vector monitors

Jiahao Chen's JuliaCon 2017 talk argues that vector transposes should be taken seriously in type systems and linear algebra libraries. It explains why treating vectors as matrices causes trouble in languages.

Freya Holmer's Dutch Game Day 2023 talk asking why vectors can't be multiplied, building from complex numbers to a single axiom and arriving at geometric algebra, quaternions and multivectors.

David Heinemeier Hansson explains what he learned about indoor air quality after his new house made his family sick. He covers CO2, VOCs, off-gassing, HVAC and ventilation, and cognitive effects, presented at a Basecamp meetup.

Seymour Cray's only surviving recorded talk, introducing the Cray-1 supercomputer in 1976. He describes the machine's design, including its vector architecture and cooling through the frame.

Jim Keller's talk at the 2020 Scaled Machine Learning conference on Moore's Law in the age of AI chips. He compares scalar, vector and GPU-style parallel approaches to computation.

David Ditzel of Esperanto Technologies presents their massively parallel, energy-efficient RISC-V processors at the 7th RISC-V Workshop in 2017. It covers the high-performance many-core design aimed at machine learning.

Andrew Adams, a Halide developer, presents the Halide language for image processing and tensor computation. The talk explains the separation of algorithm from schedule with illustrated examples of parallelism, locality and redundancy tradeoffs.

Edward Kmett's 2013 talk at Prezi in Budapest on succinct data structures, which store data in close to the information-theoretic minimum space while supporting fast queries. It ties together the research and walks through his Haskell succinct library.

Steven Wittens' JSConf US 2013 talk on drawing with WebGL, using animated visuals to walk through vectors, matrices and the rendering pipeline. Despite the title, it works as a visual primer on the linear algebra behind 3D graphics.

Johann Korndorfer's NVScene 2015 talk on building content with signed distance functions. It focuses on patterns that make SDF modelling more structured, arguing that SDFs capture a shape's essence like vector graphics do compared with polygons or voxels.

Daniel Lemire's QCon talk on how simdjson parses gigabytes of JSON per second. It covers SIMD vectorization, branch prediction and the lessons learned building a fast parser.