#Environment
> The huge #carbon footprint of large-scale #computing

> #Lannelongue would like it if researchers just started thinking more about the emissions of their computing, factoring it into their decisions.
physicsworld.com/a/the-huge-ca

> #GreenAlgorithms is an online tool that enables researchers to estimate the carbon footprint of their computing
green-algorithms.org

> #PortegiesZwart thinks that instead of teaching #physicists more computing, perhaps physics research institutes should employ more computer experts. “We are great at physics, but a computer scientist spent all the time we learned about physics learning how to communicate with a computer,” he says. “There is no doubt that [they] will be better at #programming.”

@julm That’s a misunderstanding. Computer scientists learn how to create maintainable programs. That’s not really what high performance physics computing needs. With mpi, openmp, and high performance math libraries, scientific computing runs circles around code from most computer experts. But it has horrible abstractions (if at all) and is terrible to adapt to new situations.

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@ArneBab @julm I don't completely agree. Most people working in what we call the "computer science" field had learned how to create maintainable programs. Some of us, computer scientists, had learned how to write efficient (in speed and energy) programs (or even not programs). Actually, where do you think MPI, OpenMP, maths libraries and stuff come from ? 😉

@Thib @julm I agree — but that’s not a distinction from the physicists. In both fields (CS and Physics) there are people with a specialization on time and/or¹ energy efficient programming.

Where I see CS but *not* physicists is stuff like pypy.org

¹: I prefer the "and", but there’s also the inefficient-maximum-parallelism and the serial-but-energy-saving subtype.

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