PRIMAGE project : predictive in silico multiscale analytics to support childhood cancer personalised evaluation empowered by imaging biomarkers

PRIMAGE is one of the largest and more ambitious research projects dealing with medical imaging, artificial intelligence and cancer treatment in children. It is a 4-year European Commission-financed project that has 16 European partners in the consortium, including the European Society for Paediatric Oncology, two imaging biobanks, and three prominent European paediatric oncology units. The project is constructed as an observational in silico study involving high-quality anonymised datasets (imaging, clinical, molecular, and genetics) for the training and validation of machine learning and multiscale algorithms. The open cloud-based platform will offer precise clinical assistance for phenotyping (diagnosis), treatment allocation (prediction), and patient endpoints (prognosis), based on the use of imaging biomarkers, tumour growth simulation, advanced visualisation of confidence scores, and machine-learning approaches. The decision support prototype will be constructed and validated on two paediatric cancers: neuroblastoma and diffuse intrinsic pontine glioma. External validation will be performed on data recruited from independent collaborative centres. Final results will be available for the scientific community at the end of the project, and ready for translation to other malignant solid tumours

Wygodny i bezpieczny dostęp do klastrów obliczeniowych

The investigation presented in this paper was prompted by the need to provide a manageable solution for secure access to computing clusters with a federated authentication framework. This requirement is especially important for scientists who need direct access to computing nodes in order to run their applications (e.g. chemical or medical simulations) with proprietary, open-source or custom-developed software packages. Our existing software, which enables non-Web clients to use Shibboleth-secured services, has been extended to provide direct SSH access to cluster nodes using the Linux Pluggable Authentication Modules mechanism. This allows Shibboleth users to run the required software on clusters. Validation and performance comparison with existing SSH authentication mechanisms confirm that the presented tools satisfy the stated requirements.Badania opisane w tej publikacji zostały przeprowadzone w celu zapewnienia wygodnego sposobu zabezpieczenia dostępu do klastrów obliczeniowych za pomocą federacyjnego mechanizmu uwierzytelniającego. Wymóg ten jest szczególnie istotny w odniesieniu do naukowców wykorzystujących zarówno otwarte oprogramowanie, jak i komercyjne oraz własne pakiety (np. chemiczne lub medyczne), uruchamiane bezpośrednio na węzłach obliczeniowych. Nasze poprzednie rozwiązanie, umożliwiające aplikacjom nie-webowym używanie usług zabezpieczonych mechanizmem Shibboleth zostało rozbudowane tak, aby zapewnić bezpośredni dostęp poprzez protokół SSH do węzłów klastrów, za pomocą mechanizmu "Pluggable Authentication Modules" Linuksa. Umożliwiło to użytkownikom shibbolethowym uruchamianie niezbędnego oprogramowania zainstalowanego na klastrach. Proces walidacji oraz porównanie wydajności z istniejącymi mechanizmami uwierzytelnienia dostępnymi dla protokołu SSH wykazał, że opisywane narzędzia spełniają postawione przed nimi wymagania

Exascale computing and data architectures for brownfield applications

Despite the recent dramatic advances in the computational and data processing capacities of the commodity solutions, a numerous scientific, socioeconomic and industrial “grand challenges” exists that could be solved only through capabilities that exceed the current solutions by orders of magnitude. To demonstrate the feasibility of addressing these problems necessitating processing of exascale data sets, novel architectural approaches are needed. These architectures need to support efficient service composition and balancing infrastructure- and user-centric points of view of exascale infrastructures and services. This combination of bottom-up and top-down approaches aims at narrowing the gap between infrastructure services and paving the way towards future high capacity generations einfrastructure. The resulting architecture will help us provide computing solutions to exascale challenges within the H2020 project PROCESS