A Cloud Architecture for the Execution of Medical Imaging Biomarkers

López-Huguet, Sergio; García-Castro, Fabio; Alberich‐Bayarri, Ángel; Blanquer, Ignácio

doi:10.1007/978-3-030-22744-9_10

Cited by 3 publications

(3 citation statements)

References 15 publications

(14 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, this architecture includes a workflow to ease the building, testing, delivery, and version management of the containers thanks to the adoption of a continuous integration tool. This work [100] was published in the conference International Conference on Computational Science, which is rated as CORE A and Class 2 in the GII-GRIN-SCIE conference ranking.…”

Section: Organization Of This Documentmentioning

confidence: 99%

“…In [85], the authors present an architecture to process Internet of Things (IoT) data collected from smart agriculture. In our previous works, we presented a cloud architecture for data analysis [102] and for processing medical imaging [100].…”

Section: Architecturementioning

confidence: 99%

“…In [100], the authors present an elastic cloud architecture for medical imaging processing that can be deployed in the majority of cloud provider platforms. It should be pointed out that this architecture is not a multi-site architecture, it does not consider multi-tenancy and it uses non-distributed storage.…”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

Elastic, Interoperable and Container-based Cloud Infrastructures for High Performance Computing

Huguet¹

View full text Add to dashboard Cite

show abstract

Section: Organization Of This Documentmentioning

confidence: 99%

Section: Architecturementioning

confidence: 99%

See 1 more Smart Citation

Elastic, Interoperable and Container-based Cloud Infrastructures for High Performance Computing

Huguet¹

View full text Add to dashboard Cite

show abstract

Seamlessly Managing HPC Workloads Through Kubernetes

López-Huguet

Segrelles

Kasztelnik

et al. 2020

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

This paper describes an approach to integrate the jobs management of High Performance Computing (HPC) infrastructures in cloud architectures by managing HPC workloads seamlessly from the cloud job scheduler. The paper presents hpc-connector, an open source tool that is designed for managing the full life cycle of jobs in the HPC infrastructure from the cloud job scheduler interacting with the workload manager of the HPC system. The key point is that, thanks to running hpc-connector in the cloud infrastructure, it is possible to reflect in the cloud infrastructure, the execution of a job running in the HPC infrastructure managed by hpc-connector. If the user cancels the cloud-job, as hpc-connector catches Operating System (OS) signals (for example, SIGINT), it will cancel the job in the HPC infrastructure too. Furthermore, it can retrieve logs if requested. Therefore, by using hpc-connector, the cloud job scheduler can manage the jobs in the HPC infrastructure without requiring any special privilege, as it does not need changes on the Job scheduler. Finally, we perform an experiment training a neural network for automated segmentation of Neuroblastoma tumours in the Prometheus supercomputer using hpc-connector as a batch job from a Kubernetes infrastructure.

show abstract