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    DLL-Conscious Instruction Fetch Optimization for SMT Processors

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    Date
    2006-04-12
    Author
    Mohamood, Fayez
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    Abstract
    Simultaneous multithreading (SMT) processors can issue multiple instructions from distinct processes or threads in the same cycle. This technique effectively increases the overall throughput by keeping the pipeline resources more occupied at the potential expense of reducing single thread performance due to resource sharing. In the software domain, an increasing number of Dynamically Linked Libraries (DLL) are used by applications and operating systems, providing better flexibility and modularity, and enabling code sharing. It is observed that a significant amount of execution time in software today is spent in executing standard DLL instructions, that are shared among multiple threads or processes. However, for an SMT processor with a virtually-indexed based cache implementation, existing instruction fetching mechanisms can induce unnecessary false cache misses caused by the DLL-based instructions, which were intended to be shared. This problem is more conspicuous when multiple independent threads are executing concurrently in an SMT processor. This work investigates an often-neglected form of contention between running threads in the I-TLB and I-cache caused by DLLs. To address these shortcomings, we propose a system level technique involving a light-weight modification in the microarchitecture and the OS. By exploiting the nature of the DLLs in our new architecture, we are able to reinstate physical sharing of the DLLs in an SMT machine. Using Microsoft Windows based applications, our simulation results show that the optimized instruction fetching mechanism can reduce the number of DLL misses up to 5.5 times and improve the instruction cache hit rates by up to 62%, resulting in upto 30% DLL IPC improvements and upto 15% overall IPC improvements.
    URI
    http://hdl.handle.net/1853/10560
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    • Georgia Tech Theses and Dissertations [22398]
    • School of Electrical and Computer Engineering Theses and Dissertations [3127]

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