Automatic parallelization is the conversion of sequential code into multi-threaded code with little or no supervision. An ideal implementation of automatic parallelization would allow programmers to fully utilize available hardware resources to deliver optimal performance when writing code. Automatic parallelization has been studied for a long time, with one result being that modern compilers support vectorization without any input. In the study, contemporary parallelizing compilers are studied in order to determine whether or not they can easily be used in modern software development, and how code generated by them compares to manually parallelized code. Five compilers, ICC, Cetus, autoPar, PLUTO, and TC Optimizing Compiler are included in the study. Benchmarks are used to measure speedup of parallelized code, these benchmarks are executed on three different sets of hardware. The NAS Parallel Benchmarks (NPB) suite is used for ICC, Cetus, and autoPar, and PolyBench for the previously mentioned compilers in addition to PLUTO and TC Optimizing Compiler. Results show that parallelizing compilers outperform serial code in most cases, with certain coding styles hindering the capability of them to parallelize code. In the NPB suite, manually parallelized code is outperformed by Cetus and ICC for one benchmark. In the PolyBench suite, PLUTO outperforms the other compilers to a great extent, producing code not only optimized for parallel execution, but also for vectorization. Limitations in code generated by Cetus and autoPar prevent them from being used in legacy projects, while PLUTO and TC do not offer fully automated parallelization. ICC was found to offer the most complete automatic parallelization solution, although offered speedups were not as great as ones offered by other tools. / Automatisk parallellisering innebär konvertering av sekventiell kod till multitrådad kod med liten eller ingen tillsyn. En idealisk implementering av automatisk parallellisering skulle låta programmerare utnyttja tillgänglig hårdvara till fullo för att uppnå optimal prestanda när de skriver kod. Automatisk parallellisering har varit ett forskningsområde under en längre tid, och har resulterat i att moderna kompilatorer stöder vektorisering utan någon insats från programmerarens sida. I denna studie studeras samtida parallelliserande kompilatorer för att avgöra huruvida de lätt kan integreras i modern mjukvaruutveckling, samt hur kod som dessa kompilatorer genererar skiljer sig från manuellt parallelliserad kod. Fem kompilatorer, ICC, Cetus, autoPar, PLUTO, och TC Optimizing Compiler inkluderas i studien. Benchmarks används för att mäta speedup av paralleliserad kod. Dessa benchmarks exekveras på tre skiljda hårdvaruuppsättningar. NAS Parallel Benchmarks (NPB) används som benchmark för ICC, Cetus, och autoPar, och PolyBench för samtliga kompilatorer i studien. Resultat visar att parallelliserande kompilatorer genererar kod som presterar bättre än sekventiell kod i de flesta fallen, samt att vissa kodstilar begränsar deras möjlighet att parallellisera kod. I NPB så presterar kod parallelliserad av Cetus och ICC bättre än manuellt parallelliserad kod för en benchmark. I PolyBench så presterar PLUTO mycket bättre än de andra kompilatorerna och producerar kod som inte endast är optimerad för parallell exekvering, utan också för vektorisering. Begränsningar i kod genererad av Cetus och autoPar förhindrar användningen av dessa redskap i etablerade projekt, medan PLUTO och TC inte är kapabla till fullt automatisk parallellisering. Det framkom att ICC erbjuder den mest kompletta lösningen för automatisk parallellisering, men möjliga speedups var ej på samma nivå som för de andra kompilatorerna.

No description available.

Organic semiconductors (OSCs) present an electron mobility lower by several orders of magnitude than the hole mobility, giving rise to an electron-hole charge imbalance in organic devices such as organic light-emitting diodes (OLEDs) and organic light-emitting transistors (OLETs). In this thesis project, I tried to achieve an efficient electron transport and injection properties in opto-electronic devices, using inorganic n-type metal oxides (MOs) instead of organic n-type materials and a polyethyleneimine ethoxylated (PEIE) thin layer as electron transport (ETLs) and injection layers (EILs), respectively. In the first part of this thesis, inverted OLEDs were fabricated in order to study the effect of the PEIE layer in-between ZnO and two different emissive layers (EMLs): poly(9,9-dioctylfluorene-alt-benzothiadiazole) polymer (F8BT) and tris(8-hydroxyquinolinato) aluminum small molecule (Alq3), based on a solution and thermal evaporation processes, respectively. Different concentrations (0.80 %, 0.40 %) of PEIE layers were used to further study electron injection capability in OLEDs. After a series of optimizations in the fabrication process, the opto-electrical characterization showed high-performance of devices. The inverted OLEDs reported a maximum luminance over 104 cd m-2 and a maximum external quantum efficiency (EQE) around 1.11 %. The results were attributed to the additional PEIE layer which provided a good electron injection from MOs into EMLs. In the last part of the thesis, OLETs were fabricated and discussed by directly transferring the energy modification layer from OLEDs to OLETs. As metal oxide layer, ZnO:N was employed for OLETs since ZnO:N-based thin film transistors (TFTs) showed better performance than ZnO-based TFTs. Finally, due to their short life-time, OLETs were characterized electrically but not optically.