scholarly journals Compression Challenges in Large Scale Partial Differential Equation Solvers

Algorithms ◽  
2019 ◽  
Vol 12 (9) ◽  
pp. 197 ◽  
Author(s):  
Sebastian Götschel ◽  
Martin Weiser
Keyword(s):  
Data Compression ◽  
Large Scale ◽  
Memory Hierarchy ◽  
Main Memory ◽  
Computational Science ◽  
Limiting Factor ◽  
Mass Storage ◽  
Partial Differential ◽  
Computing Power ◽  
Pde Solvers

Solvers for partial differential equations (PDEs) are one of the cornerstones of computational science. For large problems, they involve huge amounts of data that need to be stored and transmitted on all levels of the memory hierarchy. Often, bandwidth is the limiting factor due to the relatively small arithmetic intensity, and increasingly due to the growing disparity between computing power and bandwidth. Consequently, data compression techniques have been investigated and tailored towards the specific requirements of PDE solvers over the recent decades. This paper surveys data compression challenges and discusses examples of corresponding solution approaches for PDE problems, covering all levels of the memory hierarchy from mass storage up to the main memory. We illustrate concepts for particular methods, with examples, and give references to alternatives.

Current State of (Dis)Integration: Public Health and Fusion Centers

2020 ◽  
Vol 17 (2) ◽  
Author(s):  
Cody Minks ◽  
Anke Richter
Keyword(s):  
Public Health ◽  
Law Enforcement ◽  
Information Sharing ◽  
Homeland Security ◽  
Large Scale ◽  
Ad Hoc ◽  
Limiting Factor ◽  
Fusion Centers ◽  
Public Health Emergencies ◽  
Public Health Information

AbstractObjectiveResponding to large-scale public health emergencies relies heavily on planning and collaboration between law enforcement and public health officials. This study examines the current level of information sharing and integration between these domains by measuring the inclusion of public health in the law enforcement functions of fusion centers.MethodsSurvey of all fusion centers, with a 29.9% response rate.ResultsOnly one of the 23 responding fusion centers had true public health inclusion, a decrease from research conducted in 2007. Information sharing is primarily limited to information flowing out of the fusion center, with little public health information coming in. Most of the collaboration is done on a personal, informal, ad-hoc basis. There remains a large misunderstanding of roles, capabilities, and regulations by all parties (fusion centers and public health). The majority of the parties appear to be willing to work together, but there but there is no forward momentum to make these desires a reality. Funding and staffing issues seem to be the limiting factor for integration.ConclusionThese problems need to be urgently addressed to increase public health preparedness and enable a decisive and beneficial response to public health emergencies involving a homeland security response.

scholarly journals Cloud-based intelligent self-diagnosis and department recommendation service using Chinese medical BERT

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Junshu Wang ◽  
Guoming Zhang ◽  
Wei Wang ◽  
Ka Zhang ◽  
Yehua Sheng
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Medical Service ◽  
Rapid Development ◽  
Medical Knowledge ◽  
Language Models ◽  
Computing Environment ◽  
Computing Power ◽  
Cloud Computing Environment ◽  
Proposed Model

AbstractWith the rapid development of hospital informatization and Internet medical service in recent years, most hospitals have launched online hospital appointment registration systems to remove patient queues and improve the efficiency of medical services. However, most of the patients lack professional medical knowledge and have no idea of how to choose department when registering. To instruct the patients to seek medical care and register effectively, we proposed CIDRS, an intelligent self-diagnosis and department recommendation framework based on Chinese medical Bidirectional Encoder Representations from Transformers (BERT) in the cloud computing environment. We also established a Chinese BERT model (CHMBERT) trained on a large-scale Chinese medical text corpus. This model was used to optimize self-diagnosis and department recommendation tasks. To solve the limited computing power of terminals, we deployed the proposed framework in a cloud computing environment based on container and micro-service technologies. Real-world medical datasets from hospitals were used in the experiments, and results showed that the proposed model was superior to the traditional deep learning models and other pre-trained language models in terms of performance.

Towards A Multi-FPGA Infrared Simulator

2007 ◽  
Vol 4 (4) ◽  
pp. 343-355 ◽  
Author(s):  
Vinay Sriram ◽  
David Kearney
Keyword(s):  
Homeland Security ◽  
Reconfigurable Computing ◽  
High Speed ◽  
High Performance ◽  
Large Scale ◽  
Computation Time ◽  
Ccd Camera ◽  
Hardware Acceleration ◽  
Limiting Factor ◽  
Scene Simulation

High speed infrared (IR) scene simulation is used extensively in defense and homeland security to test sensitivity of IR cameras and accuracy of IR threat detection and tracking algorithms used commonly in IR missile approach warning systems (MAWS). A typical MAWS requires an input scene rate of over 100 scenes/second. Infrared scene simulations typically take 32 minutes to simulate a single IR scene that accounts for effects of atmospheric turbulence, refraction, optical blurring and charge-coupled device (CCD) camera electronic noise on a Pentium 4 (2.8GHz) dual core processor [7]. Thus, in IR scene simulation, the processing power of modern computers is a limiting factor. In this paper we report our research to accelerate IR scene simulation using high performance reconfigurable computing. We constructed a multi Field Programmable Gate Array (FPGA) hardware acceleration platform and accelerated a key computationally intensive IR algorithm over the hardware acceleration platform. We were successful in reducing the computation time of IR scene simulation by over 36%. This research acts as a unique case study for accelerating large scale defense simulations using a high performance multi-FPGA reconfigurable computer.

scholarly journals The Management Strategy of Metadata in Large-scale Network Storage System

2018 ◽  
Vol 228 ◽  
pp. 01011
Author(s):  
Haifeng Zhong ◽  
Jianying Xiong
Keyword(s):  
Large Scale ◽  
Storage System ◽  
Hash Table ◽  
Distributed Hash Table ◽  
Distributed Data ◽  
Mass Storage ◽  
Large Scale Network ◽  
Network Storage System ◽  
Mass Storage System ◽  
Scale Network

The wan Internet storage system based on Distributed Hash Table uses fully distributed data and metadata management, and constructs an extensible and efficient mass storage system for the application based on Internet. However, such systems work in highly dynamic environments, and the frequent entry and exit of nodes will lead to huge communication costs. Therefore, this paper proposes a new hierarchical metadata routing management mechanism based on DHT, which makes full use of the node stabilization point to reduce the maintenance overhead of the overlay. Analysis shows that the algorithm can effectively improve efficiency and enhance stability.

scholarly journals Energy Production Benefits by Wind and Wave Energies for the Autonomous System of Crete

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2741 ◽  
Author(s):  
George Lavidas ◽  
Vengatesan Venugopal
Keyword(s):  
Wind Turbine ◽  
Wave Energy ◽  
Energy Production ◽  
Large Scale ◽  
Capital Expenditure ◽  
Temporal Correlation ◽  
Clean Energy ◽  
Limiting Factor ◽  
Spatio Temporal ◽  
Visual Impacts

At autonomous electricity grids Renewable Energy (RE) contributes significantly to energy production. Offshore resources benefit from higher energy density, smaller visual impacts, and higher availability levels. Offshore locations at the West of Crete obtain wind availability ≈80%, combining this with the installation potential for large scale modern wind turbines (rated power) then expected annual benefits are immense. Temporal variability of production is a limiting factor for wider adaptation of large offshore farms. To this end multi-generation with wave energy can alleviate issues of non-generation for wind. Spatio-temporal correlation of wind and wave energy production exhibit that wind and wave hybrid stations can contribute significant amounts of clean energy, while at the same time reducing spatial constrains and public acceptance issues. Offshore technologies can be combined as co-located or not, altering contribution profiles of wave energy to non-operating wind turbine production. In this study a co-located option contributes up to 626 h per annum, while a non co-located solution is found to complement over 4000 h of a non-operative wind turbine. Findings indicate the opportunities associated not only in terms of capital expenditure reduction, but also in the ever important issue of renewable variability and grid stability.

scholarly journals Influência da vernalização de semente na produção, crescimento e desenvolvimento de plantas de lisianthus

2018 ◽  
Vol 39 (6) ◽  
pp. 2325 ◽  
Author(s):  
Maria Yumbla-Orbes ◽  
José Geraldo Barbosa ◽  
Wagner Campos Otoni ◽  
Marcel Santos Montezano ◽  
José Antônio Saraiva Grossi ◽  
...  
Keyword(s):  
Large Scale ◽  
Limiting Factor ◽  
Scale Production ◽  
Cut Flower ◽  
Cut Flowers ◽  
Flower Production ◽  
Commercial Scale ◽  
Large Scale Production ◽  
And Control

Flowering induction and control is a limiting factor when commercially producing cut flowers of lisianthus and seed exposure to low temperatures, a physiological event called vernalization, induces the differentiation of vegetative buds to reproductive buds, contributing to a flowering that is uniform and has quality. The objective of this study was to evaluate the influence of seed vernalization in three cultivars of lisianthus (Excalibur, Echo and Mariachi) for 12, 24, 36 and 48 days at temperatures of 5, 10 and 15°C, in the production and quality of buds, making this technology feasible to large-scale production. During cultivation it was observed that the lower the temperature and higher the vernalization period, the lower the cycle and the greater the number of plants induced to flowering for all three cultivars, and those are important features in the context of flower production in a commercial scale. The seeds subjected to vernalization originated plants that produce flower stems within the standards required by the market, showing that vernalization was efficient to induce flowering without affecting the quality of the buds. To produce lisianthus as a cut flower of quality, it is recommended seed vernalization of Mariachi and Echo cultivars for 24 days at 5°C and Excalibur for 36 days at 5°C.

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