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• W2972607526 abstract "Multiprocessor systems on a chip consisting of integrated CPUs and GPUs are suitable platforms for real-time embedded applications requiring massively parallel processing. For such applications, lifetime reliability due to permanent faults and soft-error reliability due to transient faults are major concerns. Detailed execution profiling has revealed that a CUDA task's CPU execution time significantly increases if the task executes on a different core than the operating system (OS). Based on this observation, an extended task model is introduced to consider the execution time dependencies among tasks and the OS. A hybrid framework is proposed to improve soft-error reliability while satisfying a lifetime reliability constraint for soft real-time systems executing on integrated CPU and GPU platforms. This framework: 1) reduces the total utilization of cores and improves soft-error reliability via off-line task mapping; 2) achieves a higher lifetime reliability through task migration at run time; and 3) improves soft-error reliability by dynamically scaling frequencies of CPU and GPU cores. The experimental results show that the proposed framework leads to a system that can execute without soft errors for at least 4 days (4 times) and 6 days (6 times) longer, on average, than existing approaches." @default.
• W2972607526 created "2019-09-19" @default.
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• W2972607526 date "2020-10-01" @default.
• W2972607526 modified "2023-10-11" @default.
• W2972607526 title "Improving Reliability of Soft Real-Time Embedded Systems on Integrated CPU and GPU Platforms" @default.
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• W2972607526 doi "https://doi.org/10.1109/tcad.2019.2940681" @default.
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