Ever wondered how websites stay fresh in search results?
Image: Swilsonmc, CC BY-SA 3.0, via Wikimedia Commons
Ever wondered how websites stay fresh in search results?
Imagine you're searching for a new coffee shop in your neighborhood. You want the most popular and highly-rated ones to show up first.
Search engines like Google constantly update their rankings based on what's popular and relevant. They use a method called GQA to prioritize fresh and quality content, which helps them keep the search results up-to-date.
Example
If a new coffee shop opens and gets great reviews, GQA ensures it quickly appears higher in search results.
Remember this
GQA helps search engines show you the most relevant and current results.
Text adapted from Wikipedia, licensed under CC BY-SA 4.0.
paged attention (vLLM) improves serving throughput
Paged attention (vLLM) improves serving throughput by reducing latency through non-contiguous KV-cache pages, enabling faster data retrieval
grouped query attention (GQA) does
GQA shares KV heads across multiple Q heads for efficient parameter usage
KV-cache reduces redundant computation in autoregressive generation
KV-cache stores previously computed outputs to avoid redundant calculations in autoregressive models
CPU cache
L1/L2 cache hierarchy reduces global memory latency
gradient checkpointing trades: recomputes activations to save memory
Gradient checkpointing trades off computation time for memory savings by recomputing activations
Retrieval-augmented generation
RAG enables LLMs to access new information without retraining
Swipe through 100 ML concepts daily
Open Pocket Polymath