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In this fourth article of the “Less Slow” series, I’m accelerating Unum’s open-source Vector Search primitives used by some great database and cloud providers to replace Meta’s FAISS and scale-up search in their products. This time, our focus is on the most frequent operation for these tasks - computing the the Cosine Similarity/Distance between two vectors. It’s so common, even doubling it’s performance can have a noticeable impact on applications economics.

Xeon cpusUnum usearchUnum uformJensen shannonArchitectures software developerVector searchMachine learningInformation retrievalGen intel xeonSapphire rapidsBetween pythonQuantization aware trainingPrecision supportBasic linear algebra subroutinesCosine similarityGoogle benchmark