Source-to-source automatic differentiation of OpenMP parallel loops
J Hückelheim, L Hascoët - ACM Transactions on Mathematical Software …, 2022 - dl.acm.org
This article presents our work toward correct and efficient automatic differentiation of
OpenMP parallel worksharing loops in forward and reverse mode. Automatic differentiation …
OpenMP parallel worksharing loops in forward and reverse mode. Automatic differentiation …
Automatic differentiation of parallel loops with formal methods
J Hückelheim, L Hascoët - … of the 51st International Conference on …, 2022 - dl.acm.org
This paper presents a novel combination of reverse mode automatic differentiation and
formal methods, to enable efficient differentiation of (or backpropagation through) shared …
formal methods, to enable efficient differentiation of (or backpropagation through) shared …
Automatic differentiation of C++ codes on emerging manycore architectures with sacado
Automatic differentiation (AD) is a well-known technique for evaluating analytic derivatives of
calculations implemented on a computer, with numerous software tools available for …
calculations implemented on a computer, with numerous software tools available for …
Towards reverse mode automatic differentiation of Kokkos-based codes
Derivative computation is a key component of optimization, sensitivity analysis, uncertainty
quantification, and the solving of nonlinear problems. Automatic differentiation (AD) is a …
quantification, and the solving of nonlinear problems. Automatic differentiation (AD) is a …