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We need to make sure that this experimental evaluation does indeed cover the application workload pattern in order to guarantee general applicability.
Such metrics include application workload, execution time estimation, disk or memory space availability, etc.
The study is performed by using a simulation framework that captures dynamic changes in the operating temperature and application workload.
In this paper, we present a customization approach by adding strategic links targeted to match large application workload.
When the application workload and execution profiles are known or can be estimated at compile time, then we can perform the allocation and scheduling statically at compile time.
Atomic MultiLog exploits the application workload assumptions outlined above to facilitate both high throughput data ingestion, as well as rich online and offline queries.
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It is interesting to know different hypervisors' performance for the consolidated application workloads.
Emerging application workloads are often complex and exhibit amorphous data parallelism with irregular control flow, and unstructured data access.
We use a cloud based web service for offloading parts of the application workloads intelligently to save resources, like energy and network cost.
We also present various results achieved, that demonstrate both the utility and performance of GridUFO under various application workloads and scenarios.
(It's like having to turn on all the lights in your house when you really only need one). Decoupling applications from your legacy infrastructure gives you the flexibility to scale offerings and accommodate different application workloads.
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