Understand tensor, pipeline, and expert parallelism through small worked examples, GPU placement diagrams, and a clear explanation of what each GPU computes and communicates.

A visual introduction to Mixture of Experts: follow a token through routing, blend expert outputs, and understand the compute, memory, and communication tradeoffs.

How CPUs and GPUs cooperate, how grids, blocks, warps, and tiles execute, and why memory movement matters for LLM inference.

You send a prompt to an LLM endpoint. The server spends a moment working without returning text, then words begin to stream. The first word can take much longer than the gaps between later words. I...

Part 2 of the Lucene internals series. Part 1 — Deep Dive into Apache Lucene’s Core: From In-Memory Buffers to Commits followed documents into an index. This one follows a query out of it. Part 1 ...

Apache Lucene is a highly optimized, full-featured search engine library written in Java. While developers frequently interact with its high-level objects like IndexWriter and Document, what happen...

Introduction Modern distributed systems often replicate data across nodes for availability and low latency. However, concurrent updates on different replicas without coordination can lead to confl...