Argitalpenak (115) Jose Manuel Garcia Carrasco argitalpenak

2024

  1. Adding metabolic tasks to human GEM models to improve the study of gene targets and their associated toxicities

    Scientific Reports, Vol. 14, Núm. 1

  2. POAS: a framework for exploiting accelerator level parallelism in heterogeneous environments

    Journal of Supercomputing, Vol. 80, Núm. 10, pp. 14666-14693

2023

  1. Improving a Deep Learning Model to Accurately Diagnose LVNC

    Journal of Clinical Medicine, Vol. 12, Núm. 24

  2. Matching Linear Algebra and Tensor Code to Specialized Hardware Accelerators

    CC 2023 - Proceedings of the 32nd ACM SIGPLAN International Conference on Compiler Construction

  3. On the representativeness and stability of a set of EFMs

    Bioinformatics, Vol. 39, Núm. 6

2022

  1. Applying Intel's oneAPI to a machine learning case study

    Concurrency and Computation: Practice and Experience, Vol. 34, Núm. 13

  2. HDNN: a cross-platform MLIR dialect for deep neural networks

    Journal of Supercomputing, Vol. 78, Núm. 11, pp. 13814-13830

  3. Left ventricular non-compaction cardiomyopathy automatic diagnosis using a deep learning approach

    Computer Methods and Programs in Biomedicine, Vol. 214

  4. Performance portability in a real world application: PHAST applied to Caffe

    International Journal of High Performance Computing Applications, Vol. 36, Núm. 3, pp. 419-439

  5. Staphylococcus epidermidis RP62A’s Metabolic Network: Validation and Intervention Strategies

    Metabolites, Vol. 12, Núm. 9

2021

  1. ACOTSP-MF: A memory-friendly and highly scalable ACOTSP approach

    Engineering Applications of Artificial Intelligence, Vol. 99

  2. Deploying deep learning approaches to left ventricular non-compaction measurement

    Journal of Supercomputing, Vol. 77, Núm. 9, pp. 10138-10151

2020

  1. Boosting the extraction of elementary flux modes in genome-scale metabolic networks using the linear programming approach

    Bioinformatics, Vol. 36, Núm. 14, pp. 4163-4170

  2. First experiences on applying deep learning techniques to prostate cancer detection

    Advances in Parallel Computing

  3. Flux coupling and the objective functions’ length in efms

    Metabolites, Vol. 10, Núm. 12, pp. 1-12

  4. High-throughput fuzzy clustering on heterogeneous architectures

    Future Generation Computer Systems, Vol. 106, pp. 401-411

  5. Offloading strategies for Stencil kernels on the KNC Xeon Phi architecture: Accuracy versus performance

    International Journal of High Performance Computing Applications, Vol. 34, Núm. 2, pp. 199-207

  6. Re-engineering the ant colony optimization for CMP architectures

    Journal of Supercomputing, Vol. 76, Núm. 6, pp. 4581-4602

2019

  1. Efficient, semantics-rich transformation and integration of large datasets

    Expert Systems with Applications, Vol. 133, pp. 198-214

2018

  1. Application of high performance computing techniques to the semantic data transformation

    Advances in Intelligent Systems and Computing