EPC Enacted: Integration in an Industrial Toolbox and Use Against a Railway Application

Transcription

1 EPC Enacted: Integration in an Industrial Toolbox and Use Against a Railway Application E. Mezzetti, M. Fernandez, A. Bardizbanyan I. Agirre, J. Abella, T. Vardanega, F. Cazorla, * This project Real-Time and the research Systems leading to these Symposium results has received funding from the European Community s Seventh Framework Programme [FP7 / ] under grant agreement n

2 Reliable Measurement-based Estimates Common goal of Meas-based approaches Derive high-quality WCET estimates From analysis-time measurements Hold at operation MBPTA is no different Executable MBPTA Extreme Valye Theory Exceedance Probability Execution time Threshold e.g Time Traces Analysis time pwcet Operation 2 Extended Path Coverage Enacted - RTAS 2016

3 High-quality pwcet estimates Probability (log scale) Execution time 3 Extended Path Coverage Enacted - RTAS 2016

4 High-quality pwcet estimates Probability (log scale) Analysis-time Distribution Execution time 3 Extended Path Coverage Enacted - RTAS 2016

5 High-quality pwcet estimates Probability (log scale) Analysis-time Distribution Execution time 3 Extended Path Coverage Enacted - RTAS 2016

6 High-quality pwcet estimates Probability (log scale) Operation-time Distribution (afterthought) Analysis-time Distribution Execution time 3 Extended Path Coverage Enacted - RTAS 2016

7 High-quality pwcet estimates Probability (log scale) Operation-time Distribution (afterthought) Analysis-time Distribution Execution time 3 Extended Path Coverage Enacted - RTAS 2016

8 High-quality pwcet estimates Probability (log scale) Operation-time Distribution (afterthought) Analysis-time Distribution Execution time 3 Extended Path Coverage Enacted - RTAS 2016

9 High-quality pwcet estimates Probability (log scale) Operation-time Distribution (afterthought) Analysis-time Distribution Execution time 3 Extended Path Coverage Enacted - RTAS 2016

10 The PROXIMA MBPTA approach Representativeness of pwcet estimates By controlling all sources of execution time variability HW/SW High-level (easier) Low-level (harder) Cannot rely on users to fully control lower-level aspects Demand their control to analysis tool and/or platform Upperbounding and randomization Representativeness can be probabilistically 16 After N runs the probability of not capturing random events with high impact on exec time is below a certain threshold (e.g., 10e 12 ) 4 Extended Path Coverage Enacted - RTAS 2016

11 Path-representativeness Inherent limitation of measurement-based approaches Bounds are only valid for the set of paths and execution conditions for which observations were collected The same applies to MBPTA Extended Path coverage 15 Measurements collected over a subset of the program paths EPC... EPC Synthetic measurements for unobserved paths MBPTA Exceedance Probability Execution time pwcet "Fully representative" distribution for all paths in a program obtained from both observed AND synthetic observations EPC Representativeness gap Distribution valid only for observed paths NO EPC 5 Extended Path Coverage Enacted - RTAS 2016

12 EPC nuts and bolts Automatically derive synthetic end-to-end observations By recombining partial timing information (e.g., basic block level) Cannot naively sum up maximum-observed values They are relative to particular path with cache/core-level dependencies Might not have observed basic blocks along their worst-case path Path-independence Execution times (ET) can be made independent from the path through which they have been collected EPC exploits probabilistic path independence at basic blocks level Path-independent ET can be combined to construct representative execution times for end-to-end (unobserved) paths 6 Extended Path Coverage Enacted - RTAS 2016

13 Probabilistic path independence Path-independent execution times for a basic block Values does not depend on a particular path Summing up a penalty or padding to each observed ET to compensate for any positive effect due to a specific path (e.g., cache behavior) On time-randomized single-core architectures Randomized caches are the main source of variability L ATP(@ A, φ) = hit L miss P hit (@ A, φ) P miss (@ A, φ) Probabilistic padding of ATPs To negatively compensate potential positive effects of variability (e.g., a cache hit) on a specific path L ATP(@ A ) = hit L miss P hit (@ A ) P miss (@ A ) 7 Extended Path Coverage Enacted - RTAS 2016

14 Probabilistic path independence Path-independent execution times for a basic block Values does not depend on a particular path Summing up a penalty or padding to each observed ET to compensate for any positive effect due to a specific path (e.g., cache behavior) On time-randomized single-core architectures Randomized caches are the main source of variability L ATP(@ A, φ) = hit L miss P hit (@ A, φ) P miss (@ A, φ) Probabilistic padding of ATPs To negatively compensate potential positive effects of variability (e.g., a cache hit) on a specific path L ATP(@ A ) = hit L miss Not an option P hit (@ A ) P miss (@ A ) 7 Extended Path Coverage Enacted - RTAS 2016

15 Over-approximating the worst-case ATP ATP Cumulative ATP 1 0 P hit (@ A, φ) P hit (@ A ) P + hit(@ A ) L hit P miss (@ A, φ) P miss (@ A ) L miss P + miss (@ A ) L miss+pad P + miss+pad (@ A ) ATP(@ A, φ) ATP + (@ A ) ATP(@ A ) 1 0 P + hit(@ A )+ P + miss(@ A ) P hit (@ A, φ) P hit (@ A ) P + hit(@ A ) L hit L miss L miss+pad 8 Extended Path Coverage Enacted - RTAS 2016

16 Probabilistic padding... Reuse distance and unique accesses Example 4-ways Random A B mapping to same cache set Focus on basic blocks bb 3 PPAD(@ A, φ 0 ) and PPAD(@ A, φ 1 B bb 0 bb 1 bb B P pad (@ A, φ) = { 0 if uphit (@ A, φ) = 0 1 P hit(@ A ) up hit (@ A, φ) A bb 3 P hit (@ A ) = 1 P miss (@ A ) = = 3 4 up hit (@ A, φ 0 ) = 1 (same for φ 1 A bb 4 bb C Probability of applying a padding to bb 3 is P pad (@ A, φ 0 ) = P pad (@ A, φ 1 ) = 1 C bb Extended Path Coverage Enacted - RTAS 2016

17 Meeting EPC requirements 10 Extended Path Coverage Enacted - RTAS 2016

18 EPC Process Requirements Preparation Collection Processing Computation Instrumentation at basic block level Adequate tracing throughput Tracing memory accesses and random seed information Augmented exec time profiles Generation of synthetic paths 11 Extended Path Coverage Enacted - RTAS 2016

19 EPC Process Requirements Preparation Collection Processing Computation Instrumentation at basic block level Adequate tracing throughput Tracing memory accesses and random seed information Augmented exec time profiles Generation of synthetic paths 11 Extended Path Coverage Enacted - RTAS 2016

20 EPC Process Requirements Preparation Collection Processing Computation Instrumentation at basic block level Adequate tracing throughput Tracing memory accesses and random seed information Augmented exec time profiles + Library Generation of synthetic paths Automated Tool Collect artificial execution times by iterating over all the basic blocks in each unobserved path Consider only a subset of all possible paths Pruning based on known flow facts 11 Extended Path Coverage Enacted - RTAS 2016

21 EPC Process Requirements Preparation Collection Processing Computation Instrumentation at basic block level Adequate tracing throughput Tracing memory accesses and random seed information Augmented exec time profiles Generation of synthetic paths Computation as baseline MBPTA approach 11 Extended Path Coverage Enacted - RTAS 2016

22 Evaluation Qualitative and quantitative assessment PROXIMA Platform FPGA implementation based on LEON3/NGMP Processor family 4 cores (EPC evaluated on single-core scenario) Cache hierarchy Separate 16KB 4-way set-associative L1 caches for instruction and data (write-through, no write allocate) Random-Modulo placement and Random 16 Shared 128KB 4-way unified L2 cache, write-back policy AMBA AHB bus connects cores to private caches, L2 and DRAM memory controller Synthetic example and industrial use case 12 Extended Path Coverage Enacted - RTAS 2016

23 Synthetic example Fully-controlled example Clear mapping paths inputs Full path coverage as a reference input vector v 1 v 2 v 3 v 4 entry v 1 true v 1 false v 2 true v 2 false v 3 true v 3 false v 4 true exit v 4 false basic block coverage worst-case path 13 Extended Path Coverage Enacted - RTAS 2016

24 Synthetic example Max pwcet full coverage HWM full coverage Max pwcet EPC 2 paths Max pwcet EPC 4 paths Max pwcet EPC 8 paths Max pwcet EPC 8 paths (WCP included) Exceedance probability Cycles Test MOET % 10 3 % 10 6 % 10 9 % % Full p EPC % p EPC p EPC W-8p EPC Extended Path Coverage Enacted - RTAS 2016

25 Industrial case study setcs SIL4 Application from railway domain Supervision of train traveled distance and speed Sensors, monitoring systems and emergency actuators (brakes) 50 branches, 90 procedures (for 300 proc calls), 120 BB setcs EVC_TMR Position/ Speed Sensors Balise Transmission Module (BTM) Driver Machine Interface (DMI) EVC_Node3 EVC_Node2 EVC_Node1 Odometry System (OMS) Speed & Position Emergency Brake Control (ES) Service Brake Control (SS) Emerg. Brake Serv. Brake Warning Voter V V V Safety Relay (I) Safety Relay (II) Electric Braking System Pneumatic Braking System 15 Extended Path Coverage Enacted - RTAS 2016

26 Industrial case study setcs Experiment conducted at user premises On a very limited set of input vectors (BB coverage) Plain MBPTA results as baseline reference Experiment MOET Test Test Test Test Test Test Test Test Test Test Extended Path Coverage Enacted - RTAS 2016

27 Industrial case study setcs A total of structurally feasible paths User-provided flow facts greatly reduced the amount of paths Only 26 paths were considered semantically relevant 16 of these paths had not been observed at analysis time Experiment MOET SynthTest SynthTest SynthTest SynthTest SynthTest SynthTest SynthTest SynthTest SynthTest SynthTest SynthTest SynthTest SynthTest SynthTest SynthTest SynthTest Increase wrt Worst-Case MBPTA +60% +74% +94% +111% +130% 17 Extended Path Coverage Enacted - RTAS 2016

28 setcs Gauging Overapproximation Cycles (thousands) Unobserved behavior or unnecessary pessimism? Could not collect evidence by executing the EPC WC path By code inspection it exhibit large overlapping with Path7 Overall inflation factor Padding applied to 23% of total BB, AVG increase 10.5% Few exceptions (bad case up to 4x) Pessimism function of execution frequency and relative contribution Basic blocks 18 Extended Path Coverage Enacted - RTAS 2016

29 setcs Gauging Overapproximation Assessing SynthPath12 against Path7 How far are MOET values from cumulative values Suggests SynthPath12 could incur 30% large MOET Remaining 30% originates from padding Pessimism from dirty misses assumption Dynamic references (parameter passing) and always-misses Issues could be cured with larger support to structural information in the analysis tool MOET Max Cumul Min Cumul Max EPC Inflation Test SynthTest Increase 60% 29% 16% 32% 19 Extended Path Coverage Enacted - RTAS 2016

30 Conclusions and future works EPC is an hybrid approach Extends and complements MBPTA For increased representativeness of results Evaluation on full industrial-quality toolchain Realistic requirements at HW and SW level Proved to be computationally feasible Pessimism depends on application structure and code constructs Future directions Extend tool support for contextual information Integrate with existing tools (e.g. SWEET) to automatically derive flow facts 20 Extended Path Coverage Enacted - RTAS 2016