchers will use the lab’s upcoming exascale supercomputer to aid in the search for new physics discoveries. 16.07.2021 08:55 Improving I/O Performance for Exascale Applications through Online Data Layout Reorganization. (arXiv:2107.07108v1 [cs.DC]) The applications being developed within the U.S. Exascale Computing Project (ECP) to run on imminent Exascale computers will generate scientific results with unprecedented fidelity and record turn-around time. Many of these codes are based on particle-mesh methods and use advanced algorithms, especially dynamic load-balancing and mesh-refinement, to achieve high performance on Exascale machines. Yet, as such algorithms improve parallel application efficiency, they raise new challenges for I/O logic due to their irregular and dynamic data distributions. Thus, while the enormous data rates of Exascale simulations already challenge existing file system write strategies, the need for efficient read and processing of generated data introduces additional constraints on the data layout strategies that can be used when writing data to secondary storage. We review these I/O challenges and introduce two online data layout reorganization approaches for achieving good tradeoffs between read and 14.07.2021 02:25 Supercomputer predicts cell-membrane permeability of cyclic peptides Scientists have developed a computational method based on large-scale molecular dynamics simulations to predict the cell-membrane permeability of cyclic peptides using a supercomputer. Their protocol has exhibited promising accuracy and may become a useful tool for the design and discovery of cyclic peptide drugs, which could help us reach new therapeutic targets inside cells beyond the capabilities of conventional small-molecule drugs or antibody-based drugs. 13.07.2021 15:59 TSUBAME supercomputer predicts cell-membrane permeability of cyclic peptides Scientists at Tokyo Institute of Technology have developed a computational method based on large-scale molecular dynamics simulations to predict the cell-membrane permeability of cyclic peptides using a supercomputer. Their protocol has exhibited promising accuracy and may become a useful tool for the design and discovery of cyclic peptide drugs, which could help us reach new therapeutic targets inside cells beyond the capabilities of conventional small-molecule drugs or antibody-based drugs. 07.07.2021 12:14 This powerful new supercomputer is taking on some of healthcare's hardest problems Cambridge-1 is the UK's fastest supercomputer, and it is dedicated to advancing healthcare research. 28.06.2021 19:20 A new supercomputer has joined the top five most powerful devices around the world The latest iteration of the Top500 puts the Perlmutter supercomputer in the spotlight. 10:20 New University of Edinburgh supercomputer powered by Nvidia Nvidia announces powering a new system for a Scottish university and a handful of updates to its HPC portfolio as part of MWC 2021. 24.06.2021 05:13 BFTrainer: Low-Cost Training of Neural Networks on Unfillable Supercomputer Nodes. (arXiv:2106.12091v1 [cs.DC]) Supercomputer FCFS-based scheduling policies result in many transient idle nodes, a phenomenon that is only partially alleviated by backfill scheduling methods that promote small jobs to run before large jobs. Here we describe how to realize a novel use for these otherwise wasted resources, namely, deep neural network (DNN) training. This important workload is easily organized as many small fragments that can be configured dynamically to fit essentially any node*time hole in a supercomputer's schedule. We describe how the task of rescaling suitable DNN training tasks to fit dynamically changing holes can be formulated as a deterministic mixed integer linear programming (MILP)-based resource allocation algorithm, and show that this MILP problem can be solved efficiently at run time. We show further how this MILP problem can be adapted to optimize for administrator- or user-defined metrics. We validate our method with supercomputer scheduler logs and different DNN training scenarios, and 23.06.2021 17:37 Machine learning for solar energy is a supercomputer killer Supercomputers could find themselves out of a job thanks to a suite of new machine learning models that produce rapid, accurate results using a normal laptop. 14:42 Tesla Built a Supercomputer to Develop Camera-Only Self-Driving Tech Tesla is talking about what it sees as the next leap in autonomous driving that could do away with lidar and radar, leaving self-driving cars to get around with regular optical cameras only. The post Tesla Built a Supercomputer to Develop Camera-Only Self-Driving Tech appeared first on ExtremeTech. 07:52 High Performance Optimization at the Door of the Exascale. (arXiv:2106.11819v1 [cs.DC]) quest for processing speed potential. In fact, we always get a fraction of the technically available computing power (so-called {\em theoretical peak}), and the gap is likely to go hand-to-hand with the hardware complexity of the target system. Among the key aspects of this complexity, we have: the {\em heterogeneity} of the computing units, the {\em memory hierarchy and partitioning} including the non-uniform memory access (NUMA) configuration, and the {\em interconnect} for data exchanges among the computing nodes. Scientific investigations and cutting-edge technical activities should ideally scale-up with respect to sustained performance. The special case of quantitative approaches for solving (large-scale) problems deserves a special focus. Indeed, most of common real-life problems, even when considering the artificial intelligence paradigm, rely on optimization techniques for the main kernels of algorithmic solutions. Mathematical programming and pure combinatorial methods are not 07:52 Real-Time XFEL Data Analysis at SLAC and NERSC: a Trial Run of Nascent Exascale Experimental Data Analysis. (arXiv:2106.11469v1 [cs.DC]) X-ray scattering experiments using Free Electron Lasers (XFELs) are a powerful tool to determine the molecular structure and function of unknown samples (such as COVID-19 viral proteins). XFEL experiments are a challenge to computing in two ways: i) due to the high cost of running XFELs, a fast turnaround time from data acquisition to data analysis is essential to make informed decisions on experimental protocols; ii) data collection rates are growing exponentially, requiring new scalable algorithms. Here we report our experiences analyzing data from two experiments at the Linac Coherent Light Source (LCLS) during September 2020. Raw data were analyzed on NERSC's Cori XC40 system, using the Superfacility paradigm: our workflow automatically moves raw data between LCLS and NERSC, where it is analyzed using the software package CCTBX. We achieved real time data analysis with a turnaround time from data acquisition to full molecular reconstruction in as little as 10 min -- sufficient time 07:41 Real-Time XFEL Data Analysis at SLAC and NERSC: a Trial Run of Nascent Exascale Experimental Data Analysis. (arXiv:2106.11469v1 [cs.DC]) X-ray scattering experiments using Free Electron Lasers (XFELs) are a powerful tool to determine the molecular structure and function of unknown samples (such as COVID-19 viral proteins). XFEL experiments are a challenge to computing in two ways: i) due to the high cost of running XFELs, a fast turnaround time from data acquisition to data analysis is essential to make informed decisions on experimental protocols; ii) data collection rates are growing exponentially, requiring new scalable algorithms. Here we report our experiences analyzing data from two experiments at the Linac Coherent Light Source (LCLS) during September 2020. Raw data were analyzed on NERSC's Cori XC40 system, using the Superfacility paradigm: our workflow automatically moves raw data between LCLS and NERSC, where it is analyzed using the software package CCTBX. We achieved real time data analysis with a turnaround time from data acquisition to full molecular reconstruction in as little as 10 min -- sufficient time 22.06.2021 10:31 Three-body problem -- from Newton to supercomputer plus machine learning. (arXiv:2106.11010v1 [cs.OH]) The famous three-body problem can be traced back to Newton in 1687, but quite few families of periodic orbits were found in 300 years thereafter. As proved by Poincar\`{e}, the first integral does not exist for three-body systems, which implies that numerical approach had to be used in general. In this paper, we propose an effective approach and roadmap to numerically gain planar periodic orbits of three-body systems with arbitrary masses by means of machine learning based on an artificial neural network (ANN) model. Given any a known periodic orbit as a starting point, this approach can provide more and more periodic orbits (of the same family name) with variable masses, while the mass domain having periodic orbits becomes larger and larger, and the ANN model becomes wiser and wiser. Finally we have an ANN model trained by means of all obtained periodic orbits of the same family, which provides a convenient way to give accurate enough predictions of periodic orbits with arbitrary 21.06.2021 20:40 Oil giant Petrobras launches Latin America's largest supercomputer The new equipment is intended to support the Brazilian company in its data processing requirements and to reduce geological and operational risks. 27.05.2021 20:59 US Energy Department launches the Perlmutter AI supercomputer The next-generation supercomputer that will deliver nearly four exaflops of AI performance. 17.05.2021 09:00 Toward Real-time Analysis of Experimental Science Workloads on Geographically Distributed Supercomputers. (arXiv:2105.06571v1 [cs.DC]) Massive upgrades to science infrastructure are driving data velocities upwards while stimulating adoption of increasingly data-intensive analytics. While next-generation exascale supercomputers promise strong support for I/O-intensive workflows, HPC remains largely untapped by live experiments, because data transfers and disparate batch-queueing policies are prohibitive when faced with scarce instrument time. To bridge this divide, we introduce Balsam: a distributed orchestration platform enabling workflows at the edge to securely and efficiently trigger analytics tasks across a user-managed federation of HPC execution sites. We describe the architecture of the Balsam service, which provides a workflow management API, and distributed sites that provision resources and schedule scalable, fault-tolerant execution. We demonstrate Balsam in efficiently scaling real-time analytics from two DOE light sources simultaneously onto three supercomputers (Theta, Summit, and Cori), while 14.05.2021 15:22 Supercomputer simulations unlock an old space weather puzzle Scientists have long questioned why the bursts of hot gas from the sun do not cool down as fast as expected, and have now used a supercomputer to find out. 28.04.2021 09:20 Singapore to build second national supercomputer with more on roadmap Built to support the local research community, the new national supercomputer will run on warm water-cooled system designed for tropical climates and provide up to 10 petaflops of raw compute capacity when it is operational in early-2022. 26.04.2021 17:09 Advancing AI With a Supercomputer: A Blueprint for an Optoelectronic “Brain” Building a computer that can support artificial intelligence at the scale and complexity of the human brain will be a colossal engineering effort. Now researchers at the National Institute of Standards and Technology have outlined how they think we’ll get there. How, when, and whether we’ll ever create machines that can match our cognitive capabilities […] 23.04.2021 17:08 Met Office and Microsoft to build weather-forecasting supercomputer The Met Office and Microsoft are to build a world-leading supercomputer capable of providing more accurate warnings of severe weather as part of a multimillion-pound agreement. The weather today is... 22.04.2021 16:07 This billion-dollar supercomputer will be used to create super-accurate weather forecasts The Met Office is investing in a new supercomputer to improve the precision of weather and climate models. 06:43 Quantum ESPRESSO towards the exascale. (arXiv:2104.10502v1 [physics.comp-ph]) Quantum ESPRESSO is an open-source distribution of computer codes for quantum-mechanical materials modeling, based on density-functional theory, pseudopotentials, and plane waves, and renowned for its performance on a wide range of hardware architectures, from laptops to massively parallel computers, as well as for the breadth of its applications. In this paper we present a motivation and brief review of the ongoing effort to port Quantum ESPRESSO onto heterogeneous architectures based on hardware accelerators, which will overcome the energy constraints that are currently hindering the way towards exascale computing. 21.04.2021 09:19 Exascale Landau collision operator in the Cuda programming model applied to thermal quench plasmas. (arXiv:2104.10000v1 [physics.plasm-ph]) The Landau form of the Fokker-Planck equation is the gold standard for plasmas dominated by small angle collisions, however its$\Order{N^2}\$ work complexity has limited its practicality. This paper extends previous work on a fully conservative finite element method for this Landau collision operator with adaptive mesh refinement, optimized for vector machines, by porting the algorithm to the Cuda programming model with implementations in Cuda and Kokkos, and by reporting results within a Vlasov-Maxwell-Landau model of a plasma thermal quench. With new optimizations of the Landau kernel and ports of this kernel, the sparse matrix assembly and algebraic solver to Cuda, the cost of a well resolved Landau collision time advance is shown to be practical for kinetic plasma applications. This fully implicit Landau time integrator and the plasma quench model is available in the PETSc (Portable, Extensible, Toolkit for Scientific computing) numerical library.

18.04.2021
23:25 Supercomputer simulations illuminate the behavior of dominant G form of SARS-CoV-2

Large-scale supercomputer simulations at the atomic level show that the dominant G form variant of the COVID-19-causing virus is more infectious partly because of its greater ability to readily bind to its target host receptor in the body, compared to other variants.

15.04.2021
01:11 Dell, Nvidia power new "cloud-native supercomputer" in the UK

The expanded system at the University of Cambridge will deliver multi-tenant high performance computing for research spanning astrophysics, nuclear fusion power generation and clinical medicine applications.

09.04.2021
12:41 US adds Chinese supercomputer centers to export blacklist

The United States on Thursday restricted trade with top Chinese supercomputing centers, saying that Beijing's growing efforts in the field could have military uses that pose dangers. The seven centers or entities were put on the US government's entity list, which means they require special permission for exports and imports from the United States. "Supercomputing capabilities are vital for the development of many -- perhaps almost all -- modern weapons and national security systems, such as nuclear weapons and hypersonic weapons," Commerce Secretary Gina Raimondo said in a statement. She said the commerce department would "use the full extent of its authorities to prevent China from leveraging US technologies to support these destabilizing military modernization efforts." The centers hit with the restrictions include the National Supercomputing Center in the eastern city of Wuxi, home to the Sunway TaihuLight, which was considered the world's fastest when it was launched in 2016 --

08:42 US blacklists seven Chinese supercomputer groups

President Biden's actions continue US moves to make it harder for China to obtain its technology.

30.03.2021
11:05 MT-lib: A Topology-aware Message Transfer Library for Graph500 on Supercomputers. (arXiv:2103.15024v1 [cs.DC])

We present MT-lib, an efficient message transfer library for messages gather and scatter in benchmarks like Graph500 for Supercomputers. Our library includes MST version as well as new-MST version. The MT-lib is deliberately kept light-weight, efficient and friendly interfaces for massive graph traverse. MST provides (1) a novel non-blocking communication scheme with sending and receiving messages asynchronously to overlap calculation and communication;(2) merging messages according to the target process for reducing communication overhead;(3) a new communication mode of gathering intra-group messages before forwarding between groups for reducing communication traffic. In MT-lib, there are (1) one-sided message; (2) two-sided messages; and (3) two-sided messages with buffer, in which dynamic buffer expansion is built for messages delivery. We experimented with MST and then testing Graph500 with MST on Tianhe supercomputers. Experimental results show high communication efficiency and

29.03.2021
15:12 Europe Plans 20,000 GPU Supercomputer to Create ‘Digital Twin’ of Earth

GPU prices are not moving in the right direction. The plan to create a digital twin of Earth might end up delayed due to the relative lack of available GPUs, but this isn't going to be an overnight project.  The post Europe Plans 20,000 GPU Supercomputer to Create ‘Digital Twin’ of Earth appeared first on ExtremeTech.

27.03.2021
11:23 Preparing for exascale: Aurora supercomputer to help scientists visualize the spread of cancer

Scientists are preparing a cancer modeling study to run on Argonne’s upcoming Aurora supercomputer before it goes online

20.03.2021
00:52 Chemists use supercomputers to understand solvents

To understand the fundamental properties of an industrial solvent, chemists with the University of Cincinnati turned to a supercomputer.

18.03.2021
15:24 This powerful supercomputer was built in just 20 weeks, with a bit of help from a tiny robot

Nvidia announced that it would build Cambridge-1 only 20 weeks ago. Now the supercomputer is almost up and running, despite a global health crisis.

17.03.2021
22:40 SUPERCOMPUTERS ADVANCE LONGER-LASTING, FASTER-CHARGING BATTERIES

In an effort to curb the rise in overall carbon vehicle emissions, the state of California recently announced

22:17 Supercomputers Help Accelerate Alzheimer’s Research

Since 2009, Daniel Tward and his collaborators have analyzed more than 47,000 images of human brains via MRI Cloud—a

09.03.2021
16:29 The world's most powerful supercomputer is now up and running

Japan's Fugaku supercomputer is likely to become researchers' new favorite toy.

05.03.2021
16:03 One mask is enough, Japanese supercomputer model shows

04.03.2021
11:13 VELOC: VEry Low Overhead Checkpointing in the Age of Exascale. (arXiv:2103.02131v1 [cs.DC])

Checkpointing large amounts of related data concurrently to stable storage is a common I/O pattern of many HPC applications. However, such a pattern frequently leads to I/O bottlenecks that lead to poor scalability and performance. As modern HPC infrastructures continue to evolve, there is a growing gap between compute capacity vs. I/O capabilities. Furthermore, the storage hierarchy is becoming increasingly heterogeneous: in addition to parallel file systems, it comprises burst buffers, key-value stores, deep memory hierarchies at node level, etc. In this context, state of art is insufficient to deal with the diversity of vendor APIs, performance and persistency characteristics. This extended abstract presents an overview of VeloC (Very Low Overhead Checkpointing System), a checkpointing runtime specifically design to address these challenges for the next generation Exascale HPC applications and systems. VeloC offers a simple API at user level, while employing an advanced multi-level

03.03.2021
13:34 Comet supercomputer reveals the mechanical process of cancer growth

According to the World Health Organization, one in six worldwide deaths have been attributed to cancer; however, these fatalities were not due to initial malignant tumors-;the deaths were caused by the spread of cancer cells to surrounding tissues and subsequent tumor growth.

09:04 Comet supercomputer helps understand the mechanical process of cancer cell growth

According to the World Health Organization, one in six worldwide deaths have been attributed to cancer; however, these fatalities were not due to initial malignant tumors-;the deaths were caused by the spread of cancer cells to surrounding tissues and subsequent tumor growth.

25.02.2021
16:28 Scientists use supercomputers to study reliable fusion reactor design, operation

Nuclear fusion, the same kind of energy that fuels stars, could one day power our world with abundant, safe, and carbon-free energy. Aided by supercomputers Summit at the US Department of Energy's (DOE's) Oak Ridge National Laboratory (ORNL) and Theta at DOE's Argonne National Laboratory (ANL), a team of scientists strives toward making fusion energy a reality.

24.02.2021
17:05 Fujitsu Leverages World’s Fastest Supercomputer ‘Fugaku’ and AI to Deliver Real-Time Tsunami Prediction in Joint Project

The International Research Institute of Disaster Science at Tohoku University, the Earthquake Research Institute at the University of

18.02.2021
05:33 Dell Technologies powering Kyoto University's new Yukawa-21 supercomputer

The new system will be used by the university's Yukawa Institute for Theoretical Physics to progress research in the field of theoretical physics.

17.02.2021
15:18 AI Model Harnesses the Power of World's Fastest Supercomputer to Predict Tsunami Flooding

A new AI model that harnesses the power of the world's fastest supercomputer, Fugaku, can rapidly predict tsunami flooding in coastal areas before the tsunami reaches land. The development of the...

16.02.2021
22:24 Supercomputer turns back cosmic clock

Astronomers have tested a method for reconstructing the state of the early universe by applying it to 4000 simulated universes using the ATERUI II supercomputer at the National Astronomical Observatory of Japan (NAOJ). They found that together with new observations, the method can set better constraints on inflation, one of the most enigmatic events in the history of the universe. The method can shorten the observation time required to distinguish between various inflation theories.

20:49 Supercomputer turns back cosmic clock

Astronomers have tested a method for reconstructing the state of the early Universe by applying it to 4000 simulated universes using the ATERUI II supercomputer. They found that together with new observations the method can set better constraints on inflation, one of the most enigmatic events in the history of the Universe. The method can shorten the observation time required to distinguish between various inflation theories.

20:28 Fujitsu leverages world's fastest supercomputer and AI to predict tsunami flooding

A new AI model that harnesses the power of the world's fastest supercomputer, Fugaku, can rapidly predict tsunami flooding in coastal areas before the tsunami reaches land.

08.02.2021
09:52 Cache Blocking Technique to Large Scale Quantum Computing Simulation on Supercomputers. (arXiv:2102.02957v1 [quant-ph])

Classical computers require large memory resources and computational power to simulate quantum circuits with a large number of qubits. Even supercomputers that can store huge amounts of data face a scalability issue in regard to parallel quantum computing simulations because of the latency of data movements between distributed memory spaces. Here, we apply a cache blocking technique by inserting swap gates in quantum circuits to decrease data movements. We implemented this technique in the open source simulation framework Qiskit Aer. We evaluated our simulator on GPU clusters and observed good scalability.

05.02.2021
17:09 Cell Bones Mystery Solved with Supercomputers

Our cells are filled with ‘bones,’ in a sense. Thin, flexible protein strands called actin filaments help support

03.02.2021
14:10 Who needs a supercomputer? Your desktop PC and a GPU might be enough to solve some of the largest problems

A new method significantly reduces the amount of memory needed for brain simulations, freeing some AI models from the need for a supercomputer.

02.02.2021
14:03 This Linux malware is hijacking supercomputers across the globe

Kobalos’ codebase is tiny, but its impact is not.

28.01.2021
04:22 Cell 'bones' mystery solved with supercomputers

Supercomputer simulations allocated by XSEDE on TACC's Stampede2 have helped solve the mystery of how actin filaments polymerize. Researchers employed all-atom molecular dynamics to show structural basis for polymerization kinetics at polarized ends of actin filaments. This fundamental research could be applied to treatments to stop cancer spread, develop self-healing materials, and more.

27.01.2021
00:34 Cell 'bones' mystery solved with supercomputers

Our cells are filled with 'bones,' in a sense. Thin, flexible protein strands called actin filaments help support and move around the bulk of the cells of eukaryotes, which includes all plants and animals. Always on the go, actin filaments constantly grow, shrink, bind with other things, and branch off when cells move.

26.01.2021
17:28 Supercomputers aid scientists studying the smallest particles in the universe

Since the 1930s, scientists have been using particle accelerators to gain insights into the structure of matter and the laws of physics that govern our world. These accelerators are some of the most powerful experimental tools available, propelling particles to nearly the speed of light and then colliding them to allow physicists to study the resulting interactions and particles that form.

09:16 The Artificial Intelligence Ecosystem: Ethics to Exascale

PNNL researchers contribute to global conversations about the future of neural information processing Artificial intelligence, or AI, has

09:16 Supercomputers aid scientists studying the smallest particles in the universe

Since the 1930s, scientists have been using particle accelerators to gain insights into the structure of matter and

20.01.2021
12:40 How to train a robot (using AI and supercomputers)

Computer scientists use deep learning systems to generate synthetic objects for robot training.

08:13 Saudi Aramco And STC Develops A SuperComputer Dammam 7

Research Snipers Saudi Aramco and STC on Tuesday announced the unveiling of the supercomputer, one of the... The post Saudi Aramco And STC Develops A SuperComputer Dammam 7 appeared first on Research Snipers.

04:50 How to train a robot (using AI and supercomputers)

Computer scientists developed a deep learning method to create realistic objects for virtual environments that can be used to train robots. The researchers used TACC's Maverick2 supercomputer to train the generative adversarial network. The network is the first that can produce colored point clouds with fine details at multiple resolutions.

13.01.2021
23:11 Supercomputer Models Describe Chloride’s Role in Corrosion

Researchers have been studying chloride’s corrosive effects on various materials for decades. Now thanks to high-performance computers at

07.01.2021
17:04 Supercomputer models describe chloride's role in corrosion

Researchers have been studying chloride's corrosive effects on various materials for decades. Now thanks to high-performance computers at the San Diego Supercomputer Center (SDSC) at UC San Diego and the Texas Advanced Computing Center (TACC), detailed models have been simulated to provide new insight on how chloride leads to corrosion on structrual metals, resulting in economic and environmental impacts.

05.01.2021
16:11 Supercomputers simulate new pathways for potential RNA virus treatment

University of New Hampshire (UNH) researchers recently used Comet at the San Diego Supercomputer Center at UC San Diego and Stampede2 at the Texas Advanced Computing Center to identify new inhibitor binding/unbinding pathways in an RNA-based virus. The findings could be beneficial in understanding how these inhibitors react and potentially help develop a new generation of drugs to target viruses with high death rates, such as HIV-1, Zika, Ebola, and SARS-CoV2, the virus that causes COVID-19.

25.12.2020
13:35 Supercomputers Simulate New Pathways for Potential RNA Virus Treatment

University of New Hampshire (UNH) researchers recently used Comet at the San Diego Supercomputer Center at UC San Diego and Stampede2 at

18.12.2020
06:16 Solving large permutation flow-shop scheduling problems on GPU-accelerated supercomputers. (arXiv:2012.09511v1 [cs.DC])

Makespan minimization in permutation flow-shop scheduling is a well-known hard combinatorial optimization problem. Among the 120 standard benchmark instances proposed by E. Taillard in 1993, 23 have remained unsolved for almost three decades. In this paper, we present our attempts to solve these instances to optimality using parallel Branch-and-Bound tree search on the GPU-accelerated Jean Zay supercomputer. We report the exact solution of 11 previously unsolved problem instances and improved upper bounds for 8 instances. The solution of these problems requires both algorithmic improvements and leveraging the computing power of peta-scale high-performance computing platforms. The challenge consists in efficiently performing parallel depth-first traversal of a highly irregular, fine-grained search tree on distributed systems composed of hundreds of massively parallel accelerator devices and multi-core processors. We present and discuss the design and implementation of our

04:03 Supercomputer simulations lead to an important viral inhibitor discovery

University of New Hampshire researchers recently used Comet at the San Diego Supercomputer Center at UC San Diego and Stampede2 at the Texas Advanced Computing Center to identify new inhibitor binding/unbinding pathways in an RNA-based virus.

07.12.2020
02:41 Supercomputer simulations could unlock mystery of Moon's formation

Astronomers have taken a step towards understanding how the Moon might have formed out of a giant collision between the early Earth and another massive object 4.5 billion years ago.

06.12.2020
17:43 "Quantum Supremacy" - China's New Supercomputer "10 Billion Times Faster" Than Google's

America is locked in a quantum computer race with China. The latest developments from Chinese scientists show a "significant computing breakthrough, achieving quantum computational advantage," according to state media Xinhua News Agency. Thursday, China's top quantum research group published a new research paper in the journal Science, titled "Quantum computational advantage using photons," outlines how a quantum computer prototype detected up to 76 photons through Gaussian boson sampling (GBS), a standard simulation algorithm, Xinhua said, adding that its ability to process complex problems is exponentially faster than most supercomputers.

16:25 Chinese scientists 'build quantum computer able to perform nearly 100 trillion times faster than the world's most advanced supercomputer'

Chinese scientists claim to have built a quantum computer which is 100trillion times faster than the world's most advanced supercomputer - Japan's Fugaku.

04.12.2020
15:47 Supercomputer simulation shows how the Moon may have formed through the collision of Earth with Mars-sized planet Theia 4.5 billion years ago

New supercomputer simulations show how the Moon may have formed through the collision of Earth with a Mars-sized planet called Theia about 4.5 billion years ago.

03:01 Supercomputer simulations could unlock mystery of Moon's formation

Astronomers have taken a step towards understanding how the Moon might have formed out of a giant collision between the early Earth and another massive object 4.5 billion years ago.

03.12.2020
22:54 Light-based Quantum Computer Exceeds Fastest Classical Supercomputers

The setup of lasers and mirrors effectively “solved” a problem far too complicated for even the largest traditional computer system -- Read more on ScientificAmerican.com

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