I recently saw a video that explains Diffie–Hellman key exchange in terms of mixing colors of paint. It's a wonderfully simple and informative analogy, that Wikipedia actually uses as well. If you don't know about Diffie-Hellman, definitely watch the video and/or read the Wikipedia page to get a handle on it—it's not that complicated once you get the "trick." The color analogy intrigued me because I know just enough about both cryptography and color theory to be dangerous. So in this post, I'm going to attack the security of the color exchange protocol. ("Real" Diffie-Hellman remains secure, as far as I know.) Continue reading Cracking DHCE (Diffie-Hellman color exchange)
I recently released version 1.1.3 of
bfs, my breadth-first drop-in replacement for the UNIX
find command. The major change in this release is a refactor of the optimizer, so I figured it would be a good time to write up some of the details of its implementation. Continue reading bfs from the ground up, part 3: optimization
Today is the release of version 1.0 of
bfs, a fully-compatible* drop-in replacement for the UNIX
find command. I thought this would be a good occasion to write more about its implementation. This post will talk about how I parse the command line. Continue reading bfs from the ground up, part 2: parsing
If you need to multiply some matrices together very quickly, usually it's best to use a highly optimized library like ATLAS. But sometimes adding such a dependency isn't worth it, if you're worried about portability, code size, etc. If you just need good performance, rather than the best possible performance, it can make sense to hand-roll your own matrix multiplication function. Continue reading A quick trick for faster naïve matrix multiplication
bfs is a tool I've been writing for about a year, with the goal of being a drop-in replacement for the UNIX
find command. This series of posts will be deep technical explorations of its implementation, starting from the lower levels all the way up to the user interface.
bfs is small (only about 3,500 lines of C code), which makes it possible to do a fairly complete analysis. But the codebase is fairly clean and highly optimized, which should make the analysis interesting. Continue reading bfs from the ground up, part 1: traversal
Nearest neighbour search is a very natural problem: given a target point and a set of candidates, find the closest candidate to the target. For points in the standard k-dimensional Euclidean space, k-d trees and related data structures offer a good solution. But we're not always so lucky.
In part 1, I outlined an algorithm for computing intersections between rays and axis-aligned bounding boxes. The idea to eliminate branches by relying on IEEE 754 floating point properties goes back to Brian Smits in , and the implementation was fleshed out by Amy Williams. et al. in .
It's surprisingly difficult to find a good code snippet for this on Google, so here's an efficient computation of integer powers in C, using binary exponentiation:
Clang is known for its great error messages, but I did manage to horribly confuse it: