This white paper provides an overview of cloud pricing models and a high-level description of how they could be applied to performing engineering simulation using ANSYS Enterprise Cloud, while optimizing your hardware spend on Amazon Web Services (AWS).
Resources
White paper
23 November 2016
White paper
11 November 2016
Sanjay Khetia, Chief Technology Officer at the Centre for Modelling and Simulation (CFMS), talks about Industry 4.0, and the use of modelling and simulation to explore its possibilities.
White paper
04 November 2016
This white paper describes eight best practices for cloud deployments that are fundamentally related to simulation data and end user access, licensing, HPC workloads, and business support.
White paper
01 November 2016
This eBook has been developed to give you a comprehensive resource when searching for the laboratory data management solutions that can help your business meet the most pressing business and regulatory challenges. Inside you’ll find expert commentary on how integrated informatics can help you meet ISO 17025 requirements or manage daily workflow and SOP compliance issues in the lab. You’ll also find case studies from some of the largest oil and gas companies in the world, as well as technical product information and other supporting materials.
White paper
11 August 2016
Founded by world leaders in genome technology, cancer biology and medical oncology, Foundation Medicine is a cancer diagnostics company at the forefront of bringing comprehensive genomic analysis to routine cancer care.
Pages
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Building a Smart Laboratory 2018 highlights the importance of adopting smart laboratory technology, as well as pointing out the challenges and pitfalls of the process
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Informatics experts share their experiences on the implementing new technologies and manging change in the modern laboratory
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This chapter will consider the different classes of instruments and computerised instrument systems to be found in laboratories and the role they play in computerised experiments and sample processing – and the steady progress towards all-electronic laboratories.
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This chapter considers how the smart laboratory contributes to the requirements of a knowledge eco-system, and the practical consequences of joined-up science. Knowledge management describes the processes that bring people and information together to address the acquisition, processing, storage, use, and re-use of knowledge to develop understanding and to create value
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This chapter takes the theme of knowledge management beyond document handling into the analysis and mining of data. Technology by itself is not enough – laboratory staff need to understand the output from the data analysis tools – and so data analytics must be considered holistically, starting with the design of the experiment