Projects and Funding
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TEXTAROSSA: Towards EXtreme scale Technologies and Accelerators for euROhpc hw/Sw Supercomputing Applications for exascale.
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CARES: Context-Aware Realistic Epidemic Simulator
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COURIER: COUntering RadIcalism InvEstigation platform
Funded under the Fondo Europeo di Sviluppo Regionale - Programma Operativo Rezione Lazio 2014-2020. ( POR FESR 2014-2020 - AEROSPAZIO E SICUREZZA)
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IANCIS: Indexing of Anonymous Networks for Crime Information Search.
Funded by the EU Financial Programme "Prevention of and Fight against Crime" (ISEC) - DG Home Affairs. -
SIEX: Semantic Information EXchange.
Funded by the EU Financial Programme "Prevention of and Fight against Crime" (ISEC) - DG Home Affairs. -
ISODAC: Indexing and Search Of Data Against Crime.
Funded by the EU Financial Programme "Prevention of and Fight against Crime" (ISEC) - DG Home Affairs. (http://www.isodac.eu)
To achieve high performance and high energy efficiency on near-future exascale computing systems, a technology gap needs to be bridged: increase efficiency of computation with extreme efficiency in HW and new arithmetics, as well as providing methods and tools for seamless integration of reconfigurable accelerators in heterogeneous HPC multi-node platforms. TEXTAROSSA aims at tackling this gap through applying a co-design approach to heterogeneous HPC solutions, supported by the integration and extension of IPs, programming models and tools derived from European research projects, led by TEXTAROSSA partners.
The main directions for innovation are towards: i) enabling mixed-precision computing, through the definition of IPs, libraries, and compilers supporting novel data types (including Posits), used also to boost the performance of AI accelerators; ii) implementing new multilevel thermal management and two-phase liquid cooling; iii) developing improved data movement and storage tools through compression; iv) ensure secure HPC operation through HW accelerated cryptography; v) providing RISC-V based IP for fast task scheduling and IPs for low-latency intra/inter-node communication. These technologies will be tested on the Integrated Development Vehicles mirroring and extending the European Processor Initiative ARM64-based architecture, and on an OpenSequana testbed.
To drive the technology development and assess the impact of the proposed innovations TEXTAROSSA will use a selected but representative number of HPC, HPDA and AI demonstrators covering challenging HPC domains such as general-purpose numerical kernels, High Energy Physics (HEP), Oil & Gas, climate modelling, and emerging domains such as High Performance Data Analytics (HPDA) and High Performance Artificial Intelligence (HPC-AI).
The COVID-19 pandemic has highlighted the importance of timely interventions and of being prepared to promptly and safely restart economic and social activities. To this end, we propose the design and development of an epidemic simulator based on the realistic representation of the interactions between individuals of the population under consideration.
CARES is a contagion simulator that can be adapted for specific contexts (for example parks, hospitals, school, etc.) to simulate the impact of potential containment measures. It can also be used to study the evolution of real situations for the purpose of preventing them in the future. The CARES project has been funded under the FISR 2020 COVID
The aim of the project is to develop a tool that can help Europe in facing terroristic threats, criminal's propaganda activities and radicalizzation processes. Criminal groups and organizations often use the surface and dark web for their activities disseminting documents and resources in several formats: textual, video and images. In order to act, law enforcemnt agencies need tools able to collect, elaborate and analyse such data conviniently. The COURIER project aims at providing an analysis platform to facilitate the activities of law enforcemnt agencies in this context.
The Deep Web, that is not indexed by standard search engines, has an extension that is estimated to be several orders of magnitude larger than the Surface Web, and contains many information, not necessarily related to criminal activities. Conversely, the Dark Web, a subset of the Deep Web, composed by the web resources hosted on darknets (describable as overlay networks, which despite leaning on the public Internet require specific software, configuration or authorization for te access) represents an appealing virtual place for criminal activities, empowered by the use of untraceable money, the Bitcoin. As a result, darknets are used for online child sexual exploitation, markets very often specialized in black market goods including weapons or narcotics.
Among darknets, the Tor (The Onion Router) network is probably the most known and used. Tor is a communication network designed as a low-latency, anonymity-guaranteeing and censorship-resistant network. It allows running anonymous and untraceable Web servers, called hidden services, that can be accessed only using a specific Tor-enabled browser. The main objective of the project was the development of a tool able to crawl Tor websites and feed a semantic engine for indexing and clustering collected data. The tool is meant to be the first step towards the development of an investigation instrument for the Tor network
The SIEX project aims at enhancing the quality of the information exchanged by Law Enforcement Agencies by offering a semantic engine that analyzes both requests and responses sent and received within the context of the Swedish Initiative. We are going to provide also all the necessary tools to help in automating the information and intelligence exchange by leveraging on existing technology platforms already in use by EU LEAs. One of the complaints of the LEAs is that the forms defined by the Swedish Initiative for submitting and requesting information complicates the information exchange as they are deemed to be cumbersome. Our project will simplify the procedure by offering new tools for the compilation of the forms but the main added value will be the semantic engine that will make the exchanged data more clear and informative. Although the semantic analysis tries to extract the maximum amount of information from the data, we are going to take special care to the effects of the project on individual rights and freedoms and offer, if necessary, all possible remedies in accordance to the legislation of each MS.
Current digital forensics tools are no longer adequate to meet the scope and complexity of today’s threats. Just as businesses use business intelligence solutions to monitor large amounts of customer data and watch for patterns that allow them to better understand customer behavior, investigators need similar solutions for large scale digital investigations. Finding anomalous patterns in massive data sets is crucial to spot possible evidences against criminals and prevent them for persisting in their criminal actions. In fact, due to the huge market penetration of datacenters and the rapid growth of the cloud providers, very large data storage forensic seizures are expected in the near future. Our project aims at building an intelligence solution for analyzing large unstructured data sets and gives to the investigator the ability to quickly retrieve information. We are going to rely on High Performance Computing (HPC) techniques to index and search huge amount of data that may include (but are not limited to) emails, documents, plain text file, web pages, etc.