Accelerating Recommender Systems using GPUs
arXiv:1511.02433 · doi:10.1145/2695664.2695850
Abstract
We describe GPU implementations of the matrix recommender algorithms CCD++ and ALS. We compare the processing time and predictive ability of the GPU implementations with existing multi-core versions of the same algorithms. Results on the GPU are better than the results of the multi-core versions (maximum speedup of 14.8).