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2013/12/09 Yun-Chung Yang Partitioning and Allocation of Scratch-Pad Memory for Priority-Based Preemptive Multi-Task Systems Takase, H. ; Tomiyama, H.

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Presentation on theme: "2013/12/09 Yun-Chung Yang Partitioning and Allocation of Scratch-Pad Memory for Priority-Based Preemptive Multi-Task Systems Takase, H. ; Tomiyama, H."— Presentation transcript:

1 2013/12/09 Yun-Chung Yang Partitioning and Allocation of Scratch-Pad Memory for Priority-Based Preemptive Multi-Task Systems Takase, H. ; Tomiyama, H. ; Takada, H. Design, Automation & Test in Europe Conference & Exhibition (DATE), 2010 Page(s): 1124 - 1129

2 Abstract Related Work What’s the Problem Proposed Method Experiment Result Conclusion 2

3 Scratch-pad memory has been employed as a partial or entire replacement for cache memory due to its better energy efficiency. In this paper, we propose scratch-pad memory management techniques for priority-based preemptive multi-task systems. Our techniques are applicable to a real- time environment. The three methods which we propose, i.e., spatial, temporal, and hybrid methods, bring about effective usage of the scratch-pad memory space, and achieve energy reduction in the instruction memory subsystems. 3

4 We formulate each method as an integer programming problem that simultaneously determines (1) partitioning of scratch-pad memory space for the tasks, and (2) allocation of program code to scratch-pad memory space for each task. It is remarkable that periods and priorities of tasks are considered in the formulas. Additionally, we implement a RTOS-hardware cooperative support mechanism for a runtime code allocation to the scratch-pad memory space. We have made the experiments with the fully functional real-time operating system. The experimental results with four task sets have demonstrated the effectiveness of our techniques. Up to 73 % energy reduction compared to a standard method was achieved. 4

5 5 Code Allocation Using Algorithm [2], [3], [5] For multi-task Single Task Manage content of SPM [4], [6] [8], [9] This paper [7] [10], [11], [12] [2] various size [3] compiler [5] data-cache conflicts Allocation using integer programming depends on energy Not for hard real-time system Hardware for efficient allocation at runtime

6 Cache is one of the most energy-components in SoC.  SPM attracts attention with better energy efficient than cache. The previous idea of SPM allocation  Based on soft real-time system. Solution : Propose a SPM allocation for hard real-time.

7 Three method for SPM partition and code allocation. Each method is formulated as an integer programming problem.  Spatial 。 Each task has exclusive space  Temporal 。 Running task has the entire SPM space  Hybrid 。 Spatial idea, the higher priority of task can temporally use the space of lower priority task.

8 8 Profiler using instruction-level simulator (SkyEye). Modify to the Kernel scheduler for SPM support.

9 9 X i,j denotes a binary variable, 1 => func i,j allocate to SPM. fetch i,j total number of instruction in func i,j per execution. Hyperperiod – The LCM of task period. Compute energy consumption for each task SPM allocation

10 10 Compute Energy consumption!

11 11 Spatial Temporal Priority

12 Energy consumption Total execution time

13 13

14 Energy reduction Hybrid & Temporal reduced more energy than Spatial  Effective code replacement, no more than 5% overhead. Set A has different program characteristic.  Mostly automotive program => processing straightforward. 14 MaximumAverage Spatial Method 33%18% Temporal Method 69%38% Hybrid Method 73%41%

15 Proposed three method  Spatial, temporal, hybrid Remarkable for task period and priorities are utilized. Dynamic code allocation for RTOS and hardware. My comment  Knowing the future work on improvement. 。 SPM size could be a parameter in integer programming problem.  Doesn’t have execution time comparison to original. 15


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