Software Verification for Low Power, Safety Critical Systems

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1 Software Verification for Low Power, Safety Critical Systems 29 Nov 2016, Simon Davidmann Imperas Software Ltd. Page 1

2 Software Verification for Low Power, Safety Critical Systems Page 2 DVClub Nov 2016

3 Agenda Software Verification for Systems Low Power, Safety Critical Page 3 DVClub Nov 2016

4 Agenda Software Verification for Systems Many processors with lots of software Software Verification requirements Embedded Software Development Issues Adopting Simulation (Virtual Platforms) Advanced tools available with simulators Low Power, Safety Critical Page 4 DVClub Nov 2016

5 Modern SoCs Have Many Concurrent Processing Elements SMP cores AMP cores Accelerators Renesas R-Car H2: Automotive infotainment and ADAS Page 5 DVClub Nov 2016

SW Verification Requirements Hardware Dependent Software (HDS) Hardware Dependent Software (HDS) Most complex foundation layer Drivers, hypervisors, assembly libraries, operating system Buried

6 SW Verification Requirements Hardware Dependent Software (HDS) Hardware Dependent Software (HDS) Most complex foundation layer Drivers, hypervisors, assembly libraries, operating system Buried problems often appear elsewhere in a system, leading to misdirected analysis Ripe for corner case type issues Post development bugs hardest to fix Testing needs to be platform centric not application centric Modern SoC SW verification is complex SMP/AMP multicore interaction Shared memory & devices Extensive accelerators, peripherals Externally authored, complex libraries Complex SW/HW interaction (e.g. power) How to estimate power consumption and test power management strategies over a wide range of conditions? Page 6 DVClub Nov 2016

Embedded Software Development Issues (in no specific order) Schedule Quality Functionality Timing, power constraints Security / safety Predictability of the

7 Embedded Software Development Issues (in no specific order) Schedule Quality Functionality Timing, power constraints Security / safety Predictability of the software engineering task: management accuracy on software resource and schedule requirements is +/- 50% Unknown / unmeasurable delivery risk Page 7 DVClub Nov 2016

Hardware-Based Software Development Has timing/cycle accuracy JTAG-based debug, trace Traditional development board or hardware emulator based testing Late to arrive Limited physical system

8 Hardware-Based Software Development Has timing/cycle accuracy JTAG-based debug, trace Traditional development board or hardware emulator based testing Late to arrive Limited physical system availability Emulators are too slow to run enough system scenarios Limited external test access (controllability) Limited internal visibility How to observe power consumption? To get around these limitations, software is modified printf Debug versions of OS kernels Instrumentation for specific analytical tools, e.g. code coverage, profiling Even using different tool chains and libraries Modified software may not have the same behavior as clean source code Page 8 DVClub Nov 2016

9 Virtual Platforms Complement Hardware-Based Software Development Current methodology employs testing on hardware Proven methodology Has limitations We are at the breaking point Virtual platform based methodology delivers controllability, visibility, repeatability, automation Application Layer: Customer Differentiation Middleware: TCP/IP, DHCP, LCD, OS: Linux, FreeRTOS, µc/os-iii, ThreadX, Drivers: USB, SPI, ethernet, Actual Hardware or Virtual Platform Virtual platforms software simulation provide a complementary technology to the current hardwarebased methodology Page 9 DVClub Nov 2016

10 Advantages of Virtual Platform Based Software Development (Instruction Accurate Simulation) Earlier system availability Easy access for entire team Runs actual binaries, e.g. runs ARM executables on x86 host Fast, enables quick turnaround and comprehensive testing Full controllability of platform both from external ports and internal nodes Corner cases can be tested Errors can be made to happen Full visibility into platform: if an error occurs, it will be observed by the test environment Easy to replicate platform and test environment to support automated continuous integration (CI) and test automation / regression testing on compute farms Test Set 1 Test Set n Page 10 DVClub Nov 2016

11 Building the Virtual Platform The virtual platform is a set of models that reflects the hardware on which the software will execute Could be 1 SoC, multiple SoCs, board, system; no physical limitations Functionally accurate, such that the software does not know that it is not running on the hardware Models are typically written in C or SystemC Models for individual components interrupt controller, UART, ethernet, are connected just like in the hardware Peripheral components can be connected to the real world by using the host workstation resources: keyboard, mouse, screen, ethernet, USB, Page 11 DVClub Nov 2016

Imperas Tool Architecture Output Data T E S T B E N C H Application Software & Operating System Virtual Platform Peripheral Memory B U S OVP CPU OVP CPU C P U H E L P E R O

12 Imperas Tool Architecture Output Data T E S T B E N C H Application Software & Operating System Virtual Platform Peripheral Memory B U S OVP CPU OVP CPU C P U H E L P E R O S H E L P E R V A P T O O L S Trace Profile Coverage Schedule Multiprocessor / Multicore Debugger Simulation Engine SlipStreamer API API Eclipse IDE Page 12 DVClub Nov 2016

13 Running Software on a Virtual Platform BareMetal Platform Processor Memory Quickly execute any program on a default BareMetal platform Simply run the executable with the name of the application object simulate fast Page 13 DVClub Nov 2016

14 Virtual Platform Booting Linux Kernel on ARM Cortex-A57 / Cortex-A53 big.little Imperas OVP ARM MultiCluster model (big.little) Interrupt Distributor - GIC-400/GIC-500 (GICv2/GICv3) simulate ostrace qtrace UART0 UART0 UART0 UART0 UART0 UART0_0 Cache Coherent I/F CCI-400/CCI-500 Memory Page 14 DVClub Nov 2016

15 And many many tools can be used with the simulation Trace Coverage Profile Memory analysis Dynamic (Temporal) Assertions osaware: context, schedule, task, All at the flick of a switch All non-intrusively All without requiring any changes to software Runs with production binaries => Use of simulation (virtual platforms) is the modern way to develop and verify embedded software Page 15 DVClub Nov 2016

16 And When it comes to Continuous Integration When it comes to test automation When it comes to regression testing => Virtual platforms become essential for embedded software development Page 16 DVClub Nov 2016

17 Agenda Software Verification for Systems Low Power, Safety Critical Page 17 DVClub Nov 2016

Institute for Information Technology, Oldenburg, Germany This work was partially funded by the

18 Collaborations Pontifical Catholic University of Rio Grande do Sul, (PUCRS) Porto Alegre Brazil. University of Leicester, Leicester, UK. Institute for Information Technology, Oldenburg, Germany This work was partially funded by the European Union s Horizon2020 research and innovation programme under the grant agreement No More information at Page 18 DVClub Nov 2016

19 Working on Verification of Software Timing Analysis Power Analysis Fault Simulation Page 19 DVClub Nov 2016

20 Working on Verification of Software Timing Analysis using Instruction Accurate simulation / virtual platforms => software performance Power Analysis using Instruction Accurate simulation / virtual platforms => software affected power Fault Simulation using Instruction Accurate simulation / virtual platforms for software verification and compliance to standards such as ISO => software fault tolerance Page 20 DVClub Nov 2016

21 CPU Timing Estimator Application Memory.elf file CPU CPU Timing Estimator CPU Characterization Data CPU Characterization Data for each CPU variant Limitation: In-order processors Timing Estimator loaded onto CPU instance as binary intercept library No edits/changes needed in CPU model binary, or platform, or other models Controlled by simulation command line arguments Takes account of instructions, branches, sequences, memory Page 21 DVClub Nov 2016

22 Accuracy Evaluation vs Board Example: Cortex-M4F running FreeRTOS WCET and other benchmarks 12.30% Worst case error <13% Average error across all benchmarks run <5% Most errors are <8% Simulation speeds with timing up to 500Mips Caveat: performance and accuracy are application dependent Page 22 DVClub Nov 2016

23 Working on Verification of Software Timing Analysis Power Analysis Fault Simulation Page 23 DVClub Nov 2016

24 Eu SafePower project Explorative project to enable the development of low power mixed-criticality systems through the provision of a reference architecture, platforms and tools to facilitate the development, testing, and validation Page 24 DVClub Nov 2016

25 SafePower Xilinx Zynq Virtual Platform Harness Zynq Programmable Logic Zc702/zc706 Zynq Zynq Processing Sub-system Zynq Programmable Logic MicroBlaze Memory CPU0 (ARM Cortex-A9MPx2) slcr Ethernet MAC Zynq Programmable Logic uartps devcfg MicroBlaze Memory Memory Controller Flash Controller MicroBlaze Memory Memory Smartloader Memory Interchangeable Zynq Programmable Logic Modules Page 25 DVClub Nov 2016

uartps Memory Controller Ethernet MAC devcfg Flash Controller Zynq Programmable

26 SafePower: Xilinx Zynq zc706 Virtual Platform fentiss XtratuM Hypervisor on ARM Cortex-A9MPx2 Zynq Zynq Processing Sub-system CPU0 (ARM Cortex-A9MPx2) slcr Memory uartps Memory Controller Ethernet MAC devcfg Flash Controller Zynq Programmable Logic Shown running fentiss Xtratum Hello World example application Page 26 DVClub Nov 2016

27 SafePower ARM Cortex-A9 Power Model Overview Intercept Library Voltage Regulators and Power Sensors Power Model Zynq Power Model Platform Access Memory, Registers, Voltages, etc. Zynq Processing Sub-system Int. Lib. CPU0 (ARM Cortex-A9MPx2) I²C (PMBUS) Utilizations (CPU, RAM R/W, AXI) Core Model Power Formulas Power Values Platform Model Clock Rates (CPU, RAM, AXI, IO) and Voltages VCD Sink Memory uartps Memory Controller Zynq Programmable Logic slcr Ethernet MAC devcfg Flash Controller File Output Page 27 DVClub Nov 2016

28 SafePower Dynamic Frequency Voltage Scaling (DVFS) Analysis System Application, Operating System, Firmware Runs on Virtual Platform Power Model Design-Time Opt. Understand Tracing Page 28 DVClub Nov 2016

29 SafePower Power Traces Analysis Application, Operating System, Firmware Runs on Virtual Platform Power Model Design-Time Opt. Analyze/ Debug Tracing Page 29 DVClub Nov 2016

30 SafePower : Power Monitoring in SW Application, Power Operating System, Consumption Firmware Runs on Virtual Platform Register Interface Power Model Power Sensor Design-Time Opt. Analyze/ Debug Tracing Page 30 DVClub Nov 2016 video

31 Working on Verification of Software Timing Analysis Power Analysis Fault Simulation Page 31 DVClub Nov 2016

32 Fault Simulation is needed Compliance with standards requires products to demonstrate reliability and tolerance to fault injections Eg: automotive ISO26262 requires this Fault Simulation proved in the HW world it was a good way to show hardware had been manufactured fault free Fault Simulation can be used with virtual platforms to show that software is reliable under the presence of faults Page 32 DVClub Nov 2016

33 Fault Simulation Overview 4 stages Virtual Platform Operating System Applications Virtual Platform Operating System Applications Virtual Platform Operating System Applications Fault List Fault Free Simulation Run Hardware & Software Introspection & Fault List Creation Simulation Runs With Simulation Faults Injected Runs Simulation Runs With Detection Faults Injected Data With Faults Injected Golden Data Fault Dictionary Fault Dictionary Data Analysis & Reporting Page 33 DVClub Nov 2016

34 Fault Simulation Analysis & Reporting [A, B, C] = [Cortex-A9MPx1, X2, X4] 8,000 faults generated for each processor configuration 16 applications (Rhodinia HPC benchmarks) running under Linux 3.13 Page 34 DVClub Nov 2016

35 Summary Virtual platforms software simulation provide a complementary technology to hardware-based testing of software Virtual platforms can run full production binaries including hypervisors and hardware virtualization to assist in verification of safety critical systems Besides functional correctness, timing properties and power consumption are gaining importance Virtual platforms become essential with adoption of Continuous Integration methods for embedded systems software Virtual platforms for software verification help you Achieve higher quality software Reduce development schedules Increase software project predictability Reduce delivery risk Page 35 DVClub Nov 2016

36 Thank you For more information: Page 36

Integrating Power Models into Instruction Accurate Virtual Platforms for ARM-based MPSoCs

Integrating Power Models into Instruction Accurate Virtual Platforms for ARM-based MPSoCs ARM TechCon 2016 26 October 2016 R. Görgen 2, D. Graham 1, K. Grüttner 2, L. Lapides 1, S. Schreiner 2 1 Imperas,