Parallel generalized tensor multiplication

Tensor factorization is a frequently used modelling tool in problems involving large amounts of n-way data. Probabilistic Latent Tensor Factorization framework provides a probabilistic approach to solve the tensor factorization problem. The iterative algorithms use generalized tensor multiplication operations involving large amounts of arithmetic operations with similar structures. This work shows the performance improvements achieved by performing the independent operations on a graphical processing unit (GPU).