Memory hierarchy and data communication in heterogeneous reconfigurable SoCs

The miniaturization race in the hardware industry aiming at continuous increasing of transistor density on a die does not bring respective application performance improvements any more. One of the most promising alternatives is to exploit a heterogeneous nature of common applications in hardware. Supported by reconfigurable computation, which has already proved its efficiency in accelerating data intensive applications, this concept promises a breakthrough in contemporary technology development. Memory organization in such heterogeneous reconfigurable architectures becomes very critical. Two primary aspects introduce a sophisticated trade-off. On the one hand, a memory subsystem should provide well organized distributed data structure and guarantee the required data bandwidth. On the other hand, it should hide the heterogeneous hardware structure from the end-user, in order to support feasible high-level programmability of the system. This thesis work explores the heterogeneous reconfigurable hardware architectures and presents possible solutions to cope the problem of memory organization and data structure. By the example of the MORPHEUS heterogeneous platform, the discussion follows the complete design cycle, starting from decision making and justification, until hardware realization. Particular emphasis is made on the methods to support high system performance, meet application requirements, and provide a user-friendly programmer interface. As a result, the research introduces a complete heterogeneous platform enhanced with a hierarchical memory organization, which copes with its task by means of separating computation from communication, providing reconfigurable engines with computation and configuration data, and unification of heterogeneous computational devices using local storage buffers. It is distinguished from the related solutions by distributed data-flow organization, specifically engineered mechanisms to operate with data on local domains, particular communication infrastructure based on Network-on-Chip, and thorough methods to prevent computation and communication stalls. In addition, a novel advanced technique to accelerate memory access was developed and implemented.

Development of Original Analytical Methods for the Determination of Drugs of Abuse in Biological Samples

Drug abuse is a major global problem which has a strong impact not only on the single individual but also on the entire society. Among the different strategies that can be used to address this issue an important role is played by identification of abusers and proper medical treatment. This kind of therapy should be carefully monitored in order to discourage improper use of the medication and to tailor the dose according to the specific needs of the patient. Hence, reliable analytical methods are needed to reveal drug intake and to support physicians in the pharmacological management of drug dependence. In the present Ph.D. thesis original analytical methods for the determination of drugs with a potential for abuse and of substances used in the pharmacological treatment of drug addiction are presented. In particular, the work has been focused on the analysis of ketamine, naloxone and long-acting opioids (buprenorphine and methadone), oxycodone, disulfiram and bupropion in human plasma and in dried blood spots. The developed methods are based on the use of high performance liquid chromatography (HPLC) coupled to various kinds of detectors (mass spectrometer, coulometric detector, diode array detector). For biological sample pre-treatment different techniques have been exploited, namely solid phase extraction and microextraction by packed sorbent. All the presented methods have been validated according to official guidelines with good results and some of these have been successfully applied to the therapeutic drug monitoring of patients under treatment for drug abuse.

Social network e capitale sociale degli ex-ospiti di Comunita' Liberta': Drug free e ricaduti a confronto

L'indagine condotta, avvalendosi del paradigma della social network analysis, offre una descrizione delle reti di supporto personale e del capitale sociale di un campione di 80 italiani ex post un trattamento terapeutico residenziale di lungo termine per problemi di tossicodipendenza. Dopo aver identificato i profili delle reti di supporto sociale degli intervistati, si è proceduto, in primis, alla misurazione e comparazione delle ego-centered support networks tra soggetti drug free e ricaduti e, successivamente, all'investigazione delle caratteristiche delle reti e delle forme di capitale sociale – closure e brokerage – che contribuiscono al mantenimento dell'astinenza o al rischio di ricaduta nel post-trattamento. Fattori soggettivi, come la discriminazione pubblica percepita e l'attitudine al lavoro, sono stati inoltre esplorati al fine di investigare la loro correlazione con la condotta di reiterazione nell'uso di sostanze. Dai risultati dello studio emerge che un più basso rischio di ricaduta è positivamente associato ad una maggiore attitudine al lavoro, ad una minore percezione di discriminazione da parte della società, all'avere membri di supporto con un più alto status socio-economico e che mobilitano risorse reputazionali e, infine, all'avere reti più eterogenee nell'occupazione e caratterizzate da più elevati livelli di reciprocità. Inoltre, il capitale sociale di tipo brokerage contribuisce al mantenimento dell'astinenza in quanto garantisce l'accesso del soggetto ad informazioni meno omogenee e la sua esposizione a opportunità più numerose e differenziate. I risultati dello studio, pertanto, dimostrano l'importante ruolo delle personal support networks nel prevenire o ridurre il rischio di ricaduta nel post-trattamento, in linea con precedenti ricerche che suggeriscono la loro incorporazione nei programmi terapeutici per tossicodipendenti.