In “Machine Mentality: Instructions Per Cycle & Vectors, Why Databases and LLMs Care,” we peel back the layers of modern compute architectures to reveal how low-level encoding and vectorized execution, driven by Instructions Per Cycle (IPC) and Single Instruction, Multiple Data, pipelines, influence both database, data warehouse and large language models (LLM).

What You’ll Learn

** Encoding Strategies & Data Ordering
Explore how Offset, Dictionary, Bit-Packing, Run-Length, and Delta encodings interact with cache lines and prefetchers—and why ordering your data can make or break performance.

** Instruction Throughput & Vectorization
Understand how SIMD‐driven operators leverage wide registers to execute multiple elements per cycle, and why maximizing IPC matters for both query engines and transformer inference.

** Tokenization
Learn how the core of every transformer block consists of a small handful of linear algebra routines, and how using SIMD makes it possible to achieve those tokens-per-second speeds.