Machine Learning Mastery·
This article is divided into four parts; they are: • The Problem with Static Batching • Code Example of Static Batching • Continuous Batching: Dynamic Scheduling and Ragged Batching • Full Implementation The simplest way to serve multiple requests together is to use static batching, by grouping them into fixed-size batches and processing each batch together.
Read full articleA comprehensive guide to optimizing LLM inference by eliminating padding overhead with hardware-aware sequence packing. The post I Built a C++ Backend So My GPU Would Stop Eating Air appeared first on Towards Data Science.
Top 10 KV Cache Compression Techniques for LLM Inference: Reducing Memory Overhead Across Eviction, Quantization, and Low-Rank Methods The post Top 10 KV Cache Compression Techniques for LLM Inference: Reducing Memory Overhead Across Eviction, Quantization, and Low-Rank Methods appeared first on MarkTechPost.
