Here are some key features of "Cerebrum":

· It saves the current state of the graph of objects or the neural network in the OONKB between user sessions, including the current topology of objects so that it does not require the creation of objects again at the next run.

· It restricts the amount of memory used by the graph of objects or the neural network with larger quantities of class instances. The most frequently used objects are left in the RAM, the others are moved to the physical storage area and are loaded into the RAM upon demand. It unloads the rarely used objects when other objects are loaded to the RAM. The memory amount restriction allows not using the paging file so that it significantly increases the modeling performance of networks with larger quantities of class instances.

· The primary goal of this research is to create a virtual machine supporting free topology object-oriented network with up 2 billons of object instances within one physical storage area. This possibility is provided with implementation of the network object-oriented knowledge database. So that only a few class instances are in the RAM and the most objects are frozen in the file system.