When using heterogeneous hardware, barriers of technical skills such as OpenMP, CUDA and OpenCL are high. Based on that, I have proposed environment-adaptive software that enables automatic conversion, configuration. However, including existing technologies, there has been no research to properly and automatically offload the mixed offloading destination environment such as GPU, FPGA and many core CPU. In this paper, as a new element of environment-adaptive software, I study a method for offloading applications properly and automatically in the environment where the offloading destination is mixed with GPU, FPGA and many core CPU. Y. Yamato, "Proposal of Automatic Offloading Method in Mixed Offloading Destination Environment," 2020 Eighth International Symposium on Computing and Networking Workshops (CANDARW 2020), pp.460-464, DOI: 10.1109/CANDARW51189.2020.00094, Nov. 2020. "(c) 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works."

翻译：在使用异构硬件时，OpenMP、CUDA和OpenCL等技术技能的门槛较高。基于此，我曾提出能够实现自动转换与配置的环境自适应软件。然而，包括现有技术在内，尚未有研究能够恰当且自动地处理诸如GPU、FPGA及众核CPU等混合卸载目标环境。本文作为环境自适应软件的一个新要素，研究在卸载目标混合了GPU、FPGA与众核CPU的环境中，恰当且自动地卸载应用程序的方法。Y. Yamato, "混合卸载目标环境中自动卸载方法的提出"，2020年第八届计算与网络研讨会国际会议(CANDARW 2020)，第460-464页，DOI: 10.1109/CANDARW51189.2020.00094，2020年11月。"(c) 2020 IEEE。允许个人使用本材料。所有其他用途，包括在任何现有或未来媒体中为广告或推广目的重印/再版本材料、创建新的集体作品、转售或重新分发至服务器或列表，或在其他作品中重用本作品的任何受版权保护部分，均须获得IEEE许可。"