vector processing

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.

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.

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.

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.

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.

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.

Bret Victor's 2013 MIT Media Lab talk argues that the media we think with determine which thoughts are possible. He demos new representations for scientific papers, circuits, filters and signal processing.

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.

Joscha Bach's 31c3 talk argues that the mind should be understood as an information-processing system and that even the physical universe can be seen as computational. It tours the philosophy underlying artificial intelligence and cognitive science.

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.