Abstract. Previously published methods for estimation of the worst-case execution time on high-performance processors with complex pipelines and multi-level memory hierarchies result in overestimations owing to insu cient path and/or timing analysis. This does not only give rise to poor utilization of processing resources but also reduces the schedulability in real-time systems. This paper presents a method that integrates path and timing analysis to accurately predict the worst-case execution time for real-time programs on high-performance processors. The unique feature of the method is that it extends cycle-level architectural simulation techniques to enable symbolic execution with unknown input data values; it uses alternative instruction semantics to handle unknown operands. We show that the method can exclude many infeasible (or non-executable) program paths and can calculate path information, such as bounds on number of loop iterations, without the need for manual annotations of programs. Moreover, the method is shown to accurately analyze timing properties of complex features in high-performance processors using multiple-issue pipelines and instruction and data caches. The combined path and timing analysis capability is shown to derive exact estimates of the worst-case execution time for six out of seven programs in our benchmark suite. Keywords: Real-time systems, worst-case execution time, timing analysis, path analysis, symbolic execution, multiple-issue processor, caches, architecture simulation. 1.

This paper contributes a comprehensive study of a framework to bound worst-case instruction cache performance for caches with arbitrary levels of associativity. The framework is formally introduced, operationally described and its correctness is shown. Results of incorporating instruction cache predictions within pipeline simulation show that timing predictions for set-associative caches remain just as tight as predictions for direct-mapped caches. The low cache simulation overhead allows interactive use of the analysis tool and scales well with increasing associativity. The approach taken is based on a data-ow specication of the problem and provides another step toward worst-case execution time prediction of contemporary architectures and its use in schedulability analysis for hard real-time systems.

Embedded systems often have real-time constraints. Traditional timing analysis statically determines the maximum execution time of a task or a program in a real-time system. These systems typically depend on the worst-case execution time of tasks in order to make static scheduling decisions so that tasks can meet their deadlines. Static determination of worst-case execution times imposes numerous restrictions on real-time programs, which include that the maximum number of iterations of each loop must be known statically. These restrictions can significantly limit the class of programs that would be suitable for a real-time embedded system. This paper describes work-in-progress that uses static timing analysis to aid in making dynamic scheduling decisions. For instance, different algorithms with varying levels of accuracy may be selected based on the algorithm’s predicted worst-case execution time and the time allotted for the task. We represent the worstcase execution time of a function or a loop as a formula, where the unknown values affecting the execution time are parameterized. This parametric timing analysis produces formulas that can then be quickly evaluated at run-time so dynamic scheduling decisions can be made with little overhead. Benefits of this work include expanding the class of applications that can be used in a real-time system, improving the accuracy of dynamic scheduling decisions, and more effective utilization of system resources. 1.

Previously published methods for estimation of the worstcase execution time on contemporary processors with complex pipelines and multi-level memory hierarchies result in overestimations owing to insufficient path and/or timing analysis. This paper presents a new method that integrates path and timing analysis to address these limitations. First, it is based on instruction-level architecture simulation techniques and thus has a potential to perform arbitrarily detailed timing analysis of hardware platforms. Second, by extending the simulation technique with the capability of handling unknown input data values, it is possible to exclude infeasible (or false) program paths in many cases, and also calculate path information, such as bounds on number of loop iterations, without the need for annotating the programs. Finally, in order to keep the number of program paths to be analyzed at a manageable level, we have extended the simulator with a path-merging strategy. This paper presents th...

This paper describes a general approach for automatic and accurate time-bound analysis. The approach consists of transformations for building time-bound functions in the presence of partially known input structures, symbolic evaluation of the time-bound function based on input parameters, optimizations to make the overall analysis efficient as well as accurate, and measurements of primitive parameters, all at the source-language level. We have implemented this approach and performed a number of experiments for analyzing Scheme programs. The measured worst-case times are closely bounded by the calculated bounds. 1 Introduction Analysis of program running time is important for real-time systems, interactive environments, compiler optimizations, performance evaluation, and many other computer applications. It has been extensively studied in many fields of computer science: algorithms [20, 12, 13, 41], programming languages [38, 21, 30, 33], and systems [35, 28, 32, 31]. It is particularl...

Worst-Case Execution Time (WCET) analysis means to compute a safe upper bound to the execution time of a piece of code. Parametric WCET analysis yields symbolic upper bounds: expressions that may contain parameters. These parameters may represent, for instance, values of input parameters to the program, or maximal iteration counts for loops. We describe a technique for fully automatic parametric WCET analysis, which is based on known mathematical methods: an abstract interpretation to calculate parametric constraints on program flow, a symbolic method to count integer points in polyhedra, and a symbolic ILP technique to solve the subsequent IPET calculation of WCET bound. The technique is capable of handling unstructured code, and it can find upper bounds to loop iteration counts automatically.

In this article we give an overview of the Worst-Case Execution Time (WCET) analysis research performed by the WCET group of the ASTEC Competence Center at Uppsala University. The basis for this work is our modular architecture for a WCET tool, used both to identify the components of the overall WCET analysis problem, and as a starting point for the development of an industry strength WCET tool prototype. Within this framework we have proposed solutions to several key problems in WCET analysis, including representation and analysis of the control flow of programs, modeling of the behavior and timing of pipelines and other low-level timing aspects, integration of the control flow information and low-level timing to obtain a safe and tight WCET estimate, and validation of our tools and methods. We have focussed on the needs of embedded realtime systems in designing our tools and directing our research. Our long-term goal is to provide WCET analysis as a part of the standard tool chain ...

Using the constant value for the worst case execution time for all calls to a subprogram is safe but pessimistic. We address the problem of tailoring the WCET of each call to a subprogram by building the WCET as an algebraic expression parameterised with some of the subprogram parameters. The WCET of each call may then be constrained to particular ranges of values that lead to tighter WCET. The technique relies on the power of computational algebra systems to perform sophisticated simplifications and evaluation of the intermediate expressions. The same approach also allows to obtain tighter estimations of nested loop iterations which may also be tailored for different execution calls. This approach requires the description of the non-functional behaviour of the code with annotations included as specially formatted comments. Copyright c 2000 IFAC Keywords: Real-time, timing-analysis. 1.

Analysis of program running time is important for reactive systems, interactive environments, compiler optimizations, performance evaluation, and many other computer applications. It has been extensively studied in many elds of computer science: algorithms [21, 12, 13,40], programming languages [38, 22,31, 35, 34], and systems [36, 29,33,32]. Being able to predict accurate time bounds automatically and e ciently

We have used a modified C compiler to analyze a large number of commercial real-time and embedded applications written in C for 8- and 16-bit processors. Only static aspects of the programs have been studied, i.e. such information that can be obtained from the source code without running the programs. The purpose of the study is to provide guidance for the development of worst-case execution time (WCET) analysis tools, and to increase the knowledge about embedded programs in general. Knowing how real programs are written makes it easier to focus research in relevant areas and set priorities. The conclusion is that real-time and embedded programs are not necessarily simple just because they are written for small machines. This indicates that real-life WCET analysis tools need to handle advanced programming constructions, including function pointer calls and recursion. 1.# Introduction This paper describes the results of a study undertaken by the hard real-time systems...