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Operating Systems for Reconfigurable Embedded Platforms: Online Scheduling of Real-Time Tasks

Operating Systems for Reconfigurable Embedded Platforms: Online Scheduling of Real-Time Tasks. Jinxu Ding Ramón Mercado. Outline. Introduction Models and Limitations Design Issues of Operating System Task and Resource Management Results and Conclusion. Introduction. The past of FPGAS

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Operating Systems for Reconfigurable Embedded Platforms: Online Scheduling of Real-Time Tasks

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  1. Operating Systems for Reconfigurable Embedded Platforms:Online Scheduling of Real-Time Tasks Jinxu Ding Ramón Mercado

  2. Outline • Introduction • Models and Limitations • Design Issues of Operating System • Task and Resource Management • Results and Conclusion Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  3. Introduction • The past of FPGAS • Rapid prototyping and emulation. • FPGAs replacing ASIC • reconfigurable hardware enables shorter time-to-market and updating after product deployment. • Today’s FPGA characteristics that allow for more dynamic applications: • Higher densities. • Integrate processors, memories and special function blocks. • Partial reconfiguration. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  4. Introduction (cont) • Reconfigurable Embedded Systems • High performance demands. • Frequent changes of their workloads. • Some applications: • Wearable computing, mobile system, network processors, etc. • The functions and their execution time are not known in advance. • Classical design process (i.e. complete design-time synthesis and optimization) is not enough for this systems. • This systems demand partial reconfiguration to meet their require degree of flexibility. • Multitasking Reconfigurable Hardware Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  5. IntroductionMultitasking Reconfigurable Hardware • Programming Model • Define the executable objects, their interaction and provides the developer with a set of well-defined system services. • Runtime System • Efficiently operates the system and resolves conflicts between the executable objects. • Reconfigurable Hardware Operating System • Programming model + runtime system. • Similar to an RTOS, but for partially reconfigurable hardware. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  6. IntroductionRTOS and RHOS Programming model: • Real-time task (RTOS), smallest executable unit. • This are task that have a deadline. This task not only need to produce a result, but the must do it in a specific amount of time. • Periodic or Aperiodic. • Hardware Task (RHOS), smallest executable unit. • This task, HW tasks, also have deadlines and can be periodic or aperiodic. • BUT they also have an area constrain. Run-time system: • Scheduling (RTOS) • Guarantee-based: Every task that is admitted is guaranteed by the scheduler to meet its deadline. • Acceptance Test • Scheduling (RHOS) • Also guarantee-based, but in this case the task is guaranteed that there will be space (area) for it to completely execute before its deadline. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  7. IntroductionThe Problem • Guarantee-based online scheduling of real-time tasks to partially reconfigurable hardware. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  8. Models and Limitations Device Model • For our purposes, the device (FPGA) is modeled as a rectangle of width (W) and height (H). • This rectangle is further divided into uniform sections of usable area. Any task scheduled will use an integer amount of these sections. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  9. Models and LimitationsHardware Task Model • Executable objects of our model, formal definition. • Aperiodic • Configurations are known a-priori • Preplaced and prerouted • Stored in a position-independent manner • Tasks are defined by {Ri, Ei, Di, Wi x Hi} • Ri – Ready time • Ei – Worst case execution time • Di – Deadline • Wi – Size along x-coordinate • Hi – Size along y-coordinate Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  10. Models and LimitationsArea Model • 1D – hardware tasks can be allocated anywhere along the horizontal dimension (x) • 2D – hardware tasks can be allocated anywhere on the device (x, y) Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  11. Models and LimitationsArea Model (cont) • 1D area model suffers from 2 types of external fragmentations • Type A • Type B • 2D suffers less from external fragmentation which leads to higher schedulability, but is more complex. • Most FPGAs allow only for 1D model, only latest Vertex 4 supports a 2D model Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  12. Models and LimitationsCurrent Technology Relocatability • FPGAs are non-homogeneous devices. • They contain special resources like dedicated memories (BRAM) and embedded multipliers (Xtreme DSP) which are not available at every location on the device. • This non-homogeneousness limits the relocatability of HW tasks, however an operating system takes many of these resources away from the user and puts them under OS control. Online Routing • Arbitrary relocation of task require online routing and online delay estimation of their signals (since they need to meet a deadline) neither of which is sufficiently supported by current tools. • However, the models presented here are abstract enough that, with a significant loss in performance, they could be modified to fit what is allow by the tools. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  13. Design IssuesTarget Architecture • Ci are external components. • RC is the reconfigurable device. • The configuration and readback port (C/R) gives the CPU complete control over the configuration of RC, (full and partial configurations can be downloaded to the device and full and partial device states can be read back.) • The communication port (COMM) provides a number of general-purpose signals between the host CPU and RC. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  14. Design IssuesResource Partition Hardware Task Area Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  15. Design IssuesOS Frames & Hardware Task Area • Static OS Frames accommodate functions that constitute the runtime part of the operating system. Functions such as: • Task communication and I/O through the Task Communication Bus (TCB). • Hardware Task Area is divided into a number of dummy task areas that are placeholders for hardware tasks. • Dummy tasks are palceholders for hardware tasks. The width of a harware task is an integer multiple of the width of a dummy task. • During the configuration of a hardware task, the other loaded hardware tasks remain executing. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  16. Design IssuesOS Modules Level 1 Level 2 Level 3 Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  17. Design Issues Three level architecture of the OS • First level : task and resource management. • Task scheduler decides on a starting time for each task, based on some scheduling policy; offline or online. • An offline schedule is suitable for statically defined applications and is reflected by a simple task sequence table. • Online schedulers are priority-driven and split into nonpreemptive and preemptive schedulers. • The resource manager keeps track of all dynamically assigned resources, such as the hardware task area and memory. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  18. Design Issues Three level architecture of the OS • The second level : handle task bitstreams and tasks states. • Raw Task Repository stores task circuits in their raw form. Before a raw task can be downloaded to the reconfigurable device, it must be relocated to a specific location in the hardware task area. • Task Context Store holds the task contexts that have previously been extracted from preempted tasks. • Task Preparation Unit (TPU) generates and analyzes partial bitstreams that represent the tasks. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  19. Design Issues Three level architecture of the OS • The third level : communication and configuration. • COMM Driver establishes this channel and allows the operating system modules to exchange commands and data. • C/R Driver provides device-independent configuration and readback services to the TPU. The services comprise full and partial configuration as well as full and partial readback. • Task Controller is the standard task interface and forms the connection between operating system frames and hardware task area. One task controller assigned to each task. • Memory Management Unit (MMU) offers memory services to the tasks, Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  20. Task and Resource Management • Scheduling real-time tasks • Guarantee-based online scheduling of real-time tasks to partially reconfigurable, non-preemptive platforms. • A task is schedule, or accepted to the current schedule, if its deadline can be meet and there is enough free area to accommodate the task. • An acceptance function can be define as shown, where xi is the task position and si is the start time allocated to the Ti by the scheduler. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  21. Task and Resource Management • A sophisticated online scheduling methods increase the acceptance ratio by planning (looking into the future) • We may delay starting a task for its laxity (until Si-latest = di - ei) and still meet its deadline. • The time interval [Ri, Si-latest] is the planning period for a task Ti. • During the period, a planning scheduler manages two sets of tasks: • the set of tasks currently executing on the device • the set of reserved tasks, i.e., tasks that have been previously guaranteed but not yet started. • Planning techniques split into two groups. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  22. Task and Resource Management • The first group are schedulers that may rearrange already guaranteed tasks to find guarantees for all these tasks plus the newly arrived one. Such scheduling problems are known to be NP-hard. • One such scheduling scheme is the Myopic scheme. • The second group are schedulers that try to fit the newly arrived task into the set of already guaranteed tasks rather than attempting to rearrange them. • Dis. : weaker in performance but can be more efficient algorithms. • The two scheduling algorithms that we present here, Horizon and Stuffing, fit into this group. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  23. Task and Resource ManagementScheduling Task in 1D • Definition 1: A schedule task Ti is a task with a placement xi and a starting time si such that: Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  24. Task and Resource ManagementScheduling Task in 1D (Horizon) • Execution List E: contains all currently executing tasks with their finishing time and placement (Ti, xi, fi). • xi is placement • fi is finish time of task fi = si + ei • si and ei, are start and execution time respectively. • Reservation List R: stores all scheduled but not yet executing tasks with their start time and placement (Ti, xi, si). • The Scheduling Horizon: is given by hi = ([x1, x2] @ tr), where [x1, x2] denotes an interval in the device’s x-dimension and tr gives the maximum of the last release time for this interval and the current time. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  25. Task and Resource ManagementScheduling Task in 1D (Horizon) • For completeness, here we show the Horizon algorithm. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  26. Task and Resource ManagementScheduling Task in 1D (Horizon) • Horizon Summary • Scheduler maintains a set of ‘horizons’ H • Each horizon, hi, is of the form {[x1, x2] @ tr} • Tasks are scheduled if they fit in any horizon (smallest horizon with adequate width is selected) • Adjacent horizons are merged when possible • The BestFit() function returns the horizon where the new task can be place or null and the task is rejected. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  27. Task and Resource ManagementScheduling Task in 1D (Stuffing) • Stuffing schedules task to arbitrary free areas that will exist in the future, including areas that will be used later by tasks currently in the reservation list. • More complex than Horizon, as it has to identify such potential placements and to check these potential placements for conflicts with existing reservations. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  28. Task and Resource ManagementScheduling Task in 1D (Stuffing) • Besides the Execution and Reservation lists, the stuffing scheduler employs a Free Space List F. • The free space list is a set of intervals [x1, x2] that identify currently unused resource intervals, sorted according to increasing x-coordinates. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  29. Task and Resource ManagementScheduling Task in 1D (Horizon) • For completeness, here we show the Stuffing algorithm. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  30. Task and Resource ManagementScheduling Task in 1D (Stuffing) • Stuffing Summary • Maintains a ‘free space list’ • Each free space is given by [x1, x2] • Free space list changes over time • To schedule a task, scheduler simulates execution of reserved tasks, modifying the free space list as it goes, until suitable space is found for the arriving task • The BestFit() function returns the free space where the new task can be place or null and the task is rejected. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  31. Task and Resource ManagementScheduling Task in 1D (Stuffing) • Stuffing Summary • Maintains a ‘free space list’ • Each free space is given by [x1, x2] • Free space list changes over time • To schedule a task, scheduler simulates execution of reserved tasks, modifying the free space list as it goes, until suitable space is found for the arriving task • The BestFit() function returns the free space where the new task can be place or null and the task is rejected. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  32. Task and Resource ManagementScheduling Task in 1D (Stuffing) • Stuffing Summary • Maintains a ‘free space list’ • Each free space is given by [x1, x2] • Free space list changes over time • To schedule a task, scheduler simulates execution of reserved tasks, modifying the free space list as it goes, until suitable space is found for the arriving task • The BestFit() function returns the free space where the new task can be place or null and the task is rejected. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  33. Task and Resource ManagementScheduling Task in 1D (Stuffing) • Stuffing Summary • Maintains a ‘free space list’ • Each free space is given by [x1, x2] • Free space list changes over time • To schedule a task, scheduler simulates execution of reserved tasks, modifying the free space list as it goes, until suitable space is found for the arriving task • The BestFit() function returns the free space where the new task can be place or null and the task is rejected. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  34. Task and Resource ManagementScheduling Task in 1D (Stuffing) • Stuffing Summary • Maintains a ‘free space list’ • Each free space is given by [x1, x2] • Free space list changes over time • To schedule a task, scheduler simulates execution of reserved tasks, modifying the free space list as it goes, until suitable space is found for the arriving task • The BestFit() function returns the free space where the new task can be place or null and the task is rejected. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  35. Task and Resource ManagementScheduling Task in 2D • Definition 2: A schedule task Ti is a task with a placement (xi, yi)and a starting time si such that: (Notice that this is a simple extension from the 1D model) Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  36. Task and Resource ManagementScheduling Task in 2D • The acceptance test can also be extended to fit the 2D model. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  37. Task and Resource ManagementScheduling Task in 2D (Horizon & Stuffing) • Switching from the 1D to the 2D area model mainly affects the management of free space which is done by the placer, not the scheduler. • The scheduling techniques remain basically unchanged. • Bestfit() works with rectangles instead of intervals. • MergeRectangles() can improve area unitilization. • Execution List E = {…, [Ti, (xi,yi), fi], …} which contains all currently executing tasks with their current 2D position and finish times. • Reservation List R stores all scheduled but not yet executing tasks {…, [Ti, (xi , yi ), si], …} • The Scheduling Horizon: hi = ([(x1 , y1 ), (x2 , y2 )] @ tr) Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  38. Results and Conclusion • The following table show the resulting schedule of 7 task on both area models with the horizon and stuffing algorithms. • Notice the difference in starting time for task T4 to T7 from 1D to 2D. This shows how the 2D area model provides better schedulabitlity. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  39. Results and Conclusion • Simulation settings: • 96x64 RCUs, Xilinx XCV1000 • Task are uniformly distributed in [50, 500] RCUs • UART (50 RCU), DCT (600 RCU) • Computation time also uniformly distributed in [5, 100] times units (simulation unit of 10ms) • Tasks A,B and C with laxities uniformly distributed in [1, 50], [50, 100], [100, 200] times units, respectively. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  40. Results and ConclusionReference Vs Horizon & Stuffing Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  41. Results and Conclusion1D & 2D Stuffing Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  42. Results and Conclusion • We have presented some design issues for reconfigurable hardware operating system. • We have presented the problem of real-time hardware task. • Shown two heuristics for online scheduling of this real-time hardware tasks for the 1D and 2D area models, Horizon and Stuffing. • Shown how Stuffing outperforms Horizon for both the 1D and 2D model, and how on the 1D area model the scheduling performance, for horizon as well as stuffing, depends on the aspect ratio of the hardware task. Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

  43. Questions Cpr E 583 : Reconfigurable Computing Systems - Fall 2005

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