nytm-spelling-bee

The one-liner to solve that SB is grep -v '[^victmze]' /usr/share/dict/words | grep .... | grep e A very short program to generate all possible puzzles given a word list is at https://github.com/ncm/nytm-spelling-bee .

The one-liner to solve that SB is grep -v '[^victmze]' /usr/share/dict/words | grep .... | grep e A program to generate all possible NYTM SB puzzles is at https://github.com/ncm/nytm-spelling-bee . The alterations to match the online version are trivial. It runs in well under 100 ms on a modern CPU. There are bigger dictionaries packaged, e.g. wamerican-huge.

See puzzlegen.cc in https://github.com/ncm/nytm-spelling-bee/ Order of magnitude improvement.

If you are designing a sorting algorithm component for production, it is critical to take into account all the blips and wrinkles that real components will face. But when you are investigating how and why your CPU has the performance characteristics it has evolved, all those complications directly interfere with learning. The goal here was not to make a production-grade sorting tool; it was to understand what affects performance, using the sorting problem as a microscope. The method is generally useful. Some years back I spent months refining a one-page program[1] to generate a list of word puzzles. After the first day, the list of puzzles was of no interest, but refining the means to produce it faster taught me a great deal. [1] https://github.com/ncm/nytm-spelling-bee

I wrote one to generate all possible versions of the weekly puzzle (minimum 5-letter words) that score between 26 and 32 points, that runs in under 70 ms. It finds about 4.8k puzzles, for 14us per. (Nowadays they run puzzles that score as low as 20 (pfft).) https://github.com/ncm/nytm-spelling-bee/ I did both C++ and Rust versions. They run in the same time. My goal was the fastest single-threaded program that would fit on exactly one printed page. My first version ran in about a second, and I spent months shaving off milliseconds. Rust in 2016 was much more sensitive to arbitrary details of the source code. Maybe it's better now. The final version does enough setup to enable most of the time to be spent in a four-instruction loop that a modern core can do in a single cycle per iteration, with occasional detours. Compilers (clang is espec

The author compares gcc vs rustc.[1] I'm curious if the author considered comparing clang vs rustc since both use the LLVM backend. (I'm guessing the more mature C++ code generation would still win the benchmark but one could study the intermediate code emitted by clang/rustc instead of the final machine code emitted by gcc.) [1]https://github.com/ncm/nytm-spelling-bee/blob/master/Makefil...