HPC, Big Data, and AI Convergence Towards Exascale, CRC

HPC, Big Data, and AI Convergence Towards Exascale, CRC

Terzo, O., & Martinovič, J. (2022), “HPC, Big Data, and AI Convergence Towards Exascale: Challenge and Vision (1st ed.)”, CRC Press, is now  avaiable at https://doi.org/10.1201/9781003176664

DeepHealth partners have contributed to the introduction of the book and with 2 book chapters: 

a) E. Quiñones, J. Perales, J. Ejarque, A. Badouh, S. Marco, F. Auzanneau, F. Galea, D. González, J. R. Hervás, T. Silva, I. Colonnelli, B. Cantalupo, M. Aldinucci, E. Tartaglione, R. Tornero, J. Flich, J. M. Martínez, D. Rodriguez, I. Catalán, J. Ejarque, C. Hernández, “The DeepHealth HPC Infrastructure: Leveraging Heterogenous HPC and Cloud-Computing Infrastructures for AI-Based Medical Solutions“, Chapter 10, available here

Abstract: This chapter presents the DeepHealth HPC toolkit for an efficient execution of deep learning (DL) medical application into HPC and cloud-computing infrastructures, featuring many-core, GPU, and FPGA acceleration devices. The toolkit offers to the European Computer Vision Library and the European Distributed Deep Learning Library (EDDL), developed in the DeepHealth project as well, the mechanisms to distribute and parallelize DL operations on HPC and cloud infrastructures in a fully transparent way. The toolkit implements workflow managers used to orchestrate HPC workloads for an efficient parallelization of EDDL training operations on HPC and cloud infrastructures, and includes the parallel programming models for an efficient execution EDDL inference and training operations on many-core, GPUs and FPGAs acceleration devices.

b) D. Oniga, B. Cantalupo, E. Tartaglione, D. Perlo, M. Grangetto, M. Aldinucci, F. Bolelli, F. Pollastri, M. Cancilla, L. Canalini, C. Grana, C. Muñoz Alcalde, F. A. Cardillo, M. Florea, “Applications of AI and HPC in the Health Domain“, Chapter 11, available here.

Abstract: This chapter presents the applications of artificial intelligence (AI) and high-computing performance (HPC) in the health domain, illustrated by the description of five of the use cases that are developed in the DeepHealth project. In the context of the European Commission supporting the use of AI and HPC in the health sector, DeepHealth Project is helping health experts process large quantities of images, putting at their disposal DeepLearning and computer vision techniques, combined in the DeepHealth toolkit and HPC infrastructures. The DeepHealth toolkit is tested and validated through 15 use cases, each of them representing a biomedical application. The most promising use cases are described in the chapter, which concludes with the value proposition and the benefits that DeepHealth toolkit offers to future end users.

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