2026-04-19T08:23:40Zhttps://uvadoc.uva.es/oai/requestoai:uvadoc.uva.es:10324/757772025-05-20T19:01:02Zcom_10324_1165com_10324_931com_10324_894col_10324_1337
UVaDOC
author
Castro Caballero, Manuel De
author
Osorio, Roberto R.
author
Torres de la Sierra, Yuri
author
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
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.
eng
Informática
Accelerating Scientific Model Optimization with a Pipelined FPGA-Based Differential Evolution Engine
info:eu-repo/semantics/conferenceObject
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URL
https://uvadoc.uva.es/bitstream/10324/75777/1/FCCM25_Poster.pdf
File
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FCCM25_Poster.pdf
URL
https://uvadoc.uva.es/bitstream/10324/75777/2/FCCM_extended_abstract.pdf
File
MD5
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application/pdf
FCCM_extended_abstract.pdf