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| Content Provider | ACM Digital Library |
|---|---|
| Author | Chen, Jian-Jia Chang, Che-Wei Falk, Heiko Kuo, Tei-Wei Munawar, Waqaas |
| Abstract | This work is motivated by the advance of multiprocessor system architecture, in which the allocation of tasks over heterogeneous memory modules has a significant impact on the task execution. By considering two different types of memory modules with different access latencies, this paper explores joint considerations of memory allocation and real-time task scheduling to minimize the maximum utilization of processors of the system. For implicit-deadline sporadic tasks, a two-phase algorithm is developed, where the first phase determines memory allocation to derive a lower bound of the maximum utilization, and the second phase adopts worst-fit partitioning to assign tasks. It is shown that the proposed algorithm leads to a tight $(2-⁄^{2}_{M+1})-approximation$ bound where M is the number of processors. The proposed algorithm is then evaluated with 82 realistic benchmarks from MRTC, MediaBench, UTDSP, NetBench and DSPstone, and extensive simulations are further conducted to analyze the proposed algorithm. |
| Starting Page | 153 |
| Ending Page | 162 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781450314251 |
| DOI | 10.1145/2380356.2380384 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2012-10-07 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Shared sram Multiprocessor partitioned scheduling Approximation algorithms Real-time systems |
| Content Type | Text |
| Resource Type | Article |
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