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OSSPS Workshop 2 RFI Response - Oracle
<span title="2022-02-01">2022</span>
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Oracle offers a complete technology stack in the cloud, on premises, and in the data center. ...
Our transformative approach and capabilities around Open Science Big Data aligns well with the Open-Sourced Science (OSS) for NASA Earth System Observatory (ESO) Mission Science Data Processing objectives ...
Oracle Data Lake, a relational database that uses a combination of Hadoop for big data processing of structured data and a combination of hybrid /cloud storage would meet the complex needs of the rapid ...
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Modular supercomputing design supporting machine learning applications
<span title="">2018</span>
<i title="IEEE">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/v3i5vkn5d5h3folxmo4lsxioxi" style="color: black;">2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)</a>
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In this context, this paper focuses on machine learning in the remote sensing application domain but uses methods like Support Vector Machines (SVMs) that are also used in life sciences and other scientific ...
(HPC) systems today. ...
'big data'), ideally following a systematic process such as the Cross-Industry Standard Process for Data Mining (CRISP-DM) [1] . ...
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AIPerf: Automated machine learning as an AI-HPC benchmark
<span title="">2021</span>
<i title="Tsinghua University Press">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ijf7t5u575awlfr3o2g2yds3ju" style="color: black;">Big Data Mining and Analytics</a>
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We utilize Operations Per Second (OPS), which is measured in an analytical and systematic approach, as a major metric to quantify the AI performance. ...
In particular, the de facto HPC benchmark, LINPACK, cannot reflect the AI computing power and input/output performance without a representative workload. ...
As learnable data grow at an unprecedented rate, High-Performance Computing (HPC) machines are needed in large AI models to harness big data and extract complex abstractions [2] . ...
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<a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.26599/bdma.2021.9020004">doi:10.26599/bdma.2021.9020004</a>
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High Performance Computing in Satellite SAR Interferometry: A Critical Perspective
<span title="2021-11-24">2021</span>
<i title="MDPI AG">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kay2tsbijbawliu45dnhvyvgsq" style="color: black;">Remote Sensing</a>
</i>
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In this paper, a perspective on the state-of-the-art of high performance computing (HPC) methodologies applied to spaceborne SAR interferometry (InSAR) is presented, and the different parallel algorithms ...
Synthetic aperture radar (SAR) interferometry has rapidly evolved in the last decade and can be considered today as a mature technology, which incorporates computationally intensive and data-intensive ...
It was implemented by using the CUDA programming language. Furthermore, a GPU accelerated InSAR processing chain targeting S-1 TOPS images was developed in [212] . ...
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Big Data and cloud computing: innovation opportunities and challenges
<span title="2016-11-03">2016</span>
<i title="Informa UK Limited">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/cv2lgjhgznck5gafn7qca2wwo4" style="color: black;">International Journal of Digital Earth</a>
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At the same time, Big Data presents challenges for digital earth to store, transport, process, mine and serve the data. ...
cloud computing and processing Big Data; (v) open availability of Big Data and processing capability pose social challenges of geospatial significance and (vi) a weave of innovations is transforming Big ...
Dr George Taylor reviewed a previous version of this manuscript.
Disclosure statement No potential conflict of interest was reported by the authors.
Funding ...
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Why High-Performance Modelling and Simulation for Big Data Applications Matters
[chapter]
<span title="">2019</span>
<i title="Springer New York">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6v4flwr6afbfrmhdyu6xe3dyvm" style="color: black;">Msphere</a>
</i>
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Unfortunately, big data problems are often not easily amenable to efficient and effective use of High Performance Computing (HPC) facilities and technologies. ...
In this introductory article we argue why joining forces between M&S and HPC communities is both timely in the big data era and crucial for success in many application domains. ...
This work was supported by the ICT COST Action IC1406 High-Performance Modelling and Simulation for Big Data Applications. ...
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Additive Manufacturing and Big Data
<span title="2016-12-01">2016</span>
<i title="International Journal of Mathematical, Engineering and Management Sciences plus Mangey Ram">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dmk2gs7fhrddzhyn37xo5vkr2q" style="color: black;">International journal of mathematical, engineering and management sciences</a>
</i>
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Big Data analytics helps analyze AM processes and facilitate AM in impacting supply chains. This paper introduces advantages, applications, and technology progress of AM. ...
Cybersecurity in AM and barriers to broad adoption of AM are discussed. Big data in AM and Big Data analytics for AM are also presented. ...
Neural network and data mining/machine learning algorithms are used to bound process variables. ...
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A unified framework to improve the interoperability between HPC and Big Data languages and programming models
[article]
<span title="2021-12-01">2021</span>
<i >
arXiv
</i>
<span class="release-stage" >pre-print</span>
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The main consequence is that users could combine in the same multi-language code HPC tasks (using MPI) with Big Data tasks (using MapReduce operations). ...
To deal with this problem we introduce a new computing framework called IgnisHPC, whose main objective is to unify the execution of Big Data and HPC workloads in the same framework. ...
One way to approach Big Data and HPC worlds is trying to boost the performance of well-established Big Data technologies when running on HPC systems. ...
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ETP4HPC's Strategic Research Agenda for High-Performance Computing in Europe 4
[article]
<span title="2020-03-03">2020</span>
<i title="Zenodo">
Zenodo
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together with other related technologies - the material included in this SRA is also a result of our interactions with Big Data, Internet of Things (IoT), Artificial Intelligence (AI) and Cyber Physical ...
The main objective of this SRA is to identify the European technology research priorities in the area of HPC and High-Performance Data Analytics (HPDA), which should be used by EuroHPC to build its 2021 ...
Data Value Chain. ...
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Eurolab-4-HPC Long-Term Vision on High-Performance Computing
[article]
<span title="2018-07-11">2018</span>
<i >
arXiv
</i>
<span class="release-stage" >pre-print</span>
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This document presents the "EuroLab-4-HPC Long-Term Vision on High-Performance Computing" of August 2017, a road mapping effort within the EC CSA1 Eurolab-4-HPC that targets potential changes in hardware ...
, software, and applications in High-Performance Computing (HPC). ...
Potentially New HPC Applications We expect a pull by New Applications and SW Technologies: • High Performance Data Analysis (HPDA): data mining and analysis of big data • Pre-and post-processing, and data ...
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Technical Research Priorities for Big Data
[chapter]
<span title="">2021</span>
<i title="Springer International Publishing">
The Elements of Big Data Value
</i>
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The process also highlighted the important role of data standardisation, data engineering and DevOps for Big Data. ...
The result of the process identified five key technical research priorities in the areas of data management, data processing, data analytics, data visualisation and user interactions, and data protection ...
Novel architectures for enabling new types of big data workloads (hybrid big data and HPC architecture): Some selected domains have shown a considerable increase in the complexity of big data applications ...
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Enabling Dynamic and Intelligent Workflows for HPC, Data Analytics, and AI Convergence
[article]
<span title="2022-04-20">2022</span>
<i >
arXiv
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<span class="release-stage" >pre-print</span>
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<span title="2022-05-13">2022</span>
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Finally, it proposes a development approach for such a workflow platform addressing these challenges in two directions: first, by defining a software stack that provides the functionalities to manage these ...
While traditional HPC workflows target simulations and modelling of physical phenomena, current needs require in addition data analytics (DA) and artificial intelligence (AI) tasks. ...
Anna Queralt is a Serra Húnter Fellow. ...
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D5.3: Updated Best Practices for HPC Procurement and Infrastructure
<span title="2014-08-31">2014</span>
<i title="Zenodo">
Zenodo
</i>
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-1IP WP8), which have all sought to reach informed decisions within PRACE as a whole on the acquisition and hosting of HPC systems and infrastructure. ...
Specific areas of interest are analysed in depth in terms of the market they belong to and the general HPC landscape, with a particular emphasis on the European point of view. ...
hosting HPC facilities and supercomputing infrastructures (the Consorci Centre de Serveis Cientifics i Academics de Catalunya, CESCA in Spain and the group HKNR in LUH). ...
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Toxicity Analysis and Cry Gene Profiling of Bacillus Thuringiensis Isolated from Western Ghats of Tamil Nadu State, India
<span title="2018-05-01">2018</span>
<i title="Indian National Science Academy">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/jwvalmpmyrg6vku2tgyjjhdqdq" style="color: black;">Proceedings of the Indian National Science Academy</a>
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Computing as a discipline is a recent one even though the practice of using mechanical aids for calculation can have various dates based on the perspective of the reader like Blaise Pascal in 1600s, George ...
The thesis, which had a far-reaching impact on this field, is informally stated below: Any algorithmic problem for which an algorithm can be found in any programming language on any computer (existing ...
A similar approach that has also gained much research attention recently is to use graphics processing units (GPUs) to accelerate database query tasks [P. . ...
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GPU-Based Data Processing for 2-D Microwave Imaging on MAST
<span title="">2016</span>
<i title="Informa UK Limited">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/llnxnaydqzgsnibnuye6rrxeja" style="color: black;">Fusion science and technology</a>
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The acceleration of the SAMI diagnostic data processing code by a graphics processing unit (GPU) is presented, demonstrating acceleration of up to 60x compared to the original Interactive Data Language ...
(IDL) data processing code. ...
Section II gives a review of novel hardware used in big data experiments and section III discusses the high data rate SAMI diagnostic. ...
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