Caching is as fundamental to computing as arrays, symbols, or strings. Various layers of caching throughout the stack hold instructions from memory while pending on your CPU. They enable you to reload the page quickly and without re-authenticating, should you navigate away. They also dramatically decrease application workloads, and increase throughput by not re-running the same queries repeatedly.
]]>Recommendation models have progressed rapidly in recent years due to advances in deep learning and the use of vector embeddings. The growing complexity of these models demands robust systems to support them, which can be challenging to deploy and maintain in production. In the paper Monolith: Real Time Recommendation System With Collisionless Embedding Table, ByteDance details how they built…
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