Things I wish I knew about scientific computing before I started scientific computing

Shortly after starting my maths PhD, I came up against a numerical problem that required writing some code. I had some programming experience (as a hobby, making daft websites and that sort of thing) but was surprised at how little of it was transferrable to computing specifically for science. In the ten years since, as I've worked my way through a bunch of scientific computing problems related mostly to fluid dynamics, I've picked up a bunch of tips which I think I would have liked to have known from the beginning. This talk modestly aims to fill that gap! Although I am an applied mathematician, this talk should be accessible to everyone across the mathematics spectrum, and will include honest reflections on a bunch of tools that the audience might be using, or might want to use. For the novice, I hope to provide a broad sense of the landscape and a bunch of tips on where to start. For the expert, I hope to provide little bits of experience which boosted my productivity and might boost yours.

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