Villar presentation.pdf
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Eugenio Villar's presentation at the University of Cantabria discusses model-driven design of drone-based services, highlighting the integration of cyber-physical systems (CPS) and simulation methods for effective performance analysis. The presentation emphasizes the importance of multi-level simulation and design-space exploration in creating efficient drone services and acknowledges the contributions of various researchers in this field. Conclusively, it argues for the necessity of advanced design methods like model in the loop and system design to enhance CPS applications.
![June 8, 2022
Native Simulation: Flaxibility + accuracy
Overflow = 0;
s = 1L;
for (i = 0; i < L_subfr; i++) {
Carry = 0;
s = L_macNs(s, xn[i], y1[i]);
if (Overflow != 0) {
break; }}
if (Overflow == 0) {
exp_xy = norm_l(s);
if (exp_xy<=0)
xy = round(L_shr (s, -exp_xy));
else
xy = round(L_shl (s, exp_xy)); }
mutex_lock(mutex_name);
Global variable
int Sim_Time = 0;
Sim_Time += TB();
Sim_Time += TB();
Sim_Time += TB();
Sim_Time += TB();
Sim_Time += TB();
Sim_Time += TB();
wait included
TB() is a function of
# of binary instructions
type of instructions
# of cache misses
frequency
even
data dependencies
Sim_Time += TSYS();
TSYS() is a function of
preemptions
conflicts in the bus
Design Verification & Performance Analysis
25](https://image.slidesharecdn.com/villarpresentation-220608140733-9a6230f5/85/Villar-presentation-pdf-25-320.jpg)
Villar presentation.pdf
- 1. June 8, 2022 Eugenio Villar University of Cantabria Modeling, Design and Implementation of drone-based Services
- 2. June 8, 2022 Agenda Introduction Model-Driven Design of CPSoS Drone-based Services Design Verification and Performance Analysis Experimental Results Conclusions Demos 際際滷s can be found at: /EugenioVillar/ 2
- 3. June 8, 2022 N2 B N1 M A Introduction Model-Driven Design (MDD) High-abstraction level Mature SW engineering methodology UML Standard, any (user-defined) MoC, any language Natural way to capture system architecture 3 Semantic lacks Domain-specific profiles MetaMorph OpenSource, any (user-defined) MoC, language agnostic
- 4. June 8, 2022 Introduction Model-Driven Design (MDD) Abstraction of the platform SW development on APIs MWs, VMs, OSs. Simulation is not always an issue SiL & HiL Verification Performance is not key 4 M2C PCs Servers DCs HPCs Mobiles IoT compilation MWs VMs OSs Python Java C++ GO Swift
- 5. June 8, 2022 Introduction State-of-the-Art in Simulation-Based MDD Matlab-Simulink Proprietary only one MoC, M language Application to UAVs Autopilot + Physics ROS toolbox AMeSIM/ANSyS Proprietary, only one MoC CoFluent Proprietary a few MoCs, C/C++ language Ptolemy II Academic, any MoC, C/C++ inside a Java block HEPSYCODE Academic, several MoCs, SystemC 5 M2C MWs VMs OSs Python Java C++ GO Swift
- 6. June 8, 2022 Introduction Embedded System Design (ESD) & Electronic System-Level Design (ESL) Model of the platform At different abstraction levels Platform-based HW/SW co-design Simulation is key At different abstraction levels Performance is key Cyber-Physical interaction Real-Time Systems 6 P&R C++ SystemC VHDL/Verilog SoC FPGAs Boards NoC HW accel. I/O Busses GPUs CPUs MWs VMs OSs HLS/RTL synthesis compilation
- 7. June 8, 2022 Introduction Services provided on computing platforms of many kind Programming the Internet of Everything In close interaction with the physical world => CPSoS-IoT Full abstraction of the computing platform is no longer possible 7
- 8. June 8, 2022 Introduction Gap between MDD & ESD/ESL S3D: Single-Source System Design Linking MDD with ESD/ESL Simulating the PSM At different abstraction levels Estimating performance Depending on the HW Platform Automatic generation of the executable models Design-Space Exploration Python Java C++ GO Swift SoC FPGAs Boards NoC HW accel. I/O Busses GPUs CPUs MWs VMs OSs ?? Design Gap 8
- 9. June 8, 2022 HW/SW Platform Architectural Mappings C/ C++ Scenarios PIM (App) M2T Tools SW Synthesis (mSSYN) Simulation model Synthesis (mSSYN) VIPPE Introduction S3D: System Modeling & Simulation 9
- 10. June 8, 2022 HW/SW Platform Architectural Mapping C/ C++ Scenarios PIM (App) M2T Tools SW Synthesis (eSSYN) SMP Nodes GPUs HW Accelerators Application SW Introduction S3D: HW/SW Synthesis 10
- 11. June 8, 2022 Introduction S3D: Design-Space Exploration Linking MDD with ESL Python Java C++ GO Swift SoC FPGAs Boards NoC HW accel. I/O Busses GPUs CPUs MWs VMs OSs 11
- 12. June 8, 2022 Introduction S3D: Programming the Internet of Everything Services provided on heterogeneous computing platforms of many kind Impact on functional and non-functional properties of the execution platform HW Synthesis SW Synthesis (RT)OS, Runtime, Corba, TCP/IP, MPI, MCAPI, ForTran, Python, Java, HTML5, C/C++, Concerns Performance, safety, cost, security, size, Schedulability Analysis Simulation Verification Performance Analysis Design-Space Exploration Optimization Service UML CPSoS DSL UML CPSoS DSL 12
- 13. June 8, 2022 Model-Driven Design of Cyber-Physical SoS Traditional V-Cycle for Mechatronic Systems Design & Analyze Develop (Platform-Dependent) Verify 13
- 14. June 8, 2022 Model-Driven Design of Cyber-Physical SoS New Validation/Verification V-Cycle Reusability Simulation-based Analysis & Design Design-Space Exploration Performance Analysis Architectural mapping 14
- 15. June 8, 2022 Model-Driven Design of Cyber-Physical SoS System Design & Validation System Interface Domain & System Requirements Functional Specification Input/Output Rates and Delays Test-Bench Development Minimal Functionality System Validation 15
- 16. June 8, 2022 CPS: Digital Behavior in a Physical World System Model (Specification) The implementation is as good as similar to the model Environment Model The model is as good as similar to reality Close-loop behavior can be extremely difficult to model Model-Driven Design of Cyber-Physical SoS 16
- 17. June 8, 2022 Model-Driven Design of Cyber-Physical SoS Mechanical & HW/SW Design & Validation Sub-System & Component Interface Sub-System & Component Requirements Input/Output Rates and Delays Minimal Sub-System & Component Functionality => System Validation Reusability
- 18. June 8, 2022 Model-Driven Design of Cyber-Physical SoS ROS De-facto standard for robot applications ROS Infrastructure ROS nodes Processes that perform a certain computation ROS Master (Core) Nodes registration Communication manager 18 Client-Server (RPC) Publish-Suscriber
- 19. June 8, 2022 Model-Driven Design of Cyber-Physical SoS Platform-Based Design POSIX API ROS API 19
- 20. June 8, 2022 VIPPE Scheduler Host Execution Platform Ubuntu 18.04 Intel i5-34700 x86-64 Process 1 Process 2 Process 3 Model-Driven Design of Cyber-Physical SoS Platform-Based Simulation POSIX API ROS API 20
- 21. June 8, 2022 Model-Driven Design of Cyber-Physical SoS Drone-Independent ROS Interface Extensible to robots with similar functionality 21
- 22. June 8, 2022 Model-Driven Design of Cyber-Physical SoS Drone-Independent ROS Interface Reusable ROS code Code length reduction Decrease in simulation speed 22 Reduction in program length Drone Drone-specific code (LoCs) CoDIn (LoCs) Reduction (%) Ardupilot 343 233 32.07 Px4 357 34.73 Reduction in simulation speed Drone Drone-specific code (s/s) CoDIn (s/s) Reduction (%) Ardupilot 1.9 1,85 2,6
- 23. June 8, 2022 S3D components in a drone-based service C++ components ROScpp components Drone and robot models Design Verification & Performance Analysis C++ ROScpp Drone models 23
- 24. June 8, 2022 Multi-Level Simulation & Performance Analysis C++ and ROScpp components Simulation of ROScpp components without the (slow) ROS infrastructure Functional ROS Direct links among publishers and subscribers Design Verification & Performance Analysis Abstraction Levels for C++ & ROS cpp components Level Code Timing/Energy ROS infrastructure MN Minimal No Yes/No MC Minimal Constant FC Full code Constant FD Full code Data-dependent 24
- 25. June 8, 2022 Native Simulation: Flaxibility + accuracy Overflow = 0; s = 1L; for (i = 0; i < L_subfr; i++) { Carry = 0; s = L_macNs(s, xn[i], y1[i]); if (Overflow != 0) { break; }} if (Overflow == 0) { exp_xy = norm_l(s); if (exp_xy<=0) xy = round(L_shr (s, -exp_xy)); else xy = round(L_shl (s, exp_xy)); } mutex_lock(mutex_name); Global variable int Sim_Time = 0; Sim_Time += TB(); Sim_Time += TB(); Sim_Time += TB(); Sim_Time += TB(); Sim_Time += TB(); Sim_Time += TB(); wait included TB() is a function of # of binary instructions type of instructions # of cache misses frequency even data dependencies Sim_Time += TSYS(); TSYS() is a function of preemptions conflicts in the bus Design Verification & Performance Analysis 25
- 26. June 8, 2022 Native Simulation Performance Analysis of ROScpp components Native simulation of C++ code Constant time/energy for ROS method calls Dependent on the CPU Dependent on the number of nodes and subscribers Part to be assigned to the component Design Verification & Performance Analysis 26
- 27. June 8, 2022 Performance Analysis of ROScpp components Time/energy for ROS method calls at the component Design Verification & Performance Analysis 27
- 28. June 8, 2022 Performance Analysis of ROScpp components Time/energy for ROS method calls at ROScore Design Verification & Performance Analysis 28
- 29. June 8, 2022 Performance Analysis Estimation Error Design Verification & Performance Analysis 29 Frequency (MHz) Estimated Time (ms) Measured Time (ms) Estimation Error (%) Intel 1600 485.87 582.58 16.60 3000 318.62 461.46 30.95 ARM 600 521.46 904.95 42.38 1500 233.96 398.26 41.25
- 30. June 8, 2022 Performance Analysis Error reduction Improvement increases as the ROS percentage increases Design Verification & Performance Analysis 30 Frequency (MHz) Total Application time (ms) %ROS code Impact of ROS estimation error (%) Impact of no estimation Improvement Intel 1600 22,875 2.55 0.42 2.55 83.5% 3000 22,018 2.10 0.65 2.10 69.0% ARM 600 213,446 0.42 0.18 0.42 57.1% 1500 87,688 0.45 0.19 0.45 57.8%
- 31. June 8, 2022 Multi-Level Simulation & Performance Analysis Drone models Design Verification & Performance Analysis Abstraction Levels for drone models Level Drone model Physical model ROS infrastructure FN Functional No No FY Functional No Yes AY Autopilot Yes Yes AM Autopilot Electro-Mechanical Yes 31
- 32. June 8, 2022 Drone and robot models Components in the S3D ModelLibrary Instantiation in the VerificationView Selection for synthesis of the executable model Design Verification & Performance Analysis 32
- 33. June 8, 2022 Multi-Level Simulation & Performance Analysis Simulation Infrastructure General architecture Design Verification & Performance Analysis 33
- 34. June 8, 2022 Multi-Level Simulation & Performance Analysis Simulation Infrastructure General architecture Real-Time (RT) simulation- simulation time = simulated time (SnT = SdT) As Fast As Possible (AFAP) simulation (SnT as greater as possible than SdT) Design Verification & Performance Analysis 34
- 35. June 8, 2022 Multi-Level Simulation & Performance Analysis Simulation Infrastructure Functional drone modeling Without ROS (FN) Any C++ and ROScpp models (MN + MC + FC + FD) Design Verification & Performance Analysis 35
- 36. June 8, 2022 Multi-Level Simulation & Performance Analysis Simulation Infrastructure Functional drone modeling With ROS (FY) Any C++ and ROScpp models (MN + MC + FC + FD) Design Verification & Performance Analysis 36
- 37. June 8, 2022 Multi-Level Simulation & Performance Analysis Simulation Infrastructure Realistic drone modeling (Autopilot + Physics) With ROS (AY + AM) Any C++ and ROScpp models (MN + MC + FC + FD) With or without 3D Graphics Design Verification & Performance Analysis 37
- 38. June 8, 2022 Multi-Level Simulation Impact of an increasing number of host CPUs (8 drones) Simulation Results 38
- 39. June 8, 2022 Multi-Level Simulation Impact of an increasing number or realistic vs functional drones Simulation Results 150 80 39
- 40. June 8, 2022 Simulation Results Multi-Level Simulation & Performance Analysis Impact of an increasing number of realistic drones 40
- 41. June 8, 2022 Real-Time Simulation in seconds Impact of an increasing number of realistic drones Simulation Results 41
- 42. June 8, 2022 Simulation Results Real-Time Simulation in % of CPU usage Impact of an increasing number of realistic drones 42
- 43. June 8, 2022 Conclusions Services based on CPS demand new design methods and tools e.g. Drone-based Services Close interaction between the physical world and the digital electronics Model-Driven System Design is a powerful candidate HiL & SiL are not enough Model in the loop (MiL) is required Extension of the classical V-Cycle Multi-Level Simulation is key in designing drone-based services As Fast As Possible vs Real-Time Drones are just pieces inside a complex, distributed functionality S3D is a valid approach towards MDD of drone-based services 43
- 44. June 8, 2022 Acknowledgement Last Research Results from many people Hector Posadas Javier Merino Raul Gonzalez Jose Maria Gandara and the rest of the Microelectronics Engineering Group 44
- 45. June 8, 2022 Any comment/question? 45