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c0d3x.org · proprietary · v2.14.5

status privacy changelogBUILT WITH NEXT 16 · REACT 19 · TAILWIND 4// stay curious

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#1000 #100daysofsolana #100daysofsolona #2026 #a11y #accountability #achievement #activator #actors #adaptive #adopting

LOBMay 4, 2026 · 46m ago

Redis array type: short story of a long development

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DEVMay 3, 2026 · 22h ago

↑ 0

Breaking the Speed Limit: Why C++ & JavaScript Are the Ultimate 2026 Power Combo ⚡

Hello Developers! 👋 Most developers today pick a side: Let’s talk about combining C++ and JavaScript—the ultimate hybrid stack for high-performance applications. 👇 1. The Core Engine (C++) ⚙️ 2. The Browser Bridge (WebAssembly) 🌉 3. The Cinematic Experience (Vanilla JS + UI/UX) ✨ The Takeaway 🎯 Keep optimizing, keep building! 💻✨ ~ Ujjwal Sharma | @stackbyujjwal About the Author 👨‍💻 Ujjwal

#ai#cpp#java#programming

#vectorsearch#cpp

DEVMay 3, 2026 · 23h ago

How I Made My Vector Search Engine 16x Faster Without Changing the Algorithm

I built a Vamana-based vector search engine in C++ called sembed-engine. Recently I made a pull request that sped up queries by 16x and builds by 9x. The algorithm stayed exactly the same. The recall stayed at 1.0. The number of visited nodes did not change. The speedup came from data layout. The original code stored vectors as separate objects pointed to by shared_ptr: struct Record { int64_t

#vectorsearch#cpp#performance#vamana

#algorithms#ann

DEVMay 3, 2026 · 23h ago

Reading Algorithms Like an Engineer: What DiskANN Taught Me About Pseudocode

The first time I implemented Vamana from the DiskANN paper, my approximate nearest neighbor index was slower than brute force. On tiny test fixtures, brute force took 0.27 ms per query. My Vamana implementation took 22.98 ms. That sounds absurd. ANN exists to skip work. The problem was not the algorithm. It was how I mapped the paper's abstractions to actual data structures. The DiskANN pseudocode

#algorithms#ann#cpp#diskann

#cpp#performance

DEVMay 3, 2026 · 23h ago

Why You Should Never Use std::unordered_set in Hot C++ Loops

Hash tables feel like the default choice for membership tests. std::unordered_set promises average O(1) lookup, so we reach for it automatically. In performance-sensitive C++ code, that habit can cost you an order of magnitude. I ran into this while building a Vamana graph index for approximate nearest neighbor search. The algorithm needs to track visited nodes. Node ids are dense integers, and th

#cpp#performance#algorithms#benchmarking

DEVMay 3, 2026 · 1d ago

OneDialect — Unified Assistive Communication System (UACS)

A production-grade embedded system enabling communication across speech, text, Morse, and haptic signals within a single unified pipeline. Official Project Page: https://anandps.in/projects/unified-assistive-communication-system GitHub Repository: https://github.com/anand-ps/unified-assistive-communication-system Problem Assistive communication systems are fragmented. Most tools so

#python#cpp#raspberrypi#arduino

#cpp#performance

DEVMay 3, 2026 · 1d ago

The 128-arm pattern dispatch problem and how we got from 11ns to 1.1ns

The problem Pattern matching on a large set of literal values looks clean in code but hits a wall at runtime. Every on() call constructs case objects for every arm. With 128 arms, that is 128 object constructions per match call. At 11ns per call, this is fine for one-off use. Inside a hot loop, it is a disaster. // Clean syntax, 128 case objects constructed per call return match(x) | on( lit(0

#cpp#performance#programming#tutorial

DEVMay 3, 2026 · 1d ago

Built a efficient and fast MRI compression program called KMRI!

KMRI is chunk-based MRI compression format for .nii files (Python + Zstd and C++). Check it out at https://github.com/Kiamehr5/KMRI and let me know what you think 💻