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cam5 FV dynamical core

santos

Member
spatial non-coherence between data stored on different compute nodesI should point out that this is something of an understatement; the most common load balancing strategies try to deliberately minimize spatial coherence, in order to improve the chances that each task has a mix of columns from "expensive" regions and those from "cheap" regions. E.g. day is more expensive than night, cloudy is more expensive than clear sky.
 

santos

Member
spatial non-coherence between data stored on different compute nodesI should point out that this is something of an understatement; the most common load balancing strategies try to deliberately minimize spatial coherence, in order to improve the chances that each task has a mix of columns from "expensive" regions and those from "cheap" regions. E.g. day is more expensive than night, cloudy is more expensive than clear sky.
 

santos

Member
spatial non-coherence between data stored on different compute nodesI should point out that this is something of an understatement; the most common load balancing strategies try to deliberately minimize spatial coherence, in order to improve the chances that each task has a mix of columns from "expensive" regions and those from "cheap" regions. E.g. day is more expensive than night, cloudy is more expensive than clear sky.
 

santos

Member
spatial non-coherence between data stored on different compute nodesI should point out that this is something of an understatement; the most common load balancing strategies try to deliberately minimize spatial coherence, in order to improve the chances that each task has a mix of columns from "expensive" regions and those from "cheap" regions. E.g. day is more expensive than night, cloudy is more expensive than clear sky.
 

santos

Member
spatial non-coherence between data stored on different compute nodesI should point out that this is something of an understatement; the most common load balancing strategies try to deliberately minimize spatial coherence, in order to improve the chances that each task has a mix of columns from "expensive" regions and those from "cheap" regions. E.g. day is more expensive than night, cloudy is more expensive than clear sky.
 
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