DeepRec is a high-performance recommendation deep learning framework built on TensorFlow 1.15 with Intel and NVIDIA optimizations. It supports distributed training for trillion-sample recommendation models with over ten trillion parameters. Key features include specialized embedding variables, async/sync distributed training frameworks (Parameter Server), and platform-specific performance optimizations for CPU and GPU.