What is Massively Parallel Processing (MPP)? Definition, Components, Pros & Cons

Massively parallel processing (MPP) is a method that enables large amounts of information to be processed in parallel, allowing faster and more efficient data analysis. MPP systems consist of independent nodes, each with its own operating system, which creates an efficient model for managing vast quantities of data. The main advantage of MPP is its ability to distribute data across multiple processors, allowing for concurrent processing and seamless scalability. However, managing complexity when implementing parallel processing can be challenging, as well as synchronization and fault tolerance issues. Despite these challenges, MPP remains a critical technique in the rapidly evolving fields of artificial intelligence, machine learning, and data science, with applications across various sectors including finance, healthcare, e-commerce, and more.