Sentence examples for core kernel from inspiring English sources

Exact(10)

Finally, let us recall that Linux core kernel virtual address space is not randomized.

Microsoft is shifting the core kernel of Windows Phone over to one a bit more familiar to developers.

So what's in the core kernel today will make its way to mainstream distribution in a couple months, as vendors test these new features with the rest of their stack's components.

Step 2: Selecting the SVM (the ε-SVR model was used); applying cross-validation technique (the fivefold cross-validation technique was used); and selecting the type of core kernel.

Today marks the start of the fourth annual Linux Foundation Collaboration Summit, which is "an exclusive, invitation-only summit gathering core kernel developers, distribution maintainers, ISVs, end users, system vendors and other community organizations for plenary sessions and workgroup meetings to meet face-to-face to tackle and solve the most pressing issues facing Linux today".

Guys like Linus Torvalds and Andrew Morton can know the nitty gritty of the core kernel, without having to know — or even care, much — about the nitty gritty of the X Window system, or how the GNOME environment works: other people are responsible for those things because they are, literally, separate things.

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Similar(47)

There were five core kernels in PeaceBuilders.

Its core kernels include a response cost for negative behavior (e.g., Conyers et al. 2004); team competition (e.g., Beersma et al. 2003); public posting of results (e.g., Parsons 1982); and team rotations (deemed critical but with no supporting study).

The problem with such software was that their monolithic cores ("kernels") were always bound tightly to one particular type of microprocessor and could thus only run properly on a computer built around that particular chip.Dr Rashid and his colleagues licked the problem by simplifying the kernel, adding what computer scientists call a "layer of abstraction".

Add corn kernels.

This paper focuses on the use of Machine Learning to predict the performance of stencil kernels on multi-core architectures.

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