Optimization for Classical Machine Learning Problems on the GPU

GPU, the same code needs 5.2 seconds in total while 4.6 seconds Training classical machine learning models typically means are spent in the Cauchy point subroutine. It can be seen solving an optimization problem. Hence, the design and implementation that while all other parts of the L-BFGS-B algorithm can of solvers for training these models has been be parallelized nicely on a GPU, the inherently sequential and still is an active research topic. While the use of GPUs Cauchy point computation does not and instead, dominates is standard in training deep learning models, most solvers the computation time on the GPU; as a result, the L-BFGS-B for classical machine learning problems still target CPUs.