Study of program placement optimization in mixed environments in environmental adaptation

In recent years, the number of applications using heterogeneous hardware such as FPGAs and GPUs has been increasing. However, to fully utilize them, an understanding of the hardware is necessary, which is a high barrier. Based on this background, we have proposed environment-adaptive software that automatically converts code written by programmers for normal CPUs according to the deployment environment, enabling high performance operation. This paper targets automatic offloading to appropriate hardware in a mixed environment that contains normal CPUs, multi-core CPUs, FPGAs, GPUs, and quantum computers. We confirm how much the performance of normal CPUs can be achieved with each hardware, and based on cost performance, we determine the appropriate hardware for offloading and perform automatic offloading. We confirm that the proposed method can automatically offload by measuring the processing time using actual heterogeneous hardware. Y. Yamato, "Study of program placement optimization in mixed environments in environmental adaptation," The 13th IIAE International Conference on Industrial Application Engineering 2025 (ICIAE 2025), pp.327-334, Mar. 2025.