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The TESS science processing operations center Open
The Transiting Exoplanet Survey Satellite (TESS) will conduct a search for Earths closest cousins starting in late 2017. TESS will discover approx.1,000 small planets and measure the masses of at least 50 of these small worlds. The Science…
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EPA-ng: Massively Parallel Evolutionary Placement of Genetic Sequences Open
Next generation sequencing (NGS) technologies have led to a ubiquity of molecular sequence data. This data avalanche is particularly challenging in metagenetics, which focuses on taxonomic identification of sequences obtained from diverse …
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The EC-Earth3 Earth system model for the Coupled Model Intercomparison Project 6 Open
The Earth system model EC-Earth3 for contributions to CMIP6 is documented here, with its flexible coupling framework, major model configurations, a methodology for ensuring the simulations are comparable across different high-performance c…
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The future of computing beyond Moore’s Law Open
Moore’s Law is a techno-economic model that has enabled the information technology industry to double the performance and functionality of digital electronics roughly every 2 years within a fixed cost, power and area. Advances in silicon l…
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Kokkos 3: Programming Model Extensions for the Exascale Era Open
As the push towards exascale hardware has increased the diversity of system architectures, performance portability has become a critical aspect for scientific software. We describe the Kokkos Performance Portable Programming Model that all…
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Supercomputer Lomonosov-2: Large Scale, Deep Monitoring and Fine Analytics for the User Community Open
The huge number of hardware and software components, together with a large number of parameters affecting the performance of each parallel application, makes ensuring the efficiency of a large scale supercomputer extremely difficult. In th…
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TPU v4: An Optically Reconfigurable Supercomputer for Machine Learning with Hardware Support for Embeddings Open
In response to innovations in machine learning (ML) models, production workloads changed radically and rapidly. TPU v4 is the fifth Google domain specific architecture (DSA) and its third supercomputer for such ML models. Optical circuit s…
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JURECA: Modular supercomputer at Jülich Supercomputing Centre Open
JURECA is a petaflop-scale modular supercomputer operated by Jülich Supercomputing Centre at Forschungszentrum Jülich. The system combines a flexible Cluster module, based on T-Platforms V-Class blades with a balanced selection of best of …
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Memristors—From In‐Memory Computing, Deep Learning Acceleration, and Spiking Neural Networks to the Future of Neuromorphic and Bio‐Inspired Computing Open
Machine learning, particularly in the form of deep learning (DL), has driven most of the recent fundamental developments in artificial intelligence (AI). DL is based on computational models that are, to a certain extent, bio‐inspired, as t…
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JUWELS: Modular Tier-0/1 Supercomputer at the Jülich Supercomputing Centre Open
JUWELS is a multi-petaflop modular supercomputer operated by Jülich Supercomputing Centre at Forschungszentrum Jülich as a European and national supercomputing resource for the Gauss Centre for Supercomputing. In addition, JUWELS serves th…
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An Overview of Soft Computing Open
Soft computing, as opposed to traditional computing, deals with approximate models and gives solutions to complex real-life problems. Unlike hard computing, soft computing is tolerant of imprecision, uncertainty, partial truth, and approxi…
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Interactive Supercomputing on 40,000 Cores for Machine Learning and Data Analysis Open
Interactive massively parallel computations are critical for machine learning and data analysis. These computations are a staple of the MIT Lincoln Laboratory Supercomputing Center (LLSC) and has required the LLSC to develop unique interac…
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Evaluating Modern GPU Interconnect: PCIe, NVLink, NV-SLI, NVSwitch and GPUDirect Open
High performance multi-GPU computing becomes an inevitable trend due to the\never-increasing demand on computation capability in emerging domains such as\ndeep learning, big data and planet-scale simulations. However, the lack of deep\nund…
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Parcels v0.9: prototyping a Lagrangian ocean analysis framework for the petascale age Open
As ocean general circulation models (OGCMs) move into the petascale age, where the output of single simulations exceeds petabytes of storage space, tools to analyse the output of these models will need to scale up too. Lagrangian ocean ana…
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A domain-specific supercomputer for training deep neural networks Open
Google's TPU supercomputers train deep neural networks 50x faster than general-purpose supercomputers running a high-performance computing benchmark.
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Repurposing Therapeutics for COVID-19: Supercomputer-Based Docking to the SARS-CoV-2 Viral Spike Protein and Viral Spike Protein-Human ACE2 Interface Open
The novel Wuhan coronavirus (SARS-CoV-2) has been sequenced, and the virus shares substantial similarity with SARS-CoV. Here, using a computational model of the spike protein (S-protein) of SARS-CoV-2 interacting with the human ACE2 recept…
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Fault and Error Tolerance in Neural Networks: A Review Open
Beyond energy, the growing number of defects in physical substrates is becoming another major constraint that affects the design of computing devices and systems. As the underlying semiconductor technologies are getting less and less relia…
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JURECA: Data Centric and Booster Modules implementing the Modular Supercomputing Architecture at Jülich Supercomputing Centre Open
JURECA is a Pre-Exascale Modular Supercomputer operated by Jülich Supercomputing Centre at Forschungszentrum Jülich. The system combines a flexible Data Centric (DC) module, based on the Atos BullSequana XH2000 with a selection of best-of-…
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Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms Open
We present a highly scalable Monte Carlo (MC) three-dimensional photon transport simulation platform designed for heterogeneous computing systems. Through the development of a massively parallel MC algorithm using the Open Computing Langua…
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1001 Ways to run AutoDock Vina for virtual screening Open
Large-scale computing technologies have enabled high-throughput virtual screening involving thousands to millions of drug candidates. It is not trivial, however, for biochemical scientists to evaluate the technical alternatives and their i…
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In‐Memory Vector‐Matrix Multiplication in Monolithic Complementary Metal–Oxide–Semiconductor‐Memristor Integrated Circuits: Design Choices, Challenges, and Perspectives Open
The low communication bandwidth between memory and processing units in conventional von Neumann machines does not support the requirements of emerging applications that rely extensively on large sets of data. More recent computing paradigm…
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Anomaly Detection Using Autoencoders in High Performance Computing Systems Open
Anomaly detection in supercomputers is a very difficult problem due to the big scale of the systems and the high number of components. The current state of the art for automated anomaly detection employs Machine Learning methods or statist…
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Constant-pH Molecular Dynamics Simulations for Large Biomolecular Systems Open
An increasingly important endeavor is to develop computational strategies that enable molecular dynamics (MD) simulations of biomolecular systems with spontaneous changes in protonation states under conditions of constant pH. The present w…
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Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19 Open
We present a supercomputer-driven pipeline for in silico drug discovery using enhanced sampling molecular dynamics (MD) and ensemble docking. Ensemble docking makes use of MD results by docking compound databases into representative protei…
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JURECA: General-purpose supercomputer at Jülich Supercomputing Centre Open
JURECA is a petaflop-scale, general-purpose supercomputer operated by Jülich Supercomputing Centre at Forschungszentrum Jülich. Utilizing a flexible cluster architecture based on T-Platforms V-Class blades and a balanced selection of best …
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A Bi-layered Parallel Training Architecture for Large-Scale Convolutional Neural Networks Open
Benefitting from large-scale training datasets and the complex training\nnetwork, Convolutional Neural Networks (CNNs) are widely applied in various\nfields with high accuracy. However, the training process of CNNs is very\ntime-consuming,…
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Parallelization of CPPTRAJ enables large scale analysis of molecular dynamics trajectory data Open
Advances in biomolecular simulation methods and access to large scale computer resources have led to a massive increase in the amount of data generated. The key enablers have been optimization and parallelization of the simulation codes. H…
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Deploying a Top-100 Supercomputer for Large Parallel Workloads Open
Niagara is currently the fastest supercomputer accessible to academics in Canada. It was deployed at the beginning of 2018 and has been serving the research community ever since. This homogeneous 60,000-core cluster, owned by the Universit…
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Near-global climate simulation at 1 km resolution: establishing a performance baseline on 4888 GPUs with COSMO 5.0 Open
The best hope for reducing long-standing global climate model biases is by increasing resolution to the kilometer scale. Here we present results from an ultrahigh-resolution non-hydrostatic climate model for a near-global setup running on …
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SAMSA2: a standalone metatranscriptome analysis pipeline Open
SAMSA2 is a rapid and efficient metatranscriptome pipeline for analyzing large RNA-seq datasets in a supercomputing cluster environment. SAMSA2 provides simplified output that can be examined directly or used for further analyses, and its …