C++ Compile-Time Sparse Matrices for Linear Algebra and Tracking Applications

Explore compile-time sparse matrices for linear algebra and tracking applications in this CppNow 2023 conference talk. Learn how to incorporate sparseness information into matrix classes at compile time, achieving both memory and runtime efficiency. Discover techniques to move from "No raw loops" to "No run-time loops" and create type-safe library interfaces that enforce correctness and efficiency. Delve into topics such as typeset matrices, runtime representation, matrix multiplication, matrix functions, and inversion. Examine experimental results and gain insights from Daniel Withopf's 20+ years of experience solving real-world problems in robotics and related fields using C++.

Introduction
Recap
Index Tracks
Typeset Matrix
Building Blocks
Typeset Matrices
Examples
Runtime Representation
Matrix Multiplication
C Example
Matrix Functions
Inversion
Evaluate
Experimental Results 2
Experimental Results 3