Functional Array Funhouse Intensive - Part 2 of 5
summary
Claims that Iverson-style array programming yields order-of-magnitude code shrink and speedups, demonstrates APL primitives (iota, reshape, inner/outer product, implicit elementwise mapping, quad IO) and shows a one-line Game of Life implementation with no loops or branches. Uses tryAPL.org, APL keyboard/layouts, and a Cody Funds GPU pipeline so the cellular automaton runs on GPU via Cody Funds as an animation. Examples compile and display; walk-through covers workspace, boxing/unboxing, rank/depth and practical deployment details.
AI-written summary · about
chapters (18)
- 0:00APL workspace setup
- 3:06APL workspaces and state
- 5:36Generating and reshaping arrays
- 12:15Boolean matrices in APL
- 13:45Rotating arrays and minus operators
- 17:55Strands and nested arrays
- 22:47APL keyboard layouts
- 24:03Array ranks and dimensions
- 25:56Mapping functions over arrays
- 28:33Outer products and combinations
- 32:25Reducing arrays along axes
- 36:04Game of Life in APL
- 41:37Disclosing and unboxing arrays
- 43:06Turning expressions into functions
- 47:44Iterating Game of Life
- 48:36APL animations with Kody Funds
- 53:22Debugging APL code
- 54:49Reflecting on APL challenges
related talks
01h 17mModern APL in the Real World: Theory, Practice, Case Studies
01h 07mParallel-by-construction Tree Manipulation with APL (Part 2)
27mAPL-Inspired Techniques for Advanced NumPy
55mParallel-by-construction Tree Manipulation with APL (Part 1)
43muarray - Efficient and Generic Array Computation
27mConvolutional Neural Networks in APL
32mImmutable Arrays Help Mutating Arrays More Efficiently
15mCompilation of Sparse Array Programming Models