JuliaCon 2020 (times are in UTC)

This talk will focus on the library LoopVectorization, providing an overview of how the library represents loops, and how this representation is used alongside cost modeling to pick an efficient vectorization strategy, and how it can be used for defining loops for an autodiff reverse pass.

This talk will present how basic operations on vectors, like summation and dot products, can be made more accurate with respect to Floating-Point arithmetic by using compensated algorithms. The proposed implementation is available in the AccurateArithmetic.jl package, and leverages SIMD instructions in order to achieve high performance on modern hardware architectures.