10 likes | 97 Views
T5_1. T5_1. T5_1. T5_1. T5_1. Reusable Schedule. Idle Time. Mapping. Idle [ ECU1, T5_2]. Assumptions. Task: 6-tuple parameter variable Vector. Message: 5-tuple parameter variable Vector. Reusability Scalability Jointly Reusability & Scalability. The set of Tasks
E N D
T5_1 T5_1 T5_1 T5_1 T5_1 Reusable Schedule Idle Time Mapping Idle[ ECU1, T5_2] Assumptions Task: 6-tuple parameter variable Vector Message: 5-tuple parameter variable Vector • Reusability • Scalability • Jointly Reusability & Scalability • The set of Tasks • The set of ECU • Task pair with data dependency running on the same ECU • Task pair with data dependency running on different ECU • Non-reachable task pair running on the same ECU • The set of task pair running on the same ECU • The set of task allocation for ECU Describe the Metric Case study T1 T2 T5 • Tasks data Dependency • Hard Deadline mustbe satisfied • Deadline is equal to Period • Legacy tasks can be taken into account • Multi-Rate System • Allow preemption for Tasks • Bus is modeled as a non-preemptive node • Sw-Hw mapping is given • WCET • Release Time • Period • Idle time • Starting time • Finishing time • WCTT • Left Slack • Right Slack • Starting time • Finishing time T3 T4 Automatic AMPL data file generation AMPL model with cost function and constraints Reusable Schedule---WCET Changes T5_2 T5_1 T5_2 T5_2 T5_1 Task graph expansion (in a SUPERperiod) T6 D 12_1 D 12_1 D 12_1 D 12_1 Formula cost fn in AMPL Jointly Considering Reusable and Scalable architecture functionality T3 T3 T3 T3 T3 T3 T3 T3 T3 Slack[ D12_2, T2_2] Data Slacks D 34 D 34 WCET Increase AMPL solver T5_1 T5_2 T5_2 T5_2 T5_2 T5_1 T5_2 T5_2 Checking Schedulability Minimize End to End Latency Reusability Scalability T4 T4 T4 T4 T4 T4 T4 T6 T4 T4 Idle time for task i Get Scheduling Result ECU2 ECU1 • Tolerate changes of Tasks’ WCET • Tolerate changes of Data’ WCTT • Maintains Bus Schedule • Maintains non-involved ECU schedules • Maintains involved ECU schedules without re-configuration • Message left & Right slack • Max Sum of all slacks • Min Variance of all slacks • Accommodate NEW tasks on legacy system • Provide blocks of computation time for future computation intensive tasks • Provide porosity in schedules to allow for future tasks with tight deadlines • idle time distribution on ECU • Evenly distribute idle time Motivation D 34 D 34 D 34 D 34 D 34 D 34 D 34 Automatic Gant graph generation Idle time for ECU k before the super period T2 T2 T1 T1 otherwise T5 T1_2 T1_2 T1_1 T1_2 T1_1 T1_2 T1_1 T1_2 T1_1 T1_1 T1_2 T1_1 T1_1 T1_1 T1_2 T1_2 T1_2 T1_1 T5 ECU1 ECU1 ECU1 ECU1 ECU1 ECU1 ECU1 ECU1 ECU1 if task i is not preempted by task j Scalable Schedule Scalable Schedule: Add New Task Implementation T3 T4 otherwise ECU2 ECU2 ECU2 ECU2 ECU2 ECU2 ECU2 ECU2 ECU2 Evaluate Result w.r.t. Metrics T2_2 T2_1 T2_1 T2_2 T2_1 T2_1 T2_2 T2_2 T2_2 T2_2 T2_1 T2_1 T2_1 T2_1 T2_1 T2_2 T2_2 T2_2 FlexRay Data from i to task j precedes data from task k to l Bus Bus Bus Bus Bus Bus Bus Bus Bus Off-the-shelfproject infrastructure Self-developed project infrastructure Time Time Time Time Time Time Time Time Time otherwise 4 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 . . Approach D 12_1 D 12_2 D 12_1 D 12_1 D 12_1 D 12_2 D 12_2 D 12_2 D 12_1 D 12_2 D 12_2 D 12_2 D 12_2 D 12_2 Wei Zheng Mentor: Claudio Pinello Sri Kanajan Advisor: Alberto Sangiovanni-Vincentelli Reusability and Scalability Time Triggered Scheduling of http://chess.eecs.berkeley.edu/gm Problem Background Motivation Design a task and bus scheduling tool that works with the automotive design process and captures the constraints that the automotive domain has. This project will explore metrics which can characterize the scalability and reusability of the distributed embedded system, and through solving a mixed integer quadratic programming to schedule functionality on a given architecture so that certain design constraints are satisfied. Problem Description Reusability and Scalability Problem Formulation Notation, Parameters and Variables Objective Function Constraints Tool Infrastructure Simple Case Study • Initial Results Release and Deadline Constraints Execution Time/Transmission Constraints Precedence Constraints Mutual Exclusion Constraints Idle Time Constraints November 18, 2004