A few bad ideas on the way to the triumph of parallel computing

• Parallel computing has been an enormous success.
• This is despite many arguments against it.
• Existing code has not been usable.
• Specialized hardware accelerators have had trouble remaining relevant.

Parallelism has become mainstream, in the multicore chip, the GPU, and the internet datacenter running MapReduce. In my field, large-scale scientific computing, parallelism now reigns triumphant.It was no simple, direct route that led to this triumph. Along the way, we were confused by ideas that, in retrospect, turned out to be distractions and errors. The thinking behind them was reasonable, but wrong. One can learn from a dissection of mistakes, so I will retell part of the story here.