EDACs and test integration strategies for NAND flash memories

Mission-critical applications usually presents several critical issues: the required level of dependability of the whole mission always implies to address different and contrasting dimensions and to evaluate the tradeoffs among them. A mass-memory device is always needed in all mission-critical applications: NAND flash-memories could be used for this goal. Error Detection And Correction (EDAC) techniques are needed to improve dependability of flash-memory devices. However also testing strategies need to be explored in order to provide highly dependable systems. Integrating these two main aspects results in providing a fault-tolerant mass-memory device, but no systematic approach has so far been proposed to consider them as a whole. As a consequence a novel strategy integrating a particular code-based design environment with newly selected testing strategies is presented in this pape

Berkeley Packet Filter: theory, practice and perspectives

Inizialmente in molte versioni di Unix il meccanismo di filtraggio dei pacchetti era implementato nello spazio utente, richiedendo la copia di ogni pacchetto dallo spazio kernel, prima di essere filtrato. L'introduzione di BPF ha permesso di migliorare la performance consentendo il filtraggio dei pacchetti direttamente nel kernel space. La prima implementazione, classic BPF (cBPF) permette di iniettare dallo spazio utente codice assembly per la macchina virtuale che risiede nel kernel, in modo che il programmatore possa scrivere filtri personalizzati. L' utilizzo di cBPF e' stato esteso anche al filtraggio delle system call tramite l'implementazione di seccomp che sfrutta la stessa sintassi ma per agire su una struttura dati che rappresenta la system call eseguita, invece che il pacchetto di rete. Successivamente la macchina virtuale e' stata riscritta sia per adeguarla alle innovazioni riguardanti l'architettura dei moderni processori (e.g. piu' registri, piu' istruzioni) sia con lo scopo di aggiungere ulteriori funzionalita'. La nuova implementazione prende il nome di extended BPF (eBPF) e prevede molte piu' tipologie di programmi, la possibilita' di utilizzare mappe per la comunicazione tra user space e kernel space, la possibilita' di chiamare da un programma BPF altri programmi BPF o un sottoinsieme di funzioni del kernel chiamate helpers, nonche' la possibilita' di fissare alcuni oggetti in un file system virtuale in modo da poterli recuperare successivamente. Il supporto eBPF per seccomp non e' stato introdotto sebbene vi siano state alcune patch proposte. Il seguente lavoro di tesi ha l'obiettivo di introdurre cBPF ed eBPF, sia a livello teorico descrivendone le componenti, che pratico tramite la creazione di un repository github ed di una documentazione tecnica ed infine di analizzare alcuni aspetti relativi a seccomp

A cDNA Microarray Gene Expression Data Classifier for Clinical Diagnostics Based on Graph Theory

Despite great advances in discovering cancer molecular profiles, the proper application of microarray technology to routine clinical diagnostics is still a challenge. Current practices in the classification of microarrays' data show two main limitations: the reliability of the training data sets used to build the classifiers, and the classifiers' performances, especially when the sample to be classified does not belong to any of the available classes. In this case, state-of-the-art algorithms usually produce a high rate of false positives that, in real diagnostic applications, are unacceptable. To address this problem, this paper presents a new cDNA microarray data classification algorithm based on graph theory and is able to overcome most of the limitations of known classification methodologies. The classifier works by analyzing gene expression data organized in an innovative data structure based on graphs, where vertices correspond to genes and edges to gene expression relationships. To demonstrate the novelty of the proposed approach, the authors present an experimental performance comparison between the proposed classifier and several state-of-the-art classification algorithm

Gene expression classifiers and out-of-class samples detection

The proper application of statistics, machine learning, and data-mining techniques in routine clinical diagnostics to classify diseases using their genetic expression profile is still a challenge. One critical issue is the overall inability of most state-of-the-art classifiers to identify out-of-class samples, i.e., samples that do not belong to any of the available classes. This paper shows a possible explanation for this problem and suggests how, by analyzing the distribution of the class probability estimates generated by a classifier, it is possible to build decision rules able to significantly improve its performance

FLARE: A design environment for FLASH-based space applications

Designing a mass-memory device (i.e., a solid-state recorder) is one of the typical issues of mission-critical space system applications. Flash-memories could be used for this goal: a huge number of parameters and trade-offs need to be explored. Flash-memories are nonvolatile, shock-resistant and power-economic, but in turn have different drawback: e.g., their cost is higher than normal hard disk and the number of erasure cycles is bounded. Moreover space environment presents various issues especially because of radiations: different and quite often contrasting dimensions need to be explored during the design of a flash-memory based solid-state recorder. No systematic approach has so far been proposed to consider them all as a whole: as a consequence a novel design environment currently under development is aimed at supporting the design of flash-based mass-memory device for space application

Flash-memories in Space Applications: Trends and Challenges

Nowadays space applications are provided with a processing power absolutely overcoming the one available just a few years ago. Typical mission-critical space system applications include also the issue of solid-state recorder(s). Flash-memories are nonvolatile, shock-resistant and power-economic, but in turn have different drawbacks. A solid-state recorder for space applications should satisfy many different constraints especially because of the issues related to radiations: proper countermeasures are needed, together with EDAC and testing techniques in order to improve the dependability of the whole system. Different and quite often contrasting dimensions need to be explored during the design of a flash-memory based solid- state recorder. In particular, we shall explore the most important flash-memory design dimensions and trade-offs to tackle during the design of flash-based hard disks for space application

Exploring Design Dimensions in Flash-based Mass-memory Devices

Mission-critical space system applications present several issues: a typical one is the design of a mass-memory device (i.e., a solid- state recorder). This goal could be accomplished by using flash- memories: the exploration of a huge number of parameters and trade-offs is needed. On the one hand flash-memories are nonvolatile, shock-resistant and power-economic, but on the other hand their cost is higher than normal hard disk, the number of erasure cycles is bounded and other different drawbacks have to be considered. In addition space environment presents various issues especially because of radiations: the design of a flash- memory based solid-state recorder implies the exploration of different and quite often contrasting dimensions. No systematic approach has so far been proposed to consider them all as a whole: as a consequence the design of flash-based mass-memory device for space applications is intended to be supported by a novel design environment currently under development and refinemen

Design Issues and Challenges of File Systems for Flash Memories

This chapter discusses how to properly address the issues of using NAND flash memories as mass-memory devices from the native file system standpoint. We hope that the ideas and the solutions proposed in this chapter will be a valuable starting point for designers of NAND flash-based mass-memory devices

GPU acceleration for statistical gene classification

The use of Bioinformatic tools in routine clinical diagnostics is still facing a number of issues. The more complex and advanced bioinformatic tools become, the more performance is required by the computing platforms. Unfortunately, the cost of parallel computing platforms is usually prohibitive for both public and small private medical practices. This paper presents a successful experience in using the parallel processing capabilities of Graphical Processing Units (GPU) to speed up bioinformatic tasks such as statistical classification of gene expression profiles. The results show that using open source CUDA programming libraries allows to obtain a significant increase in performances and therefore to shorten the gap between advanced bioinformatic tools and real medical practic

Differential gene expression graphs: A data structure for classification in DNA microarrays

This paper proposes an innovative data structure to be used as a backbone in designing microarray phenotype sample classifiers. The data structure is based on graphs and it is built from a differential analysis of the expression levels of healthy and diseased tissue samples in a microarray dataset. The proposed data structure is built in such a way that, by construction, it shows a number of properties that are perfectly suited to address several problems like feature extraction, clustering, and classificatio