Sentence examples for multiple workloads and from inspiring English sources

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Multiple workloads and an increasing number of processes have been taken into account to compare the above mentioned protocols.

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And there weren't multiple workloads contending for the resource.

Models of train driving behaviour have concentrated on safely and punctuality by studying how train drivers manage multiple workloads such as time pressure, cognitive demands of procedural tasks, and behavioural conflict between tasks.

For operators, our results provide a model for dimensioning BitTorrent caches, and a thorough evaluation of cache performance with multiple workloads.

The whole point of restructuring was to strip away bureaucracy and improve earnings, she said, but because there were fewer management positions to go around, those who survived faced multiple workloads.

However, for the case where multiple workloads are considered, the search for removes the need to jointly consider the application configurations across different workloads.

In addition to providing a direct solution to the scheduling of multiple workloads known in advance, the Lagrangian approach also allows us to solve the allocation problem stochastically, permitting statisically optimal allocations to be made even if we have only a probability distribution of the workloads that are to be run.

When multiple workloads share a single GPU device at fine-grained level (e.g., API-level multiplexing [ 20– 22]), the GPU memory should be shared between multiple workloads.

The latter models our system as a closed queuing network considering multiple resources, different classes of devices based on their service request patterns and multiple workload mixes [18].

In contrast with [27], which addresses the management of datacenters based on thermal awareness with external sensing infrastructure for energy and cooling efficiency, the work, presented in this paper, focuses on coordinating multiple workload-aware managers to ensure an energy efficiency.

Map systems often serve dynamic web workloads and involve multiple CPU- and I/O-intensive tiers, which makes it challenging to meet the response time targets of map requests while using the resources efficiently.

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