High-performance Computation-based Geographical Data Processing and Process Simulation

2013 ◽  
Vol 5 (1) ◽  
pp. 243-250
Author(s):  
Wanqing Li ◽  
Xin Zhang
Keyword(s):  
Data Processing ◽  
Process Simulation ◽  
High Performance ◽  
Geographical Data ◽  
High Performance Computation

scholarly journals DEFINING EARTH DATA BATCH PROCESSING TASKS BY MEANS OF A FLEXIBLE WORKFLOWDESCRIPTION LANGUAGE

2016 ◽  
Vol III-4 ◽  
pp. 59-66 ◽  
Author(s):  
Constantin Nandra ◽  
Dorian Gorgan
Keyword(s):  
Image Processing ◽  
Data Processing ◽  
High Performance ◽  
Satellite Image ◽  
Batch Processing ◽  
Development Effort ◽  
Description Language ◽  
Design Complexity ◽  
Satellite Image Processing ◽  
High Performance Computation

This paper aims to present some of the main features of the Workflow Description Language (WorDeL) and demonstrate their usage in defining Earth Data processing tasks. This description language is based on the flexible description of processing tasks as workflows, composed of basic processing operators. This approach allows the language to offer an intuitive way of representing processing tasks, without requiring programming expertise from its users. It also allows its users to employ and integrate existing functionality into their design, thereby reducing the design complexity and development effort of newly defined processing workflows. WorDeL supports the transparent adaptive parallelization of the processing tasks over high performance computation architectures, such as cloud-based solutions. Throughout the paper, we will exemplify this language’s use in creating flexible, reusable and easy-to-understand earth data processing descriptions, with an emphasis on satellite image processing.

scholarly journals DEFINING EARTH DATA BATCH PROCESSING TASKS BY MEANS OF A FLEXIBLE WORKFLOWDESCRIPTION LANGUAGE

2016 ◽  
Vol III-4 ◽  
pp. 59-66 ◽  
Author(s):  
Constantin Nandra ◽  
Dorian Gorgan
Keyword(s):  
Image Processing ◽  
Data Processing ◽  
High Performance ◽  
Satellite Image ◽  
Batch Processing ◽  
Development Effort ◽  
Description Language ◽  
Design Complexity ◽  
Satellite Image Processing ◽  
High Performance Computation

This paper aims to present some of the main features of the Workflow Description Language (WorDeL) and demonstrate their usage in defining Earth Data processing tasks. This description language is based on the flexible description of processing tasks as workflows, composed of basic processing operators. This approach allows the language to offer an intuitive way of representing processing tasks, without requiring programming expertise from its users. It also allows its users to employ and integrate existing functionality into their design, thereby reducing the design complexity and development effort of newly defined processing workflows. WorDeL supports the transparent adaptive parallelization of the processing tasks over high performance computation architectures, such as cloud-based solutions. Throughout the paper, we will exemplify this language’s use in creating flexible, reusable and easy-to-understand earth data processing descriptions, with an emphasis on satellite image processing.

Quantum-Dot Transistor Based Multi-Bit Multiplier Unit for In-Memory Computing

2020 ◽  
Vol 29 (01n04) ◽  
pp. 2040007
Author(s):  
Yang Zhao ◽  
Fengyu Qian ◽  
Faquir Jain ◽  
Lei Wang
Keyword(s):  
Quantum Dot ◽  
Data Processing ◽  
High Performance ◽  
Memory Cell ◽  
Process Variations ◽  
High Energy ◽  
Data Movement ◽  
Neuron Networks ◽  
Fast Processing ◽  
Dot Product

In-memory computing is an emerging technique to fulfill the fast growing demand for high-performance data processing. This technique provides fast processing and high throughput by accessing data stored in the memory array rather than dealing with complicated operation and data movement on hard drive. For data processing, the most important computation is dot product, which is also the core computation for applications such as deep learning neuron networks, machine learning, etc. As multiplication is the key function in dot product, it is critical to improve its performance and achieve faster memory processing. In this paper, we present a design with the ability to perform in-memory multi-bit multiplications. The proposed design is implemented by using quantum-dot transistors, which enable multi-bit computations in the memory cell. Experimental results demonstrate that the proposed design provides reliable in-memory multi-bit multiplications with high density and high energy efficiency. Statistical analysis is performed using Monte Carlo simulations to investigate the process variations and error effects.

High-Performance Computing for Big Data Processing

2018 ◽  
Vol 88 ◽  
pp. 693-695 ◽  
Author(s):  
Yulei Wu ◽  
Yang Xiang ◽  
Jingguo Ge ◽  
Peter Muller
Keyword(s):  
Big Data ◽  
Data Processing ◽  
High Performance Computing ◽  
High Performance ◽  
Big Data Processing ◽  
Performance Computing

MITK Diffusion Imaging

2012 ◽  
Vol 51 (05) ◽  
pp. 441-448 ◽  
Author(s):  
P. F. Neher ◽  
I. Reicht ◽  
T. van Bruggen ◽  
C. Goch ◽  
M. Reisert ◽  
...  
Keyword(s):  
Data Processing ◽  
Open Source ◽  
High Performance ◽  
Diffusion Imaging ◽  
Software Tool ◽  
Brain Anatomy ◽  
Sustainable Evaluation ◽  
Imaging Research ◽  
Interactive Data

SummaryBackground: Diffusion-MRI provides a unique window on brain anatomy and insights into aspects of tissue structure in living humans that could not be studied previously. There is a major effort in this rapidly evolving field of research to develop the algorithmic tools necessary to cope with the complexity of the datasets.Objectives: This work illustrates our strategy that encompasses the development of a modularized and open software tool for data processing, visualization and interactive exploration in diffusion imaging research and aims at reinforcing sustainable evaluation and progress in the field.Methods: In this paper, the usability and capabilities of a new application and toolkit component of the Medical Imaging and Interaction Toolkit (MITK, www.mitk.org), MITKDI, are demonstrated using in-vivo datasets.Results: MITK-DI provides a comprehensive software framework for high-performance data processing, analysis and interactive data exploration, which is designed in a modular, extensible fashion (using CTK) and in adherence to widely accepted coding standards (e.g. ITK, VTK). MITK-DI is available both as an open source software development toolkit and as a ready-to-use in stallable application.Conclusions: The open source release of the modular MITK-DI tools will increase verifiability and comparability within the research community and will also be an important step towards bringing many of the current techniques towards clinical application.

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