Computing applied to the earth sciences will save human lives, according to Felix Grant
Gemma Church finds out how scientists are using HPC to predict climate and weather more accurately and efficiently
The increase in automation in forensic science in the last few years has led to a requirement for data management systems. Greg Blackman looks at the importance of LIMS in forensic laboratories
While GPUs (graphics processing units) were initially designed to accelerate video and gaming, vendors of science and engineering software are using them to accelerate their code. Paul Schreier looks at the benefits for today and tomorrow
Professor Marek Niezgódka, Director of the ICM Centre at the University of Warsaw, explains why the centre heads the Green Top500 list and concentrates on open systems
Trevor Heritage, president, Symyx Software
Paul Schreier reviews a sample of the applications and breakthrough products that advanced optics software have made possible
Dietmar Maringer, professor of computational management sciences, University of Basel
In January 2020 the American Diabetes Association released a new set of clinical standards that, for the first time, included the use of an FDA-approved autonomous artificial intelligence (AI) platform for detecting diabetic retinopathy in people with diabetes.
At the end of February physIQ and the US Department of Veteran’s Affairs published data from a clinical trial demonstrating the use of physIQ’s machine-learning algorithm to predict when an individual patient with previously diagnosed heart failure will likely require a readmission to hospital.
Cloud research tools provide a platform for new avenues of scientific research by providing fast access to bare-metal resources.
New processors and GPU technology continue to demand more power than the previous generations, combining this with increasingly dense architectures requires cooling solutions such as liquid or immersion cooling.
Tate Cantrell, CTO, Verne Global, comments on the cost of the AI computing revolution
European researchers are working on a new programming environment for exascale computing that aims to make using these systems more efficient and programmers more productive.
