Master Degree / Yüksek Lisans Tezleri
Permanent URI for this collectionhttps://hdl.handle.net/11147/3008
Browse
2 results
Search Results
Master Thesis Evaluating Impacts of Micro-Architectural Metrics on Error Resilience and Performance of General Purpose Gpu Applications(01. Izmir Institute of Technology, 2023) Topçu, Burak; Öz, IşılRapidly growing data processing tasks require powerful and energy-efficient heterogeneous computing systems, and GPUs take on a significant mission for those systems in accelerating heavy workloads by executing multiple parallel tasks concurrently. Increasing architectural complexity and widening employment of GPUs bring error resiliency concerns for safety-critical applications. Furthermore, approaches that enhance performance and reduce energy dissipation handle error resiliency on GPUs through approximate computing solutions. Evaluating error resiliency in terms of either identifying error proneness of a system or investigating approximations without much disturbing the output necessities robust knowledge about the execution of a program on a device. In this thesis, we develop a runtime performance and power monitoring tool visualizing the execution with detailed micro-architectural metrics. By utilizing the tool, we acquire several fundamental understandings about runtime performance bottlenecks and how perturbations affect output quality. Afterward, we propose a framework predicting fault vulnerability for error-resilient GPU applications. The framework can accurately estimate error tolerance and saves from analyzing the fault occurrence probability requiring significant effort. Depending on the performance bottlenecks observed with the tool and the error propagation gained during prediction experiments, we introduce a hardware-based approximation computing approach targeting to improve the performance and power of GPU programs, especially memory-bound ones. The approximation method, which resolves memory utilization bottlenecks at runtime, enhances performance by 1.49× (up to 2.1×) and diminishes energy consumption by 28.4% (up to 52.6%) while maintaining the accuracy on the output above 98%.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.