  This paper describes a method for accelerating large scale Artificial Neural
Networks (ANN) training using multi-GPUs by reducing the forward and backward
passes to matrix multiplication. We propose an out-of-core multi-GPU matrix
multiplication and integrate the algorithm with the ANN training. The
experiments demonstrate that our matrix multiplication algorithm achieves
linear speedup on multiple inhomogeneous GPUs. The full paper of this project
can be found at [1].
