Bridging the Chasm: A Deep Dive into Machine Learning Compilation with TVM and XLA for Hardware-Specific Optimization

The Imperative for Machine Learning Compilation From Development to Deployment: The Core Challenge Machine Learning Compilation (MLC) represents the critical technological bridge that transforms a machine learning model from its Read More …

A System-Level Analysis of Continuous Batching for High-Throughput Large Language Model (LLM) Inference

The Throughput Imperative in LLM Serving The deployment of Large Language Models (LLMs) in production environments has shifted the primary engineering challenge from model training to efficient, scalable inference. While Read More …

A Comprehensive Analysis of Modern LLMs Inference Optimization Techniques: From Model Compression to System-Level Acceleration

The Anatomy of LLM Inference and Its Intrinsic Bottlenecks The deployment of Large Language Models (LLMs) in production environments has shifted the focus of the machine learning community from training-centric Read More …