Projects

We are currently working on the following research lines:

Application of efficient, high-performance computing with advanced artificial intelligence techniques for diagnosing diseases in heterogeneous systems. Last publications:

• G. Bernabé, P. González-Férez, José M. García, G. Casas y J. González-Carrillo. “Expanding the deep-learning model to diagnosis LVNC: limitations and trade-offs”. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization (ISSN: 2168-1163), Vol.: 12, pp. 1-9, 2024. Taylor & Francis.
• Jesús M. Rodríguez-de Vera, Josefa González-Carrillo, José M. García y Gregorio Bernabé. “Deploying deep learning approaches to left ventricular non-compaction measurement”. The Journal of Supercomputing (ISSN: 1573-0484), Vol.: 77, pp. 10138-10151, 2021. https://doi.org/10.1007/s11227-021-03664-0
• Jesús M. Rodríguez-de Vera, Gregorio Bernabé, José M. García, Daniel Saura y Josefa González-Carrillo. “Left Ventricular Non-Compaction Cardiomyopathy Automatic Diagnosis Using a Deep Learning Approach”. Computer Methods and Programs in Biomedicine (ISSN: 0169-2607), Vol.:214, Artículo ID: 106548, 2022. https://doi.org/10.1016/j.cmpb.2021.106548

Development of advanced techniques for efficient execution of the hardware accelerators in the superchip architecture. Last publications:

• Pablo Antonio Martínez, Gregorio Bernabé y José Manuel García. “Code Detection for Hardware Acceleration Using Large Language Models”. IEEE Access (ISSN: 2169-3536), Vol.: 12, pp. 35271-35281, 2024. Institute of Electrical and Electronics Engineers.
• Pablo Antonio Martínez, Jackson Woodruff, Jordi Armengol-Estapé, Gregorio Bernabé, José Manuel García y Michael F. P. O’Boyle. “Matching linear algebra and tensor code to specialized hardware accelerators”. En Proceedings of the 32nd ACM SIGPLAN International Conference on Compiler Construction (CC ’23), New York, NY, USA. Páginas: 85-97, 2023. Association for Computing Machinery.
• Pablo Antonio Martínez-Sánchez, Biagio Peccerillo, Sandro Bartolini, José M. García y Gregorio Bernabé. “Performance portability in a real-world application: PHAST applied to Caffe”. The International Journal of High-Performance Computing Applications (ISSN: 1094-3420), Vol.: 36, pp. 419-439, 2022.
• Pablo Antonio Martínez, Gregorio Bernabé y José M. García. “HDNN: a cross-platform MLIR dialect for deep neural networks”. The Journal of Supercomputing (ISSN: 1573-0484), Vol.: 78, pp. 13814-13830, 2022. https://doi.org/10.1007/s11227-022-04417-3

Code modernization for Bioinformatics: Acceleration of bioinformatics and bio-inspired algorithms, mainly focused on those of Systems Biology. Last publications:

• Francisco Guil, José F. Hidalgo y José M. García. “On the representativeness and stability of a set of EFMs”. Bioinformatics (ISSN: 1367-4811), Vol.: 39, Artículo ID: btad356, 2023. Oxford University Press.
• Francisco Guil, José F. Hidalgo y José M. García. “Boosting the extraction of Elementary Flux Modes in Genome-Scale Metabolic Networks using the Linear Programming approach”. Bioinformatics (ISSN: 1367-4803), Vol.: 36, pp. 4163-4170, 2020. https://doi.org/10.1093/bioinformatics/btaa280
• Francisco Guil, Guillermo Sánchez-Cid y José M. García. “Staphylococcus epidermidis RP62A’s Metabolic Network: Validation and Intervention Strategies”. Metabolites (ISSN: 2218-1989), Vol.: 12, Artículo ID: 808, 2022. https://doi.org/10.3390/metabo12090808

High-Performance Computing and Energy-Efficient Deep Neural Network Systems.

Memory Hierarchy and Cache Coherence for Many-core CMP

Fault-tolerance in CMP Architectures

Benchmarking the GPU for Novel Computations

Design, Implementation, Evaluation, and Exploitation of Bioinformatics Applications in High Performance Massively Parallel Architectures