Linux Computational Caching
Despite decades of research computer systems are no more “intelligent” today than they were when they were first constructed. That is to say they do not systemically incorporate the ability to exploit their past to improve their current or future operation.
In this speculative work we are attempting to explore a biologically motivated conjecture on how memory of past computing can be stored and recalled to automatically improve a system’s behavior. Building on our prior work our goal is to combine machine learning mechanisms with a representation of a virtual machines execution as images of a movie. The goal is to construct a distributed virtual machine runtime, based on LINUX KVM, that extracts such movies to create a form of associate cache that is used to recognize and recall information from past execution. This recalled information is then used to synthesize information that is specific to the current computation and permits its acceleration. The first steps, however, are to create and demonstrate the ability to extract and recognize “useful” patterns using existing machine learning techniques.
Principal Investigator: Jonathan Appavoo