Master Degree / Yüksek Lisans Tezleri
Permanent URI for this collectionhttps://hdl.handle.net/11147/3008
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Master Thesis Compiler-Managed Fault Tolerance Techniques for General Purpose Graphics Processing Units(Izmir Institute of Technology, 2022) Kaya, Ercüment; Öz, Işıl; Öz, IşılAs the use of graphics processing units evolves for general-purpose computations besides inherently-fault tolerant graphics programs, soft error reliability becomes a first-class citizen in program design. In this thesis, we aim to increase the reliability of general-purpose graphics processing units. We propose compiler-based redundancy schemes for graphics processing units. Our framework replicates the annotated kernel function by a programmer at compile time. Our selective redundancy approach enables us to provide full redundancy with no error and partial redundancy with an acceptable error rate with higher performance. We develop different schemes to satisfy the performance and memory requirements of the general-purpose graphics processing unit applications. We build our framework on top of the LLVM compiler framework to increase the reliability of applications that exploit the CUDA programming model and evaluate our schemes for the applications from the PolyBench benchmark suite. We reveal that our partial redundancy approach improves the reliability with a small performance overhead and our full redundancy schemes provide complete fault coverage with varying performance differences based on the application's characteristics.Master Thesis Parallelization of a Novel Frequent Itemset Hiding Algorithm on a Cpu-Gpu Platform(Izmir Institute of Technology, 2014) Heye, Samuel Bacha; Ayav, Tolga; Ayav, TolgaData mining is used to extract useful information from large data. But the organizations which mine the data might not be the owner of the data. So, before the owners can make their data accessible for data mining they want to make sure that no sensitive information can be mined from the released data whose discovery by others might harm them. Itemset hiding is one mechanism to prevent the disclosure of sensitive itemsets. In this thesis, a new integer programing based itemset hiding algorithm was developed and a mechanism to speed up the computation time of its implementation was proposed by using parallel computation on Graphical Processing Units (GPUs).