By David Peleg
This quantity provides the locality-sensitive method of allotted community algorithms-the usage of locality to simplify regulate buildings and algorithms and decrease their bills. the writer starts with an introductory exposition of allotted community algorithms targeting themes that illustrate the function of locality in dispensed algorithmic ideas. He then introduces locality-preserving community representations and describes sequential and dispensed concepts for his or her building. eventually, the applicability of the locality-sensitive technique is confirmed via a number of functions.
Distributed Computing: A Locality-Sensitive technique is the one ebook that offers an intensive exposition of community spanners and different locality-preserving community representations reminiscent of sparse covers and walls. The e-book comes in handy for machine scientists drawn to dispensed computing, electric engineers drawn to community architectures and protocols, and for discrete mathematicians and graph theorists.
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This quantity provides the locality-sensitive method of dispensed community algorithms-the usage of locality to simplify keep an eye on constructions and algorithms and decrease their bills. the writer starts with an introductory exposition of allotted community algorithms concentrating on subject matters that illustrate the function of locality in allotted algorithmic suggestions.
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Additional resources for Distributed computing: a locality-sensitive approach
The Thread object creates a series of counters for each thread on the system. Modern systems can handle millions of threads, so when you multiply this by the number of counters in the Thread object, you can get a lot of counters being logged. Technically speaking, when Performance Monitor collects counter data, it collects all counters and instances of a counter object and then filters it to the specified counters and instances if needed. This means that it requires less processor overhead to collect all counters and instances of a counter object, but again, it can have a significant impact on the counter log size.
Blg) format. ” Initially this sounds like text-based counter logs are the better, but unfortunately, text-based counter logs do not collect transient counter instances that come and go after the data collector has started. This means that if you start a performance counter data collector in CSV format capturing all instances of the Process object and restart the worker processes of IIS, then the counter log will be missing the data of the new IIS worker processes. This is because the text-based data collectors are unable to make schema changes to the log file.
COUNTER PATHS A counter path is a line of text that defines one or more counter instances. It is similar to a UNC path (\\server\share) but has a slightly different syntax. The path can include a computer name as the source for the counter data. If the computer portion of the path is omitted such as \Processor(_Total)\% Processor Time, then the local computer is assumed. An asterisk (*) is used as a wild card for counter instances Performance counters (example: \Processor(*)\% Processor Time), for counter names (example: \Processor(_Total)\*), or both (example: \Processor(*)\*).