Attention-Mechanisms

A visual representation of compressed KV cache attention with memory tiers

Build a Memory-Compressed Attention Engine with KV Caching from Scratch

A hands-on build guide for implementing a memory-compressed attention engine with key-value caching from scratch in Python. Includes architecture diagrams, production-grade code, and a roadmap to senior-level extensions.

A visualization of ring attention with tokens flowing in a circular topology across GPU devices.

Build a Ring Attention Engine: A Hands-On Guide for Signal-Level Systems Engineers

A hands-on build guide for implementing ring attention — the technique behind near-infinite context transformers — as a portfolio project that signals deep distributed systems and ML engineering skill to hiring managers.

Code on a terminal screen representing a semantic cache

Building an Attention-Driven Semantic Caching Layer for LLM APIs

Learn how to build a production-grade semantic caching layer for LLM APIs using custom attention-based scoring, demonstrating critical infrastructure skills.

Diagram of a streaming attention engine processing tokens through a sliding window with KV-cache reuse.

Building a Streaming Sliding-Window Attention Engine in Pure Python

A portfolio-grade systems project that demystifies LLM inference by implementing streaming sliding-window attention, prefix KV-cache reuse, and dynamic context eviction from scratch in pure Python.

Stylized diagram of a GPU die with attention tile matrices overlaid in cyan and amber.

Optimizing Triton Kernels for Custom Attention Patterns on H100 GPUs

A working engineer’s guide to squeezing the H100 with custom Triton kernels: tile sizing, swizzle patterns, pipeline stages, and the warp-specialization tricks that make non-vanilla attention fly.