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Performance and power consumption evaluation in smartphone based image processing for medical applications

机译:基于智能手机的医学应用中的图像处理性能和功耗评估

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More and more image processing applications are intended to run on mobile devices. This trend is visible also in medical industry, which have very strict reliability and safety requirements. Increased power consumption and inefficient image processing can affect both of these factors significantly. More over, it affects the user experience as well. In this paper authors investigates the performance and power consumption of several different numeric algorithms implemented on iPhone device. The comparison is made between CPU and GPU based solutions. Authors evaluated the test scenarios involving common used operations: matrix multiplication, thresholding and Canny's edge detection. The results showed that GPU based solution can be up to 4 times faster as CPU based one, with similar power footprint in particular cases. All measurements have been gathered without hardware interference nor jailbreaking of the device. Finally authors discuss possible application considerations and scenarios in medical related image processing smartphone apps.
机译:越来越多的图像处理应用程序旨在在移动设备上运行。这种趋势也可见,也可见,具有非常严格的可靠性和安全要求。增加功耗和低效图像处理可以显着影响这些因素。更多结束,它也会影响用户体验。在本文中,作者研究了在iPhone设备上实现了几种不同数字算法的性能和功耗。 CPU和基于GPU的解决方案之间的比较。作者评估了涉及常见使用操作的测试场景:矩阵乘法,阈值和Canny的边缘检测。结果表明,基于GPU的解决方案可以在基于CPU的速度速度快4倍,特别是具有类似的功率足迹。已经收集所有测量,而无需硬件干扰也不越狱。最后作者讨论了医学相关图像处理智能手机应用中可能的应用程序考虑因素和情景。

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