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kernelpopper11

Kernel Eleven is looking for contributors for theoretical debate and code implementations.

Kernel Popping is an interesting area of work. Shannon set the limits on how much a signal could be compressed using traditional means known as the entropy of information. The entropy of information states that a digital chunk of information can be compressed until there are an even number of ones and zeros. Of course this isn't true, if the chunk consisted of a series of 010101... and it was ran through a compression scheme which compressed 01->1 than the output would be a series of ones, 111... which by it's own entropy would contain no information (could be reduced to nothing).

We would like to take a chunk of information and expand it to a point were it has no information and then squash it down. Only with parallel programming we are dealing with processes instead of information. We take a long sequential process and expand it into a larger process that can be broken up and ran in parallel.

The barrier of the entropy of information is commonly overcome with mp4 type compression schemes by exploiting redundancies. This factor of how much redundancy exists in a block of information will be named here as the enthalpy of information. Any block of information can be expanded and compressed into nothing, but to pass information to a receiver on how to reconstruct that signal (from nothing) may or may not contain less bits than the original block of information.

With processes a similar scheme is devised. Anything a computer can do can be related to some form of process. One commonly studied type of process is the finite state machine. Finite state machines are ideal because they are stable, they clearly define every state the process can be in and how navigation between states is accomplished. Any process can be expanded into a finite state machine "theoretically" but to do so in real time isn't realizable with modern day computing devices (yet:)); However, we can define a finite number of processes contained in a Kernel, and often do as there are only a handful of assembly line instructions.

That is all for now, if you would like to join into the conversation please contact joem.walter@gmail.com

Stay tuned for py-calculus and vector space versus <i\[>the Matrix, <]#></i\[>

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