You are employed at a biotech startup focused on experimenting with deep learning ML models inspired by biological organisms. Your team frequently engages in early-stage experiments involving novel ML model architectures and develops custom TensorFlow operations in C++. Training your models involves large datasets and substantial batch sizes, with a typical batch comprising 1024 examples, each approximately 1 MB in size. Furthermore, the average size of a network, including all weights and embeddings, is 20 GB. In light of these requirements, which hardware should you select for your models?