2012
DOI: 10.1016/j.compeleceng.2011.09.009
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An efficient scheduler of RTOS for multi/many-core system

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Cited by 7 publications
(6 citation statements)
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“…We also plan to study the possibility of extending USG to supercomputing and cloud computing, as has been presented in [29,30].…”
Section: Resultsmentioning
confidence: 98%
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“…We also plan to study the possibility of extending USG to supercomputing and cloud computing, as has been presented in [29,30].…”
Section: Resultsmentioning
confidence: 98%
“…LLF fails to schedule the above-mentioned example because task T 3 can only take the processor in the intervals [9,10], [19,20], and [29,30] before it can be prioritized over T 1 and T 2 at time t = 36, when it will have zero laxity. Therefore, T 3 will be executed to completion before its deadline at time t = 40.…”
Section: Examplementioning
confidence: 93%
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“…It does not support manual task switching through any system calls. It will considerably increase the overhead by changing work-item task priority or through synchronization module such as semaphore [8] to allow expected execution sequence. Task schedule overhead is heavy when using DSP/BIOS kernel, and it involves task stack change and context switch.…”
Section: Second Level Rtos Schedulermentioning
confidence: 99%
“…It is a challenging task to support OpenCL program model on multicore DSP for embedded application. We address this problem by firstly utilizing the LLVM (low level virtual machine) [5] and Clang [6] open source compiler to support kernel compilation and further optimization for the DSP platform; then we designed 2 Advances in Mechanical Engineering [7,8] scheduler that aimed to schedule work-item in a work group to decrease the task switching overhead. Finally, we proposed a kind of software managed CACHE method to efficiently administrate the distributed global memory which was combined through interconnections such as PCIE, SRIO (serial rapid IO), Hyperlink, and SGMII.…”
Section: Introductionmentioning
confidence: 99%