Shared Memory Parallelization of MTTKRP for Dense Tensors

Understand

The matricized-tensor times Khatri-Rao product (MTTKRP) is the computational bottleneck for algorithms computing CP decompositions of tensors.

• In this paper, we develop shared-memory parallel algorithms for MTTKRP involving dense tensors.
• The algorithms cast nearly all of the computation as matrix operations in order to use optimized BLAS subroutines, and they avoid reordering tensor entries in memory.
• We benchmark sequential and parallel performance of our implementations, demonstrating high sequential performance and efficient parallel scaling.