Conveners
Technology Tracking: Parte 1
- Michele Michelotto (Istituto Nazionale di Fisica Nucleare)
Technology Tracking: Parte 2
- Michele Michelotto (Istituto Nazionale di Fisica Nucleare)
Advancements in computing hardware technology enabled HEP experiments to achieve their scientific objectives. However, the path to HL-LHC requires to continuously align increasing resource needs with constant (or decreasing) financial resources. Consequently, it is crucial to monitor hardware technology trends as a prerequisite for optimising infrastructure investments.
We will provide an...
GARR-T, l’ultima generazione della rete GARR attiva dal 2023, è un’infrastruttura in continua evoluzione, progettata per offrire maggiore capillarità, capacità di trasmissione potenziata e nuove funzionalità software. Questa evoluzione consente di espandere la rete con connessioni sottomarine e abilitare applicazioni avanzate oltre la trasmissione dati.
Nel percorso verso...
In questo intervento presenteremo la proposta di un nuovo servizio comunitario.
Il progetto di Federazione Storage S3 mira a creare un servizio di storage federato qualificato ACN basato sul protocollo S3, gestito da Università e Centri di Ricerca. Questo servizio offrirà un controllo completo sui dati, riducendo la latenza di accesso e migliorando la sicurezza e la continuità del servizio....
COKA is a small HPC cluster, designed for codes prototyping and benchmarking, initially installed in 2015 at INFN Ferrara with a DP peak performance of about 100 TFLOP/s. Like the Voyager, it outlived its original mission and it has been continuously operational since almost ten years, but the original system is now being decommissioned to be replaced by newer heterogeneous compute nodes and a...
Neural Networks (NNs) are widely employed in tasks such as feature extraction, classification, segmentation, and reconstruction of quantitative MRI maps, particularly in scenarios lacking an analytical model, resulting in a reconstruction process that is computationally intensive and time-consuming. The versatility and ability of NNs to be trained on ground-truth datasets are particularly...
Since 2017 we started R&D on co-designing (HW/SW) computational systems, targeting mainly FPGAs. We developed over the years several solutions for computational acceleration on FPGAs, including, but not limited to, the creation of a full framework for building FPGA-based modular architectures, namely the BondMachine project.
The problems addressed by these solutions range from the standard...
