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.
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About Ross Dickson
Ross is a Research Consultant with ACENET, an Atlantic Canadian not-for-profit that provides clients with access to a cutting-edge local supercomputing platform with CPUs, GPUs and cloud, along with extensive consulting expertise and training in how to use the system. Ross has been with ACENET for 12 years, providing support and training for clients in a wide range of research areas. After completing postdoctoral studies in computational chemistry, Ross worked in software development for Hypercube Inc., and for Molecular Mining Corporation. Over his years with ACENET, Ross has helped hundreds of supercomputing users accelerate their discoveries and achieve their project goals.
