<html><head><meta name="color-scheme" content="light dark"></head><body><pre style="word-wrap: break-word; white-space: pre-wrap;">\section{Conclusion}\label{ch6:conclu}

In this chapter, different methodologies that effectively take advantage of
current cluster technologies with GPUs have been presented. Beyond the simple
collaboration of several nodes that include GPUs, we have addressed parallel
schemes to efficiently overlap communications with computations (including GPU
transfers), and also computations on the CPU with computations on the
GPU. Moreover, parallel schemes for synchronous as well as asynchronous
iterative processes have been proposed. The proposed schemes have been validated
experimentally and provide the expected behavior. Finally, as a prospect we have
developed a programming tool that will, in middle or long term, provide all the
required technical elements to implement the proposed schemes in a single tool,
without requiring several external libraries.

We conclude that GPU computations are very well suited to achieve overlap with
CPU computations and communications and they can be fully integrated in
algorithmic schemes combining several levels of parallelism.

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