{"id":162391,"date":"2011-03-01T00:00:00","date_gmt":"2011-03-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/scheduling-in-variable-core-collaborative-systems\/"},"modified":"2019-07-26T15:24:37","modified_gmt":"2019-07-26T22:24:37","slug":"scheduling-in-variable-core-collaborative-systems","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/scheduling-in-variable-core-collaborative-systems\/","title":{"rendered":"Scheduling in Variable-Core Collaborative Systems"},"content":{"rendered":"<div class=\"asset-content\">\n<p>The performance of a collaborative system depends on how two mandatory collaborative tasks, processing and transmission of user commands, are scheduled. We have developed multiple policies for scheduling these tasks on computers that have (a) one processing element on the network interface card and (b) one or more processing cores on the CPU. To compare these policies, we have a developed a formal analytical model that predicts their performance. It shows that the optimal scheduling policy depends on several factors including the number of cores that is available. We have implemented a system that supports all of the policies and performed experiments to validate the formal model. This system is a component of a self-optimizing scheduler we have developed that improves response times by automatically choosing the scheduling policy based on number of cores and other factors.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The performance of a collaborative system depends on how two mandatory collaborative tasks, processing and transmission of user commands, are scheduled. We have developed multiple policies for scheduling these tasks on computers that have (a) one processing element on the network interface card and (b) one or more processing cores on the CPU. To compare 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