Is All-Flash Storage Needed for Deep Learning?

Organizations building deep learning data pipelines may struggle with their accelerated I/O needs, and whenever I/O is the question, the usual answer is "throw flash/SSD at it." Certainly expensive all-flash storage arrays are highly beneficial for line-of-business applications (and to storage vendors' sales). But DL applications and workflows are inherently different from typical file-based workloads, and should not be architected the same way. Let's start by looking inside those servers. DL uses several hidden layers of neural networks, such as convolutional (CNN), long short-term memory (LTSM), and/or recurrent (RNN).