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00925njm 22002777a 4500 dc Castro Caballero, Manuel De author Osorio, Roberto R. author Torres de la Sierra, Yuri author Llanos Ferraris, Diego Rafael author 2025 Differential Evolution (DE) [5] with Numerical Integration (NI) is an ideal target for Custom Computing Machines on FPGAs, since it produces deep pipelines, requires minimal external memory bandwidth, and benefits from large memory bandwidth. DE is a genetic algorithm used for scientific model optimization. We propose a generic FPGA-based DE architecture, parameterized to accommodate to different scientific models. It supports both non-adaptive and adaptive NI methods. The core DE engine is programmed in VHDL for high adaptability and performance, whereas the scientific models and their NI are programmed in C++ for flexibility and easiness of development. 33rd IEEE Symposium on Field-Programmable Custom Computing Machines (FCCM), Fayetteville, Arkansas, USA https://uvadoc.uva.es/handle/10324/75777 10.13140/RG.2.2.22570.94403 Informática Accelerating Scientific Model Optimization with a Pipelined FPGA-Based Differential Evolution Engine