Machine Learning Workload and GPGPU NUMA Node Locality - frankdenneman.nl

Oversimplified ML is "using data to answer questions." With traditional programming models, you create "rules" by using the programming language and apply these rules to the input to get output (results) (output). With ML training, you provide input and the output to train the program to create rules. This creates a predictive model that can be used to analyze previously unseen data to provide accurate answers. The key component of the entire ML process is data.