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Cost Minimization for Heterogeneous Systems with Gaussian Distribution Execution Time

机译:高斯分布执行时间的异构系统成本最小化

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Time and cost are the most critical performance metrics for computer systems including embedded system, desktop, laptop, mainframe computer, and smart phone. In real world, the execution time may not be fixed and it usually follows Gaussian distribution. In this paper, we analyze how to minimize total cost while satisfying time constraints for heterogeneous systems with Gaussian execution time. This is called HAP-G (Heterogeneous Assignment with Probability - Gaussian) problem, which is a NP-complete problem. However, for simple path special cases, we find a polynomial-time optimal solution and propose the HAP-G-SP algorithm, and the experimental results show the effectiveness of our approach.
机译:时间和成本是计算机系统中最关键的性能指标,包括嵌入式系统,桌面,笔记本电脑,大型计算机和智能手机。在现实世界中,执行时间可能无法修复,并且通常遵循高斯分布。在本文中,我们分析了如何最小化总成本,同时满足高斯执行时间的异构系统的时间约束。这被称为HAP-G(具有概率 - 高斯的异构分配 - 高斯)问题,这是一个NP完整的问题。然而,对于简单的路径特殊情况,我们发现多项式最佳解决方案并提出了HAP-G-SP算法,实验结果表明了我们的方法的有效性。

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