Difference between revisions of "CSC352 DT's Class Notes 2013"

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(DFT Class Notes for CSC352)
 
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__TOC__
 
__TOC__
  
==Papers==
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<br />
* Landscape of parallel computing research: a view from berkeley
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<center>
** General introduction to world of // computing in 2006
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'''PLEASE SEE [[CSC352_2017_DT%27s_Notes| THE 2017 NOTES PAGE FOR MORE INFO]]'''
** old wisdom/new wisdom ==> world of // computing is changing
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</center>
** moore's law
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<br />
:::"Key to this approach is a layer of libraries and programming frameworks centered on the 13 computational bottlenecks ("dwarfs") that we identified in the original Berkeley View report. "
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==Threads==
** Page 7: we have been concentrating on massively parallel architectures, but this may apply to new forms of parallelism
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* good example with multiple ping processes: [http://www.wellho.net/solutions/python-python-threads-a-first-example.html]
** Page 7: good match between scientific // approaches and current parallel (non scientific) domains
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* multi-core not used by python [http://smoothspan.wordpress.com/2007/09/14/guido-is-right-to-leave-the-gil-in-python-not-for-multicore-but-for-utility-computing/]
** Page 7: 7 Dwarfs
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*** ==> question: what's a dwarf? (google berkeley + dwarf)
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===Programs===
*** high level of abstraction
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* [[NQueens.py | NQueens.py]]
** Page 11: 3 new areas for adoption as dwarf?
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* [[threadedNQueens.py | threadedNQueens.py ]]
*** machine learning
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* [[classExample1.py | classExample1.py ]]
*** database software
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* [[classExample2.py | classExample2.py ]]
**** Page 12: map-reduce
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* [[classExample3.py | classExample3.py ]]
*** computer graphics
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* [[serialPing.py | serialPing.py ]]
** Page 14: introduces 6 new dwarfs
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* [[threadedPing.py | threadedPing.py ]]
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* [[searchKeywordsRetrieveEtexts.py | searchKeywordsRetrieveEtexts.py ]]
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* [[threadedSearchKeywordRetrieveEtexts.py | threadedSearchKeywordRetrieveEtexts.py ]]
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===Setting up documents and swish-e===
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(Note: there are 2 other alternatives: sphinx and zend-lucene.  Sphinx requires data in xml form or in mysql database)
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* all operations on xgridmac
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* downloaded &amp; installed swish-e.  Install dir is ~thiebaut/research/swish-e/
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* downloaded &amp; installed www.etext.org in http://xgridmac.dyndns.org/~thiebaut/www_etext_org/
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* swish-e index stored in ~thiebaut/Site/swish-e
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* added [[www.etext.org_swish-e.php | swishe.php]] in ~thiebaut/Site/swish-e/
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* test:
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<code><pre>
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  cd
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  cd Site/swish-e
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  php swishe.php search=love
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  ...
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<br>
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<br>rank:  20
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<br>score:  809
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<br>url:    http://xgridmac.dyndns.org/~thiebaut/www_etext_org/Religious_357/Polyamory/Keys2LovingUnity.html
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<br>link:  <a href="http://xgridmac.dyndns.org/~thiebaut/www_etext_org/Religious_357/Polyamory/Keys2LovingUnity.html">link</a>
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<br>file:  Keys2LovingUnity.html
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<br>offset: 47813
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<br>
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</pre></code>
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* test on Web at url http://xgridmac.dyndns.org/~thiebaut/swish-e/swishe.php?search=love
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* test with delay: http://xgridmac.dyndns.org/~thiebaut/swish-e/swishe.php?delay=20&search='local%20government'
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Where delay is number of 1/10s of a second to wait.  This is a bound as the true delay is random between 0.1 sec and the integer specified times 1/10 seconds.)
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==Project==
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;Project 1:
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:Threading in Python: given two lists of keywords, List1 and List2, retrieve docs from a site (xgridmac.dyndns.org, yahoo, google) that respond/match List1.  Filter the docs received and keep only those that contain most of the words in List2.
  
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;Project 2:
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:XGrid: process a gzip xml dump of wikipedia and break it up into individual pages (9 million or so of them)!
  
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;Project 3:
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:Map-Reduce: process wikipedia pages and create an index of words and their associated categories
  
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==Papers==
  
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[[CSC352 Notes on A View From Berkeley| Notes]] on a View from Berkeley paper
  
  
 
</onlydft>
 
</onlydft>
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[[Category:CSC352]][[Category:Class Notes]]

Latest revision as of 15:01, 7 December 2016

DFT Class Notes for CSC352


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