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A Parallel GPU Implementation of the Timber Wolf Placement Algorithm

机译:木狼放置算法的平行GPU实现

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GPUs have been gaining acceptance in the electronic design automation field as attractive platforms for implementing and accelerating computationally extensive applications. Researchers agree that it is critical that EDA algorithms exploit future platforms and explore the use of parallel algorithms as we move to the many core era. This paper describes the implementation of the Timber Wolf placement algorithm using CUDA and demonstrates the applicability of GPUs in accelerating electronic design automation tools. The algorithm has been implemented on a Xeon Workstation using C, and achieved a substantial acceleration on an Nvidia Tesla C2070 card.
机译:GPU在电子设计自动化领域获得了可吸引力的平台,用于实现和加速计算广泛应用的有吸引力平台。研究人员认为,EDA算法利用未来的平台并探索了并行算法,因为我们转移到许多核心时代,这是至关重要的。本文介绍了使用CUDA的木狼放置算法的实现,并展示了GPU在加速电子设计自动化工具中的适用性。该算法已经在使用C的Xeon工作站上实现,并在NVIDIA TESLA C2070卡上实现了大量的加速度。

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