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 old design The original code stored vectors as separate objects pointed to by shared_ptr : struct Record { int64_t id ; std :: shared_ptr Vector > vector ; }; This is clean C++. Every record has an id