February 23, 2026
Math flex or hype train?
C99 implementation of new O(m log^(2/3) n) shortest path algorithm
Dev claims 20,000x faster shortest paths; commenters scream “show your work”
TLDR: A C99 implementation of a new shortest-path method claims massive speedups on huge graphs, breaking an old performance limit. The community’s split: some cheer the breakthrough, while skeptics question if benefits only appear at extreme sizes and want proof, transparency, and less AI mystery.
A C99 dev dropped a bombshell: a new shortest-path code based on a 2025 paper promises 20,000x speedups and breaks a 65-year-old “sorting barrier.” Translation: it finds routes from one point to everything else way faster, especially on giant graphs. The author touts zero memory allocations, cache-hugging data, and a recursive twist instead of the old-school priority queue. Cue the comments: chaos. One skeptic asked if the fancy math only wins when your network is astronomically huge, wondering if everyday users will notice. Another linked the vibe to the arcane world of number-crunching like the General Number Field Sieve, turning the thread into a math meme party. The spiciest drama? A self-described “reviewer #2” called out the dev for using AI and demanded a blow-by-blow of the process, essentially asking: is this more than a copy-paste flex? Meanwhile, someone just wrote “Slop”—the internet’s most efficient code review. Fans cheered the claim that on million-node graphs, the code blitzes past the old bottleneck, while doubters want real-world benchmarks and reproducible tests, not just compiler flags and vibes. The mood is equal parts hype, homework assignment, and one-word roast. For receipts, readers pinged the paper on arXiv and asked for head-to-head demos against Dijkstra.
Key Points
- •DMMSY is a C99 implementation of a new SSSP algorithm achieving O(m log^(2/3) n), based on a STOC 2025 paper by Duan, Mao, Mao, Shu, and Yin.
- •The implementation replaces global priority queues with recursive subproblem decomposition to break the traditional sorting bottleneck.
- •Design features include zero-allocation with pre-allocated workspaces, a cache-optimized CSR layout, modular components, and platform-independent high-precision timing.
- •Benchmarks on x86_64 using Clang -O3 with LTO and Fast-Math report speedups exceeding 20,000x over standard Dijkstra on large sparse graphs (≈250k–1M+ nodes).
- •The project provides build instructions, a benchmarking suite, reference Dijkstra implementation, dual MIT/Apache-2.0 licensing, and references to the research paper and sources.