Think Parallel
Bryce Adelstein Lelbach
But we must shatter these assumptions, for today, we live in a parallel world. Almost every hardware platform is parallel, from the smallest embedded devices to the largest supercomputers.
We must change our mindset. Anyone who writes code has to think in parallel. Parallelism must become our default.
In this example-driven talk, we will journey into the world of parallelism. We'll look at four algorithms and data structures in depth, comparing and contrasting different implementation strategies and exploring how they will perform both sequentially and in parallel.
During this voyage, we'll uncover and discuss some foundational principles of parallelism, such as latency hiding, localizing communication, and efficiency vs performance tradeoffs. By the time we're done, you'll be thinking in parallel.