Fabien Benetou's PIM | Analysis / OnThePoliticsOfComputations

Principle

If the universe as a whole can be considered as a computational fabric on which matter is organized to allow for computations to be efficiently done (cf Beliefs#B1), then the choice of which to conduct is of fundamental importance.

Those political decisions can be partly witnessed in the history of large computations at the scale of nations (hence the dedicated section on this page) but also through individual decision leveraged by the private sector, typically 2-sided market as explained in InformationRules (still to develop).

Overall allocation of resources is strategical and have fundamental social implication. Computation, despite the famous adage that "knowledge is power", have rarely so far been considered as a resource per se, yet it might be one of the most important one around which others revolve.

This should be use as a part of ways to be politically more efficient, e.g. with VotingIsALearningProcess.

Content

patterns
- mostly only information about the technical specification of the supercomputers but hardly about the computations they ran
- pushing structured matter around (final product)
- pushing information to locally build the final product around
- pre-computations, distributed computation, ...
- handling increasingly large datasets (thus endless race)
  - e.g. manipulating no genome then 1 genome with difficulty then currently doing work with hundreds or whole taxa
- economy of scale, specialization/standardization/distribution
at the political level, who decides how supercomputers will be allocated?
- how does the hierarchy influences such choices?
- how does the underlying ideology influences such choices?
publicly funded classics
- weather
- high energy with no foreseeable exploitation means
- cosmological simulations
- defense
  - note that Agnotology could help distinguish a pattern from the history of declassification
private sector classics
- energy e.g. drilling simulation for B.P., ...
- finance e.g. JP Morgan
- mass end-user information e.g. Google, Facebook, ...
large computations
- what is currently the algorithm currently consuming the most CPU cycles? the most energy? (see also Seedea:Content/Newconcepts#FERD )
  - interesting measure also to compare distributed computations, e.g. comparing BitcoinFabelier with the Top500 or http://wiki.apache.org/hadoop/PoweredBy
  - which algorithms a society has historically invested the most energy on
    - and related hypothesis e.g.
      - Is there a constant shared dedicated to cryptoanalysis?
    - is there a book on the history of large computations? (ideally cryptography and cryptoanalysis included), not the history of calculus, computation or automation but rather on using those tools and methods for a significant period of time thus using a large amount of available resources that would have otherwise been used for other important task (thus being a political question)
    - have humanity overall always spent an equivalent or increasing share of its resources on computations?
    - consider using Seedea:Content/Newconcepts#FERD and as a ratio of total available FERD per period
    - recall Wikipedia:Lewis Fry Richardson#Weather_forecasting in which a room of computers was then filled with people
    - see StructuralInformationAsymmetries#ArchitectureIsomorphisms on patterns in space rather than in time or the impact off Cognition#HistoryOfDominantCognitiveModels regarding what problems are actually trying to be solved
    - see MecaMind
    - consider a DBPedia request using the Purpose in Categories: Supercomputers (added to SemanticWeb#Requests)
  - note that those lists are mainly "just" public research computations, privates (e.g. currently Facebook, Google, etc) not distributed individuals (e.g. Folding@Home, BitCoin, etc) are not included even though individually they may not be relevant, there sum might be significant
    - significant update motivated by WithoutNotesJune11#RIKENK
  - restricted to science?
    - e.g. The Most Highly Cited Paper in Publishing History: Protein Determination by Oliver H. Lowry or in the related field BLAST or FASTA
      - what about Felsenstein's PHYLIP package?
- different programs running and with size of share
  - http://www.top500.org/
    - Green500 a ranking of the most energy-efficient supercomputers in the world
    - Graph500.org
- In graphics: Supercomputing superpowers, BBC News May 2010
  - including treemap by applications
- history of the largest computations
  - simulating atomic bombs, predicting weather, breaking cryptographic code, proteome, ...
  - Wikipedia:Military simulation
  - Grid Observatory traces
  - to put in perspective against Wikipedia:World energy consumption
- consider the link with the evolution of Mathematics#ComplexityTheory and what is calculable, what is not
  - inspired by WithoutNotesAugust11#ScottAaronson
- In graphics: Supercomputing superpowers, BBC News May 2010
military battle
- what was computed before? what outcome did it result it?
  - map, estimation of enemy resource, ...
note that the energy required to run might not be the most important, cf WithoutNotesSeptember11#WatsonEnergyConsumptionEstimate which would seem to show that it is actually potentially negligible!

Financing such a study

How many "rich" history inclined geeks Financial#crowdfunding principle to the point of donating?
- note that those crowd-funding platforms have a different distribution population, e.g. Flattr might have more geeks than KickStarter yet their income might be lower, etc
- see existing non-fiction examples http://www.kickstarter.com/discover/categories/nonfiction
potential bonus for helpers
- shipped paper copy from Lulu.com
- shipped poster of a summing-up infographic
- dedicated visit of a significant place (e.g. Computer History Museum)

On The Politics Of Computations {Analysis}

Principle

Content

Financing such a study

Inspired by

See also