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program optimization USING INVARIANTS

IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 1978年第5期4卷 378-389页

作者： KATZ, S IBM-Israel Scientific Center

Compilers to "optimize" the code produced from computer programs have been in use for many years. optimization improves execution time of a program by changing or moving some of the statements and leaving the correctness of the program intact. All crucial relationships are maintained between the variables. Computations are tests are altered to reduce the time needed for computation. One technique of optimization imvolves various program transformations that are independent of the machine code. They can be applied to an intermediate-level program prior to machine code generation or directly to source-level programs. The user defines the acceptable input values for the program and the desired relationship between the input and output. "Invariant assertions" are then attached to prechosen points in the program. The correctness of the program with respect to its specifications is provided by these assertions. Figures.

关键词： Transformations Of programs Invariants program optimization Proof Of Correctness

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Graph rewrite systems for program optimization

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ACM TRANSACTIONS ON programMING LANGUAGES AND SYSTEMS 2000年第4期22卷 583-637页

作者： Assmann, U Univ Karlsruhe Inst Programmstrukturen & Datenorg D-76128 Karlsruhe Germany

Graph rewrite systems can be used to specify and generate program optimizations. For termination of the systems several rule-based criteria are developed, defining exhaustive graph reunite systems. For nondeterministic systems stratification is introduced which automatically selects single normal forms. To illustrate hew far the methodology reaches, parts of the lazy code motion optimization are specified. The resulting graph rewrite system classes can be evaluated by a uniform algorithm, which forms the basis for the optimizer generator OPTIMIX. With this tool several optimizer components have been generated, and some numbers on their speed are presented.

关键词： algorithms languages performance theory graph rewrite systems compiler generators program analysis program optimization program transformation specification stratification very high-level languages visual programming

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Scenario-based multi-period program optimization for capability-based planning using evolutionary algorithms

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APPLIED SOFT COMPUTING 2017年 56卷 717-729页

作者： Shafi, Kamran Elsayed, Saber Sarker, Ruhul Ryan, Michael Univ New South Wales Canberra SEIT Canberra ACT 2600 Australia Zagazig Univ Zagazig Egypt

Capability based planning (CBP) is a strategy focused planning framework that facilitates organizations to systematically develop capacity to achieve their business objectives in highly uncertain, dynamic and competitive environments. Capability programming is an integral part of CBP which requires selecting a portfolio of capability projects for execution, referred as a capability program, such that the overall strategic risk facing the planning organization across a number of projected future operating scenarios is minimized while maintaining the most economical choice. It is a challenging optimization problem that requires handling a number of dynamic constraints and objectives that vary throughout the entire planning horizon. An optimizing simulation approach is presented in this paper that combines an evolutionary multi-objective optimization algorithm with a reinforcement learning technique to generate capability programs which optimize strategic risks and program costs across multiple planning scenarios as well as over a rolling planning horizon. The role of the optimization algorithm in this approach is to search for the non-dominated capability programs at each decision point by minimizing the strategic risks associated with individual capability projects across a number of planning scenarios as well as the total cost of the program. The reinforcement learning algorithm, on the other hand, searches horizontally within the set of non-dominated programs to minimize capability risks and costs over the entire planning horizon. The methodology is evaluated on a test problem generated based on the data distributions in an Australian Defence Capability Plan and the performance is compared with two myopic heuristic methods. (c) 2016 Elsevier B.V. All rights reserved.

关键词： Capability-based planning program optimization Project portfolio optimization Multi-objective evolutionary optimization

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Eliminating Abstraction Overhead of Java Stream Pipelines using Ahead-of-Time program optimization

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PROCEEDINGS OF THE ACM ON programMING LANGUAGES-PACMPL 2020年第OOPSLA期4卷 1–29页

作者： Moller, Anders Veileborg, Oskar Haarklou Aarhus Univ Aarhus Denmark

Java 8 introduced streams that allow developers to work with collections of data using functional-style operations. Streams are often used in pipelines of operations for processing the data elements, which leads to concise and elegant program code. However, the declarative data processing style comes at a cost. Compared to processing the data with traditional imperative language mechanisms, constructing stream pipelines requires extra heap objects and virtual method calls, which often results in significant run-time overheads. In this work we investigate how to mitigate these overheads to enable processing data in the declarative style without sacrificing performance. We argue that ahead-of-time bytecode-to-bytecode transformation is a suitable approach to optimization of stream pipelines, and we present a static analysis that is designed to guide such transformations. Experimental results show a significant performance gain, and that the technique works for realistic stream pipelines. For 10 of 11 micro-benchmarks, the optimizer is able to produce bytecode that is as effective as hand-written imperative-style code. Additionally, 77% of 6 879 stream pipelines found in real-world Java programs are optimized successfully.

关键词： program optimization static program analysis Java 8

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High-level adaptive program optimization with ADAPT 01

High-level adaptive program optimization with ADAPT

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8th ACM SIGPLAN Symposium on the Principles and Practice of Parallel Computing

作者： Voss, MJ Eigenmann, R Purdue Univ Sch Elect & Comp Engn W Lafayette IN 47907 USA

ISBN: (纸本)9781581133462

Compile-time optimization is often limited by a lack of target machine and input data set knowledge. Without this information, compilers may be forced to make conservative assumptions to preserve correctness and to avoid performance degradation. In order to cope with this lack of information at compile-time, adaptive and dynamic systems can be used to perform optimization at runtime when complete knowledge of input and machine parameters is available. This paper presents a compiler-supported high-level adaptive optimization system. Users describe, in a domain specific language, optimizations performed by stand-alone optimization tools and backend compiler flags, as well as heuristics for applying these optimizations dynamically at runtime. The ADAPT compiler reads these descriptions and generates application-specific runtime systems to apply the heuristics. To facilitate the usage of existing tools and compilers, overheads are minimized by decoupling optimization from execution. Our system, ADAPT, supports a range of paradigms proposed recently, including dynamic compilation, parameterization and runtime sampling. We demonstrate our system by applying several optimization techniques to a suite of benchmarks on two target machines. ADAPT is shown to consistently outperform statically generated executables, improving performance by as much as 70%.

关键词： object computer Adapt compilers Runtime program optimization self-adapting program Heuristics Dynamic systems degradation of performance BENCHMARKS accuracy class

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An Effective Framework of program optimization for High Performance Computing

An Effective Framework of Program Optimization for High Perf...

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17th CCF Annual Conference on Computer Engineering and Technology (NCCET)

作者： Lu, Pingjing Li, Bao Pang, Zhengbin Zhang, Ying Wang, Shaogang Xu, Jinbo Liu, Yan Natl Univ Def Technol Sch Comp Changsha 410073 Hunan Peoples R China

ISBN: (纸本)9783642416354;9783642416347

The increasing complexity of modern architectures and memory models challenges the design of optimizing compilers. It is mandatory to perform several optimizing transformations of the original program to exploit the machine to its best, especially for scientific, computational intensive codes. Aiming at investigating the best transformation sequence and the best transformation parameters simultaneously, this paper combines polyhedral model and empirical search to create a powerful optimization framework that is capable of fully automated non-parametric transformations and automatic parameter search. The framework employs polyhedral model to facilitate the search of non-parametric code transformation composition, and designs uses Genetic Algorithms to find the optimal parameters. The framework is demonstrated on three typical computational kernels for code transformations to achieve performance that greatly exceeds the native compiler, and is significantly better than state-of-the-art polyhedral model based loop transformations and iterative compilation, generating efficient code on complex loop nests.

关键词： program optimization loop transformation polyhedral model empirical search

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KODA: Knit-program optimization by Dependency Analysis 24

KODA: Knit-Program Optimization by Dependency Analysis

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37th ACM Annual Symposium on User Interface Software and Technology (UIST)

作者： Hofmann, Megan Northeastern Univ Khoury Coll Comp Sci Boston MA 02115 USA

ISBN: (纸本)9798400706288

Digital knitting machines have the capability to reliably manufacture seamless, textured, and multi-material garments, but these capabilities are obscured by limiting CAD tools. Recent innovations in computational knitting build on emerging programming infrastructure that gives full access to the machine's capabilities but requires an extensive understanding of machine operations and execution. In this paper, we contribute a critical missing piece of the knitting-machine programming pipeline-a program optimizer. program optimization allows programmers to focus on developing novel algorithms that produce desired fabrics while deferring concerns of efficient machine operations to the optimizer. We present KODA, the Knit-program optimization by Dependency Analysis method. KODA re-orders and reduces machine instructions to reduce knitting time, increase knitting reliability, and manage boilerplate operations that adjust the machine state. The result is a system that enables programmers to write readable and intuitive knitting algorithms while producing efficient and verified programs.

关键词： program optimization Machine Knitting Digital Fabrication

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Automatic program optimization by Semantic Relaxation for Parallel Processing Accelerators

Automatic Program Optimization by Semantic Relaxation for Pa...

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作者： Liou, Jhe-Yu Arizona State University

学位级别：Ph.D., Doctor of Philosophy

Graphic Processing Units (GPUs) have become a key enabler of the big-data revolution, functioning as defacto co-processors to accelerate large-scale computation. As the GPU programming stack and tool support have matured, the technology has also become accessible to programmers. However, optimizing programs to run efficiently on GPUs requires developers to have both detailed understanding of the application logic and significant knowledge of parallel programming and GPU *** dissertation proposes GEVO, a tool for automatically tuning the performance of GPU kernels in the LLVM representation to meet desired criteria. GEVO uses population-based search to find edits to programs compiled to LLVM-IR which improves performance on desired criteria and retains required functionality. The evaluation of GEVO on the Rodinia benchmark suite demonstrates many runtime optimization techniques. One of the key insights is that semantic relaxation enables GEVO to discover these optimizations that are usually prohibited by the compiler. GEVO also explores many other optimizations, including architecture- and application-specific. A follow-up evaluation of three bioinformatics applications at their different stages of development suggests that GEVO can optimize programs as well as human experts, sometimes even into a code base that is beyond a programmer’s reach. Furthermore, to unshackle the constraint of GEVO in optimizing neural network (NN) models, GEVO-ML is proposed by extending the representation capability of GEVO, where NN models and the training/prediction process are uniformly represented in a single intermediate language. An evaluation of GEVO-ML shows that GEVO-ML can optimize network models similar to how human developers improve model design, for example, by changing learning rates or pruning non-essential parameters. These results showcase the potential of automated program optimization tools to both reduce the optimization burden for researchers and provi

关键词： Graphic Processing Units program optimization Neural network Compiler optimization techniques

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Automatic Recognition and Replacement of Cyclic Redundancy Checks for program optimization

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IEEE ACCESS 2024年 12卷 192146-192158页

作者： Arutunian, Mariam Sargsyan, Sevak Mehrabyan, Matevos Bareghamyan, Lilit Aslanyan, Hayk Russian Armenian Univ Ctr Adv Software Technol Yerevan 0051 Armenia

Cyclic redundancy check (CRC) is a fundamental error-detection mechanism widely used in digital networks and storage systems to ensure data integrity. CRC can be implemented in various ways. Some methods, like bitwise implementations, are slow and less efficient. Other approaches, such as those using lookup tables, carry-less multiplication, or CRC instructions, offer better performance. This paper presents a novel method for automatic recognition and replacement of bitwise CRC implementations with more optimized alternatives. The method begins with the detection of potential code fragments containing bitwise CRC implementations using fast and simple checks. It then computes various parameters and employs a customized symbolic execution to verify the identified candidates. Subsequently, the method substitutes the CRC code fragment with more efficient alternatives. The method is implemented in the GCC compiler as a separate pass and is open-source available. Experimental evaluation was performed for x86-64, ARM64, and RISC-V architectures, and the results demonstrated up to 91%, 98%, and 93% performance improvements respectively, highlighting the effectiveness of the proposed optimization.

关键词： Polynomials optimization Engines Software algorithms Protocols Memory management Lenses Computational complexity Buffer storage Vectors Cyclic redundancy check program analysis program optimization

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Dynamic points-to sets: A comparison with static analyses and potential applications in program understanding and optimization 01

Dynamic points-to sets: A comparison with static analyses an...

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ACM SIGPLAN - SIGSOFT Workshop on program Analysis for Software Tools and Engineering (PASTE 01)

作者： Mock, M Das, M Chambers, C Eggers, SJ Univ Washington Dept Comp Sci & Engn Seattle WA 98195 USA Microsoft Res Redmond WA 98052 USA

ISBN: (纸本)9781581134131

In this paper, we compare the behavior of pointers in C programs, as approximated by static pointer analysis algorithms, with the actual behavior of pointers when these programs are run. In order to perform this comparison, we have implemented several well known pointer analysis algorithms, and we have built an instrumentation infrastructure for tracking pointer values during program execution. Our experiments show that for a number of programs from the Spec95 and Spec2000 benchmark suites, the pointer information produced by existing scalable static pointer analyses is far worse than the actual behavior observed at run-time. These results have two implications. First, a tool like ours can be used to supplement static program understanding tools in situations where the static pointer information is too coarse to be usable. Second, a feedback-directed compiler can use profile data on pointer values to improve program performance by ignoring aliases that do not arise at run time (and inserting appropriate run-time checks to ensure safety). As an example, we were able to obtain a factor of 6 speedup on a frequently executed routine from m88ksim.

关键词： points-to analysis alias analysis dynamic analysis program understanding program optimization Calpa program instrumentation

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