低消費電力マルチコアプロセッサとその並列ソフトウェアに関する研究

该研究在移动的设备和数据中心中的（云）服务器的功率控制领域取得了新的成果。在Linux和Android操作系统上，OSCAR编译的应用程序的运行时间得到了改进，并且变得更加可预测。为了实现这一成功，修改了操作系统，以支持更确定的任务到处理器的映射。此外，操作系统扩展了一个新的编程接口（API），以控制处理器内核的性能。API包括动态频率和电压缩放（DVFS）、时钟门控和功率门控操作。为了评估性能，操作系统还收集有关CPU和DRAM功耗以及处理器温度的数据。测量设置执行全自动数据采集。这使得在一个月内收集了数千次测量结果。该数据被用于执行多核编译器运行时（“libgomp”）和科学应用的离线设计空间探索。因此，可以在不对应用的二进制代码进行任何修改的情况下降低功耗。

The research lead to new results in the area of power control for mobile devices and for (cloud) servers which are found in data centers. On the Linux- and Android-operating system the run-time of OSCAR-compiled applications has been improved and also became more predictable. In order to achieve this success the operating system was modified to support more deterministic task to processor mappings. Furthermore the operating system was extended with a new programming interface (API) to control the performance of the processor cores. The API includes operations for dynamic frequency and voltage scaling (DVFS), clock- and power-gating. To assess the performance the operating system also collects data on CPU- and DRAM power consumption as well as processor temperature. The measurement setup performs fully automatic data acquisition. This allowed thousands of measurements to be collected over a month. The data was used to perform an offline design space exploration for a multi-core compiler run-time ("libgomp") and a scientific application. As a result the power consumption could be reduced without any modifications to the binary code of the application.