Extreme Virtual Memory

In today's data-driven world, managing and distributing vast amounts of parallel data is a key challenge. Parallel hierarchical storage systems have become popular because they help to store and manage data in an efficient and organized manner. However, the process of orchestration, often manual and time-consuming, needs a method that can dynamically handle such volumes of parallel data and storage systems. Current approaches to managing and distributing parallel data have shown to be slow and inefficient, often relying on manual processes. These approaches lack the granularity and dynamic capability to partition large arrays of data into subarrays, thus limiting the system's ability to handle large datasets. Furthermore, storing parallel data in a hierarchical manner is often unsystematic and can negatively affect the data retrieval process.

Technology Description

This technology presents a method and computer program product for managing and distributing parallel data across a parallel hierarchical storage system. It works by utilizing a hierarchical map of the parallel data that consists of multiple map objects. Each of these map objects provides intricate details on how to partition a given array of data into multiple subarrays. This data partitioning is outlined by a parent map object of the map object. The technology also clearly describes how to store the parallel data into the computer's parallel storage hierarchy. This unique approach to data organization and distribution differentiates this technology from others. The use of a hierarchical map to manage and control data distribution across storage systems provides tremendous efficiency, scalability, and organization to enable the handling of large data sets in a structured manner. This programmatic approach to data storage ensures the right segregation of data into subarrays, enabling faster data retrieval and processing.