DROPOUT FOR ACCELERATED DEEP LEARNING IN HETEROGENEOUS ARCHITECTURES

A heterogeneous processing system includes at least one central processing unit (CPU) core and at least one graphics processing unit (GPU) core. The heterogeneous processing system is configured to compute an activation for each one of a plurality of neurons for a first network layer of a neural network. The heterogeneous processing system randomly drops a first subset of the plurality of neurons for the first network layer and keeps a second subset of the plurality of neurons for the first network layer. Activation for each one of the second subset of the plurality of neurons is forwarded to the CPU core and coalesced to generate a set of coalesced activation sub-matrices.