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{"algorithm":{"algorithm":{"currentFile":{"count":1,"lastUpdated":1736360369637}}},"computing":{"computing":{"currentFile":{"count":2,"lastUpdated":1736427522780}}},"tasks":{"tasks":{"currentFile":{"count":1,"lastUpdated":1736428160890}}},"parallelization":{"parallelization":{"currentFile":{"count":1,"lastUpdated":1736428239757}}},"Implicit":{"Implicit":{"currentFile":{"count":1,"lastUpdated":1736429811730}}},"Semi-implicit":{"Semi-implicit":{"currentFile":{"count":1,"lastUpdated":1736429857427}}},"Agent":{"Agent":{"currentFile":{"count":1,"lastUpdated":1736527234430}}},"Agents":{"Agents":{"currentFile":{"count":3,"lastUpdated":1736528265726}}},"actions":{"actions":{"currentFile":{"count":1,"lastUpdated":1736527553391}}},"successful":{"successful":{"currentFile":{"count":1,"lastUpdated":1736527687166}}},"agents":{"agents":{"currentFile":{"count":3,"lastUpdated":1736529446424}}},"environment":{"environment":{"currentFile":{"count":2,"lastUpdated":1736528276442}}},"actuators":{"actuators":{"currentFile":{"count":1,"lastUpdated":1736528278631}}},"Sensors":{"Sensors":{"currentFile":{"count":1,"lastUpdated":1736528280975}}},"state":{"state":{"currentFile":{"count":1,"lastUpdated":1736529437831}}},"types":{"types":{"currentFile":{"count":1,"lastUpdated":1736529458373}}},"Operatiosn":{"Operatiosn":{"currentFile":{"count":1,"lastUpdated":1736530551849}}},"Algorithms":{"Algorithms":{"currentFile":{"count":1,"lastUpdated":1736792441945}}},"Problem":{"Problem":{"currentFile":{"count":1,"lastUpdated":1736792504102}}},"parallel":{"parallel":{"currentFile":{"count":2,"lastUpdated":1736858881146}}},"processing":{"processing":{"currentFile":{"count":1,"lastUpdated":1736858379041}}},"resources":{"resources":{"currentFile":{"count":1,"lastUpdated":1736858873851}}},"Reduce":{"Reduce":{"currentFile":{"count":1,"lastUpdated":1736859169038}}}}
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{"algorithm":{"algorithm":{"currentFile":{"count":1,"lastUpdated":1736360369637}}},"computing":{"computing":{"currentFile":{"count":2,"lastUpdated":1736427522780}}},"tasks":{"tasks":{"currentFile":{"count":1,"lastUpdated":1736428160890}}},"parallelization":{"parallelization":{"currentFile":{"count":1,"lastUpdated":1736428239757}}},"Implicit":{"Implicit":{"currentFile":{"count":1,"lastUpdated":1736429811730}}},"Semi-implicit":{"Semi-implicit":{"currentFile":{"count":1,"lastUpdated":1736429857427}}},"Agent":{"Agent":{"currentFile":{"count":1,"lastUpdated":1736527234430}}},"Agents":{"Agents":{"currentFile":{"count":3,"lastUpdated":1736528265726}}},"actions":{"actions":{"currentFile":{"count":1,"lastUpdated":1736527553391}}},"successful":{"successful":{"currentFile":{"count":1,"lastUpdated":1736527687166}}},"agents":{"agents":{"currentFile":{"count":3,"lastUpdated":1736529446424}}},"environment":{"environment":{"currentFile":{"count":2,"lastUpdated":1736528276442}}},"actuators":{"actuators":{"currentFile":{"count":1,"lastUpdated":1736528278631}}},"Sensors":{"Sensors":{"currentFile":{"count":1,"lastUpdated":1736528280975}}},"state":{"state":{"currentFile":{"count":1,"lastUpdated":1736529437831}}},"types":{"types":{"currentFile":{"count":1,"lastUpdated":1736529458373}}},"Operatiosn":{"Operatiosn":{"currentFile":{"count":1,"lastUpdated":1736530551849}}},"Algorithms":{"Algorithms":{"currentFile":{"count":1,"lastUpdated":1736792441945}}},"Problem":{"Problem":{"currentFile":{"count":1,"lastUpdated":1736792504102}}},"parallel":{"parallel":{"currentFile":{"count":2,"lastUpdated":1736858881146}}},"processing":{"processing":{"currentFile":{"count":1,"lastUpdated":1736858379041}}},"resources":{"resources":{"currentFile":{"count":1,"lastUpdated":1736858873851}}},"Reduce":{"Reduce":{"currentFile":{"count":1,"lastUpdated":1736859169038}}},"minimized":{"minimized":{"currentFile":{"count":1,"lastUpdated":1736860208884}}},"oriented":{"oriented":{"currentFile":{"count":1,"lastUpdated":1736860250593}}},"Memory":{"Memory":{"currentFile":{"count":1,"lastUpdated":1736860492193}}}}
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@ -32,3 +32,10 @@ The time and process requirements of each task may differ, which introduces the
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Embarrassingly parallel: Problem which can be parallelized by simply allocating more hardware resources.
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Embarrassingly parallel: Problem which can be parallelized by simply allocating more hardware resources.
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### Word Count with Map Reduce
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### Word Count with Map Reduce
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Each thread can map a document of a word to a count, which after completion can be reduced to one map from each thread, usually with a parallel hash table.
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Each thread can map a document of a word to a count, which after completion can be reduced to one map from each thread, usually with a parallel hash table.
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## Memory Schemes
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Multicore systems, ones which have the ability to compute multiple tasks at the same time in a shared memory environment are often latency oriented, with the start and stop time of results being minimized, as well as the time between results is minimized.
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Manycore systems, ones which are often a large number of cores tasked with the same problem, in a shared memory environment are often throughput oriented, with the amount computation being higher amortized over a period of time, or focusing on longer running tasks/computation.
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### Distributed Memory
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The tasks are not within the same memory space, and do not share memory addresses, and there is no need for communication between nodes
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