Robert Roe interviews MathWorks Loren Dean, on the use of AI in modelling and simulation
Features
14 June 2019
As software has allowed scientists to focus on science, SaaS technologies in the cloud free up IT teams to focus on strategic priorities, writes Brady Haggstrom
14 June 2019
With data rates increasing and more complex challenges arising in life sciences, Robert Roe speaks with Panasas’ Jim Donovan and Dale Brantly about the benefits of using HPC for these workloads
14 June 2019
As HPC systems get larger and more complex, companies are developing services and tools to help users manage their resources effectively, writes Robert Roe
14 June 2019
FPGAs provide an early Insight into possibile architectural specialisation options for HPC and machine learning, writes Robert Roe
14 June 2019
Ivo Sbalzarini discusses how researchers are developing computational methods and software systems to understand biological processes on an algorithmic basis
14 June 2019
Robert Roe interviews John Shalf on the development of digital computing in the post Moore’s law era
14 May 2019
Robert Roe looks at storage technologies being developed to suit both AI and HPC workloads
14 May 2019
Robert Roe looks at advances in exascale computing and the impact of AI on HPC development
01 April 2019
Gemma Church investigates modelling and simulation tools required for accurate weather prediction
01 April 2019
Sophia Ktori concludes her two-part feature on the development of LIMS and ELN technology
01 February 2019
Gemma Church looks at modelling and simulation software in the aerospace industry
01 February 2019
Robert Roe considers cooling technologies available to HPC users
Pages
Latest issue
Every device needs to work seamlessly in its operating environment. But when that environment is a human body, things get complicated.
Christian Marcazzo, general manager at IDBS, highlights trends in life sciences research and development.
Data is a company’s biggest asset, yet for any organisation, keeping a handle on the potentially vast volumes and diversity of data that are generated can represent a considerable issue.
Rob Lalonde, Univa’s cloud VP general manager, considers the unique challenges posed by HPC
Deep learning has seen a huge rise in popularity over the last five years in both enterprise and scientific applications.
HPC users are increasingly turning to cloud technologies due to their flexibility and scalability, allowing them to quickly change the size of their workloads, adopt new technologies in a small testing environment and to help to increase the agility of a company working across multiple sites, or
