Gpu generation of binary 2-separating codes

[EN] This paper addresses the generation of binary 2-separating codes and the study of the code rates that can be achieved in practice. In the case of binary 2-separating codes, there exist lower and upper theoretical bounds in the rates that can be achieved. The generation of 2-separating codes has...

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Detalles Bibliográficos
Autores: Fernandez, Marcel, Livieratos, John, Martínez Zaldívar, Francisco José|||0000-0002-7845-6273, García Mollá, Víctor Manuel|||0000-0003-4768-7367, Simarro, M. Angeles|||0000-0001-6238-2532, Gonzalez, Alberto|||0000-0002-6984-3212
Tipo de recurso: artículo
Fecha de publicación:2026
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:dnet:riunet______::c5088c2b4e36ed46351ecec04953be35
Acceso en línea:https://riunet.upv.es/handle/10251/233505
Access Level:acceso abierto
Palabra clave:Binary 2-separating codes
GPU computing
CUDA
Numerical computing
Descripción
Sumario:[EN] This paper addresses the generation of binary 2-separating codes and the study of the code rates that can be achieved in practice. In the case of binary 2-separating codes, there exist lower and upper theoretical bounds in the rates that can be achieved. The generation of 2-separating codes has been studied from a theoretical point of view, but, as far as we know, it has not been tackled from a practical point of view. In this paper, we consider and analyze two different generation algorithms. Both algorithms were implemented in CUDA and executed in GPUs, for the sake of efficiency. The first algorithm is inspired by the Moser-Tardos algorithm, which is based on the Local Lov & aacute;sz Lemma. This algorithm has a strong theoretical appeal; codes obtained through this first algorithm can be shown to match the best known lower bound. To generate codes with rates as large as possible, a second algorithm has been implemented. The rates achieved are larger than those achieved with the first algorithm, but they still are very far from the theoretical upper bound. The results obtained suggest that the theoretical upper bound can probably be improved.