  Recent years NLP research has witnessed the record-breaking accuracy
improvement by DNN models. However, power consumption is one of the practical
concerns for deploying NLP systems. Most of the current state-of-the-art
algorithms are implemented on GPUs, which is not power-efficient and the
deployment cost is also very high. On the other hand, CNN Domain Specific
Accelerator (CNN-DSA) has been in mass production providing low-power and low
cost computation power. In this paper, we will implement the Super Characters
method on the CNN-DSA. In addition, we modify the Super Characters method to
utilize the multi-modal data, i.e. text plus tabular data in the CL-Aff
sharedtask.
