e-infrastructure Roadmap for Open Science in Agriculture

A bibliometric study

The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.

This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.

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Advances in compute hardware platforms for computational lithography - art. no. 652018


The last six years have seen the increasing advance of computational and algorithmic complexity to compute mask patterns that retain sufficient lithographic fidelity to print and yield well enough to maintain the advances in circuit density that are the engine of the semiconductor economy. New Computational Lithography techniques such as Optical Proximity Correction (OPC), Scattering Bars (SB), Phase Shift Masks (PSM), and Lithography Verification (LV) constitute a significant transformation of the design. Initially applied only to the most critical portions of the most critical layers such as gate poly and active, they are now considered de-rigueur for almost every layer through and including the topmost metal layers. These new Computational Lithography applications have become one of the most computationally demanding steps in the design process. Compute farms of hundreds and even thousands of CPUs are now routinely used to run these applications. This paper will examine the evolution of these techniques and the computing systems to run them. A variant of Amdahl's law and an example COO equation to compute cost of ownership for the hardware platforms are developed. The practical aspects of the infrastructure needed to support such extensive compute farms including power, support, and cooling will be examined. Newly emerging High Performance Computing (HPC) techniques that hold the promise of checking this unbridled growth in computational requirements will be reviewed and contrasted including multi-core processors, Field Programmable Gate Arrays (FPGAs), The Cell Broadband Engine (CBE), Digital Signal Processors (DSPs), and Graphics Processing Units (GPUs) will be considered.

  • US
  • Mentor_Graph (US)
Data keywords
  • high performance computing
Agriculture keywords
  • farm
Data topic
  • big data
Optical Microlithography XX, Pts 1-3
Document type

Inappropriate format for Document type, expected simple value but got array, please use list format

Institutions 10 co-publis
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    e-ROSA - e-infrastructure Roadmap for Open Science in Agriculture has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730988.
    Disclaimer: The sole responsibility of the material published in this website lies with the authors. The European Union is not responsible for any use that may be made of the information contained therein.