Parallel computing is the business of breaking a large problem into tens, hundreds, or even thousands of smaller problems which can then be solved at the same time, possibly on more than one computer. It can reduce processing time to a fraction of what it would have been, or enable you to tackle larger, more complex problems, or both. It’s widely used in big data mining, AI, time-critical simulations, and advanced graphics such as augmented or virtual reality. It’s used in fields as diverse as genetics, biotech, geographic information systems, computational fluid dynamics, medical imaging, drug discovery, and agriculture. During this talk, we’ll discuss: • The concepts around parallel computing • Opportunities for applying it • Where it works well, or not • Some of the challenges and considerations when thinking about applying it • How to assess whether your code is parallelizable If your computer is bursting at the seams to run your analyses, if you wonder “Is there a way to get these results faster?”, or if you have thought “we could do this better with more computing power”, this session will be of interest to you. Register About Ross Dickson Ross is a Research Consultant with ACENET, […]