A Transformational Approach to Parametric Accumulated-Cost Static Profiling

Haemmerlé, Rémy; López-García, Pedro; Liqat, Umer; Klemen, Maximiliano; Gallagher, John P.; Hermenegildo, Manuel V.

doi:10.1007/978-3-319-29604-3_11

Cited by 9 publications

(36 citation statements)

References 35 publications

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“…Other optimizations include not building equations for unreachable program parts. Table 1 shows the results of the comparison between the proposed approach and our previous, program transformation-based approach (Haemmerlé et al 2016) -New and Prev respectively from now on. Column Bench shows, for each program, the entry predicate (marked with a star, e.g., sublist * ) and the predicates that are declared as cost centers (which always include the entry predicate).…”

Section: Implementation and Experimental Resultsmentioning

confidence: 99%

“…As already said, in this case the standard cost of a single call p(x) is the sum of its accumulated costs in all the cost centers in the program. This is formalized by Theorem 1 in (Haemmerlé et al 2016), which holds under the assumption that p is a cost center. Intuitively, predicate c is "reachable" from predicate p if c = p or c can be invoked (either directly or indirectly) by p. If p is a cost center, Theorem 1 also holds if we restrict to the set of cost centers that are reachable from p, or to the set of cost centers that are descendants (in the call stack) of p. The reason is that if p is a cost center, and another cost center c (different from p) is not reachable from p, then no part of the cost of a call to p is attributed to c. This is stated in Lemma 3.…”

Section: Appendix B Additional Comments On the Relation Of The Standamentioning

confidence: 99%

“…While based on different techniques, all these analyses are aimed at inferring the standard notion of cost. Please see (Haemmerlé et al 2016) for a further discussion of related work.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A general framework for static profiling of parametric resource usage

López-García¹,

Klemen²,

Liqat³

et al. 2016

Theory and Practice of Logic Programming

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For some applications, standard resource analyses do not provide the information required. Such analyses estimate the total resource usage of a program (without executing it) as functions on input data sizes. However, some applications require knowing how such total resource usage is distributed over selected parts of a program. We propose a novel, general, and flexible framework for setting up cost equations/relations which can be instantiated for performing a wide range of resource usage analyses, including both static profiling and the inference of the standard notion of cost. We extend and generalize standard resource analysis techniques, so that the relations generated include additional Boolean control variables for switching on or off different terms in the relations, as required by the desired resource usage profile. We also instantiate our framework to perform static profiling of accumulated cost (also parameterized by input data sizes). Such information is much more useful to the software developer than the standard notion of cost: it identifies the parts of the program that have the greatest impact on the total program cost, and which therefore should be optimized first. We also report on an implementation of our framework within the CiaoPP system, and its instantiation for accumulated cost, and provide some experimental results. In addition to generality, our new method brings important advantages over our previous approach based on a program transformation, including support for non-deterministic programs, better and easier integration in the compiler, and higher efficiency.

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Section: Implementation and Experimental Resultsmentioning

confidence: 99%

Section: Appendix B Additional Comments On the Relation Of The Standamentioning

confidence: 99%

See 1 more Smart Citation

A general framework for static profiling of parametric resource usage

López-García¹,

Klemen²,

Liqat³

et al. 2016

Theory and Practice of Logic Programming

Self Cite

View full text Add to dashboard Cite

show abstract

“…The model in [36] The execution of instruction sequences may give rise to other costs beyond the cost of circuit state switching, depending on the micro architecture of the processor. Resource contention due to data dependencies between instructions may cause pipeline stalls.…”

Section: Defining and Constructing An Energy Model At Isa Levelmentioning

confidence: 99%

“…A further extension of the method of generating constraints and solving them yields static energy profiling [36], which shows the distribution of energy usage over the parts of the code, rather than a single function giving the total consumption of the program.…”

Section: More Complex Analysesmentioning

confidence: 99%

Energy-Aware Software Engineering

Eder¹,

Gallagher

2017

ICT - Energy Concepts for Energy Efficiency and Sustainability

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A great deal of energy in Information and Communication Technology (ICT) systems can be wasted by software, regardless of how energy-efficient the underlying hardware is. To avoid such waste, programmers need to understand the energy consumption of programs during the development process rather than waiting to measure energy after deployment. Such understanding is hindered by the large conceptual gap from hardware, where energy is consumed, to high-level languages and programming abstractions. The approaches described in this chapter involve two main topics: energy modelling and energy analysis. The purpose of modelling is to attribute energy values to programming constructs, whether at the level of machine instructions, intermediate code or source code. Energy analysis involves inferring the energy consumption of a program from the program semantics along with an energy model. Finally, the chapter discusses how energy analysis and modelling techniques can be incorporated in software engineering tools, including existing compilers, to assist the energy-aware programmer to optimise the energy consumption of code.

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A General Framework for Static Cost Analysis of Parallel Logic Programs

Klemen

López-García

Gallagher

et al. 2020

Logic-Based Program Synthesis and Transformation

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The estimation and control of resource usage is now an important challenge in an increasing number of computing systems. In particular, requirements on timing and energy arise in a wide variety of applications such as internet of things, cloud computing, health, transportation, and robots. At the same time, parallel computing, with (heterogeneous) multicore platforms in particular, has become the dominant paradigm in computer architecture. Predicting resource usage on such platforms poses a difficult challenge. Most work on static resource analysis has focused on sequential programs, and relatively little progress has been made on the analysis of parallel programs, or more specifically on parallel logic programs. We propose a novel, general, and flexible framework for setting up cost equations/relations which can be instantiated for performing resource usage analysis of parallel logic programs for a wide range of resources, platforms and execution models. The analysis estimates both lower and upper bounds on the resource usage of a parallel program (without executing it) as functions on input data sizes. In addition, it also infers other meaningful information to better exploit and assess the potential and actual parallelism of a system. We develop a method for solving cost relations involving the max function that arise in the analysis of parallel programs. Finally, we instantiate our general framework for the analysis of logic programs with Independent And-Parallelism, report on an implementation within the CiaoPP system, and provide some experimental results. To our knowledge, this is the first approach to the cost analysis of parallel logic programs.

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A Transformational Approach to Parametric Accumulated-Cost Static Profiling

Cited by 9 publications

References 35 publications

A general framework for static profiling of parametric resource usage

A general framework for static profiling of parametric resource usage

Energy-Aware Software Engineering

A General Framework for Static Cost Analysis of Parallel Logic Programs

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