  The increasing application of deep learning technology drives the need for an
efficient parallel computing architecture for Convolutional Neural Networks
(CNNs). A significant challenge faced when designing a many-core CNN
accelerator is to handle the data movement between the processing elements. The
CNN workload introduces many-to-one traffic in addition to one-to-one and
one-to-many traffic. As the de-facto standard for on-chip communication,
Network-on-Chip (NoC) can support various unicast and multicast traffic. For
many-to-one traffic, repetitive unicast is employed which is not an efficient
way. In this paper, we propose to use the gather packet on mesh-based NoCs
employing output stationary systolic array in support of many-to-one traffic.
The gather packet will collect the data from the intermediate nodes eventually
leading to the destination efficiently. This method is evaluated using the
traffic traces generated from the convolution layer of AlexNet and VGG-16 with
improvement in the latency and power than the repetitive unicast method.
