2026-04-16T04:43:00Zhttps://uvadoc.uva.es/oai/request

oai:uvadoc.uva.es:10324/757772025-05-20T19:01:02Zcom_10324_1165com_10324_931com_10324_894col_10324_1337

Castro Caballero, Manuel De Osorio, Roberto R. Torres de la Sierra, Yuri Llanos Ferraris, Diego Rafael 2025-05-20T08:10:22Z 2025-05-20T08:10:22Z 2025 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 Producción Científica 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. This work was supported in part by Grant PID2022-142292NB-I00 (NATASHA Project); by grant TED2021–130367B–I00, funded by MCIN/AEI/10.13039/501100011033; and by MCIN/AEI/10.13039/501100011033 through the EU Grant PID2022-136435NB-I00. Manuel de Castro has been supported by a FPU 2022 grant. This research was supported by grants from NVIDIA and utilized NVIDIA A100. Póster application/pdf eng IEE info:eu-repo/semantics/openAccess Informática 1203 Ciencia de Los Ordenadores 3304 Tecnología de Los Ordenadores Accelerating Scientific Model Optimization with a Pipelined FPGA-Based Differential Evolution Engine 33rd IEEE Symposium on Field-Programmable Custom Computing Machines (FCCM) info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion https://www.researchgate.net/publication/391892110_Accelerating_Scientific_Model_Optimization_with_a_Pipelined_FPGA-Based_Differential_Evolution_Engine