Author: Matthew Hull
Date: 16:13:38 03/02/05
Go up one level in this thread
On March 02, 2005 at 18:59:18, Axel Schumacher wrote: >Hi all, >I have two question regarding the storage requirements for information; I hope >somebody can help me with answering them. Please excuse if my questions are >stupid. > >1. For each data-point (e.g. let's say the position of a pawn on the chessboard) >one requires 1 bit (either 0 or 1). Right? However, the information does not >include where the pawn is located. So, how much data has to be stored to >describe e.g. the position of a pawn? In bit-board programs, all paws of a color with their locations can be stored in in one 64 bit word. Analysis on the pawn struction can be done with bit masks using a single instruction on a 64 bit machine or two instructions on 32 bit (in principle). > >2. How much calculation power is need to calculate a certain amount of data? I >know, this this may sound a little bit abstract and, of course, it depends on >the time-factor. But let's you have 1 terabyte of data in a data-spreadsheet. >What calculation-power (e.g. amount of average desktop computers) is needed to >make simple algebraic calculations with such a data-table? There are alogorithms for matrix operations. These can be very fast on processors with vector facilities. > >I hope sombody can help me with this. >I'm writing a paper in which I make an analogy from biostatistic calculations >with chess and calculations in chess (e.g. from a typical chess program). I know very little about this, but it seems the protein-folding people are doing something similar. Check them out here: http://folding.stanford.edu/ >The >reason for this is to examplify how biological data can be stored and how it can >be interpreted. In this special case we are dealing with 3.6 x 10^14 raw data >points deriving from chemical modifications in the human genome (so called >epigenetics). For example, is a specific DNA base in the genome methylayted or >not we have the state 0 or 1 again (plus this data has to be referenced). These >information-units could interact in an infinite number of ways, so that it seems >that it impossible to make sense out of them. However, IMHO, the analogy with >the game of chess exemplifies that it still should be feasible to approach the >problem of complex genetic information. In chess, a small number of rules can >generate a huge number of board configurations (states), which are analogous to >the configurations of molecules obeying physiological laws. Chess is known to >have also an infinite number of possible combinations in its play but in theory >the number is finite, since specific positions are impossible, as not all >(epi)genetic factors can be found in all functional working combinations. E.g. >it is said that in chess ‘merely’ ~10^43 to 10^50 states (positions) are needed >to to describe the state (or the game) of the system. Out of these subsets of >possible states, patterns can be established and calculated. So it is not >necessary, to know every possible state. It is obvious that pure reductionism, >the theory that all complex systems can be completely understood in terms of >their components, may not be a fully fruitful approach. >Yet, recent development in the field of complexity (e.g. statistical mechanics) >has come up with alternative statistical approaches. It considers the average >behaviour of a large number of components rather than the behaviour of any >individual component, drawing heavily on the laws of probability, and aims to >predict and explain the measurable properties of macroscopic systems on the >basis of the properties and behaviour of their microscopic constituents. Chess >programs don't rely on brute force alone anymore. Maybe such 'pattern >recognition' or reduction of legal states can help in making sense out of >complex data. >Your opinion? Answers to the qustions? :-) > >Axel
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