**Massively parallel non-linear
computation**

The surface depicts tolerance rates of 46 * 46 solutions.
The central plain is occupied by isolated CA in which delivery was not
activated and change state was not effective. Even in their isolated
state they accumulate tolerance at varying rates. Below
this plain tolerance accumulation rate declines. (v.
Tolerance accumulation. We may now ask
what combination of CA states accumulates tolerance fastest?

Eleven
out of 46 CA exhibited a tolerance rate maximum. In the rest, tolerance was constant,
yet varied between CA. The set of maxima is : {1,43},{8,14}, {10,8},
{14,8}, {18,28},{22,18},{26,10}, {31,10},{35,33},{39,30},{43,42}}. The first number is the CA-0 state initiating
delivery activation. The second is the CA-0 state initiating state change. CA-tolerances of this set
were summed up and added to the tolerances (at any coordinate) of the
other CA. The overall mean daily tolerance gain above the isolated state
(= 9.79) was 14.60 units. When the tolerances were summed up along the
consecutive CA-0 exchange states the overall mean daily tolerance gain
was 4.47.

**Streaming processes**

This surface may be generated in parallel. The stem
CA-0 plants 46 zygotes of transient processes, When they mature it activates
its two functions, delivery activation and change state, and the set
starts delivering resources into the environment. In each CA cells are
born and die. The change state function determines the
CA period of 46, and when it starts. The surface depicts the average
daily tolerance accumulation rate during steady state (homeorhesis).
** ****It depicts a rate!**
The overall tolerance of the CA system continually
rises.

Additional reading:
Streaming organism

**Massively parallel non-linear
computation**

The surface depicts a parallel computation, and the question is how
to chose the couplets so as to **maximize tolerance gain rate **by
the CA set. We are dealing with different combinations of couplets and ask whose tolerance accumulation
rate is the fastest? The solution
was given above.

The future objective is to let the 47 CA proliferon
find the answer by itself. In other words let it evolve towards its
most optimal solution. At this stage of my research
the proliferon exhibits **one WOB property,
it
always settles at a solution**. The aim
here is to equip it with another WOB property, **the
capability (knowledge) to optimize**. The objective here is to find
a strategy which will guide the proliferon to settle at the most optimal
solution with the fastest tolerance accumulation rate.