Design and implementation of DeepDSL: A DSL for deep learning

In this work, we introduce DeepDSL, a domain specific language (DSL) embedded in Scala, that compiles DL networks encoded with DeepDSL to efficient, compact, and portable Java source programs for DL training and inference. DeepDSL represents DL networks as abstract tensor functions, performs symbolic gradient derivations to generate Intermediate Representation (IR), optimizes the IR expressions, and translates the optimized IR expressions to Java code that runs on GPU without additional dependencies other than the necessary GPU libraries and the related invocation interfaces: a small set of JNI (Java Native Interface) wrappers. Our experiments show DeepDSL outperforms existing tools in several benchmark programs adopted from the current mainstream Deep Neural Networks (DNNs).