<p> Concurrent Computing has certain interesting links with Algebraic Topology. There are various geometric models for concurrent computing. We examine one geometric approach to modeling concurrency, via the notion of a locally partially ordered space. We examine a notion analogous to that of homotopy, called dihomotopy, that is compatible with a local partial order. In the category of locally partially ordered spaces and di-maps we examine the isomorphisms, which are called di-homeomorphisms. We classify all di-homeomorphic embeddings of the unit square into the Euclidean plane.</p> / Thesis / Master of Science (MSc)

Somatic Copy Number Alterations (CNAs) are common events in human cancers. Identifying CNAs and Significant Copy number Aberrations (SCAs) in cancer genomes is a critical task in searching for cancer-associated genes. Advanced genome profiling technologies, such as SNP array technology, facilitate copy number study at a genome-wide scale with high resolution. However, due to normal tissue contamination, the observed intensity signals are actually the mixture of copy number signals contributed from both tumor and normal cells. This genetic confounding factor would significantly affect the subsequent copy number analyses. In order to accurately identify significant aberrations in contaminated cancer genome, we develop a Java AISAIC package (Accurate Identification of Significant Aberrations in Cancer) that incorporates recent novel algorithms in the literature, BACOM (Bayesian Analysis of Copy number Mixtures) and SAIC (Significant Aberrations in Cancer). Specifically, BACOM is used to estimate the normal tissue contamination fraction and recover the "true" copy number profiles. And SAIC is used to detect SCAs using large recovered tumor samples. Considering the popularity of modern multi-core computers and clusters, we adopt concurrent computing using Java Fork/Join API to speed up the analysis. We evaluate the performance of the AISAIC package in both empirical family-wise type I error rate and detection power on a large number of simulation data, and get promising results. Finally, we use AISAIC to analyze real cancer data from TCGA portal and detect many SCAs that not only cover majority of reported cancer-associated genes, but also some novel genome regions that may worth further study. / Master of Science

Memory management errors in concurrent software running on multi-core architectures can be difficult and costly to detect and repair. Examples of errors are usage of uninitialized memory, memory leaks, and data corruptions due to unintended overwrites of data that are not owned by the writing entity. If memory management errors could be detected at an early stage, for example when using a simulator before the software has been delivered and integrated in a product, significant savings could be achieved. This thesis investigates and develops methods for detection of usage of uninitialized memory in software that runs on a virtual hardware platform. The virtual hardware platform has models of Ericsson Radio Base Station hardware for baseband processing and digital radio processing. It is a bit-accurate representation of the underlying hardware, with models of processors and peripheral units, and it is used at Ericsson for software development and integration. There are tools available, such as Memcheck (Valgrind), and MemorySanitizer and AddressSanitizer (Clang), for memory management error detection. The features of such tools have been investigated, and memory management error detection algorithms were developed for a given processor’s instruction set. The error detection algorithms were implemented in a virtual platform, and issues and design considerations reflecting the application-specific instruction set architecture of the processor, were taken into account. A prototype implementation of memory error presentation with error locations mapped to the source code of the running program, and presentation of stack traces, was done, using functionality from a debugger. An experiment, using a purpose-built test program, was used to evaluate the error detection capability of the algorithms in the virtual platform, and for comparison with the error detection capability of Memcheck. The virtual platform implementation detects all known errors, except one, in the program and reports them to the user in an appropriate manner. There are false positives reported, mainly due to the limited awareness about the operating system used on the simulated processor / Minneshanteringsfel i parallell mjukvara som exekverar på flerkärniga arkitekturer kan vara svåra att detektera, samt kostsamma att åtgärda. Exempel på fel kan vara användning av ej initialiserat minne, minnesläckage, samt att data blir överskrivna av en process som inte är ägare till de data som skrivs över. Om minneshanteringsfel kan detekteras i ett tidigt skede, t ex genom att använda en simulator, som körs innan mjukvaran har levererats och integrerats i en produkt, skulle man kunna erhålla signifikanta kostnadsbesparingar. Detta examensarbete undersöker och utvecklar metoder för detektion av ej initialiserat minne i mjukvara som körs på en virtuell plattform. Den virtuella plattformen innehåller modeller av delar av den digitala hårdvara, för basband och radio, som finns i en Ericsson radiobasstation. Modellerna är bit-exakta representationer av motsvarande hårdvarublock, och innefattar processorer och periferienheter. Den virtuella plattformen används av Ericsson för utveckling och integration av mjukvara. Det finns verktyg, exempelvis Memcheck (Valgrind), samt MemorySanitizer och AddressSanitizer (Clang), som kan användas för att detektera minneshanteringsfel. Egenskaper hos sådana verktyg har undersökts, och algoritmer för detektion av minneshanteringsfel har utvecklats, för en specifik processor och dess instruktioner. Algoritmerna har implementerats i en virtuell plattform, och kravställningar och design-överväganden som speglar den tillämpnings-specifika instruktionsrepertoaren för den valda processorn, har behandlats. En prototyp-implementation av presentation av minneshanteringsfel, där källkodsraderna samt anropsstacken för de platser där fel har hittats pekas ut, har utvecklats, med användning av en debugger. Ett experiment, som använder sig av ett för ändamålet utvecklat program, har använts för att utvärdera feldetektions-förmågan för de algoritmer som implementerats i den virtuella plattformen, samt för att jämföra med feldetektions-förmågan hos Memcheck. De algoritmer som implementerats i den virtuella plattformen kan, för det program som används, detektera alla kända fel, förutom ett. Algoritmerna rapporterar också falska felindikeringar. Dessa rapporter är huvudsakligen ett resultat av att den aktuella implementationen har begränsad kunskap om det operativsystem som används på den simulerade processorn.