论文标题
迈向商品异质系统的共同执行：适时约束场景的优化
Towards Co-execution on Commodity Heterogeneous Systems: Optimizations for Time-Constrained Scenarios
论文作者
论文摘要
由于其出色的性能和能耗，因此存在从强大的超级计算机到移动设备（包括台式计算机）的异质系统。这些体系结构在台式机系统和中型服务服务器中的无处不在，可以利用足够的可变性来利用多种问题，例如多媒体工作负载，视频编码，图像过滤和机器学习中的推断。由于异质性，已经采取了一些努力来减少编程工作并保留性能可移植性，但是这些系统包括一系列挑战。在执行共执行时，应用程序卸载工作负载以及引入的管理间接费用的上下文，对时间约束的情况下的绩效提高处进行惩罚。因此，本文提出了对EngineCl运行时的优化，以减少商品系统共同执行的惩罚以及负载平衡时算法改进。进行了详尽的实验评估，分别针对基于二进制和ROI的卸载模式的优化改进为7.5 \％和17.4 \％。由于所有优化，新的负载平衡算法始终是最有效的调度配置，在悲观的情况下，平均效率为0.84。
Heterogeneous systems are present from powerful supercomputers, to mobile devices, including desktop computers, thanks to their excellent performance and energy consumption. The ubiquity of these architectures in both desktop systems and medium-sized service servers allow enough variability to exploit a wide range of problems, such as multimedia workloads, video encoding, image filtering and inference in machine learning. Due to the heterogeneity, some efforts have been done to reduce the programming effort and preserve performance portability, but these systems include a set of challenges. The context in which applications offload the workload along with the management overheads introduced when doing co-execution, penalize the performance gains under time-constrained scenarios. Therefore, this paper proposes optimizations for the EngineCL runtime to reduce the penalization when co-executing in commodity systems, as well as algorithmic improvements when load balancing. An exhaustive experimental evaluation is performed, showing optimization improvements of 7.5\% and 17.4\% for binary and ROI-based offloading modes, respectively. Thanks to all the optimizations, the new load balancing algorithm is always the most efficient scheduling configuration, achieving an average efficiency of 0.84 under a pessimistic scenario.
