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Journal articles on the topic 'Just-in-time (JIT) compiler'

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Published: 7 September 2024

Last updated: 31 July 2025

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1

Телегин, В. А. "AHEAD-OF-TIME and JUST-IN-TIME technologies." Vestnik of Russian New University. Series «Complex systems: models, analysis, management», no. 4 (December 29, 2023): 171–75. http://dx.doi.org/10.18137/rnu.v9187.23.04.p.171.

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Статья посвящена исследованию AOT- и JIT-технологий. Обосновывается актуальность и значимость темы исследования. Существует два способа компиляции приложения: своевременная компиляция ( JIT) или компиляция с опережением времени (AOT). Первый вид – это режим по умолчанию, который используется виртуальной машиной Java Hotspot для преобразования байт-кода в машинный код во время выполнения. Второй вид поддерживается новым компилятором GraalVM и позволяет статически компилировать байт-код непосредственно в машинный код во время сборки. Рассматриваются основные различия между этими двумя стратегиям

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Silva, Anderson Faustino da, and Vitor Costa. "An Experimental Evaluation of JAVA JIT Technology." JUCS - Journal of Universal Computer Science 11, no. (7) (2005): 1291–309. https://doi.org/10.3217/jucs-011-07-1291.

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Interpreted languages are widely used due to ease to use, portability, and safety. On the other hand, interpretation imposes a significance overhead. Justin Time (JIT) compilation is a popular approach to improving the runtime performance of languages such as Java. We compare the performance of a JIT compiler with a traditional compiler and with an emulator. We show that the compilation overhead from using JIT is negligible, and that the JIT compiler achieves better overall performance, suggesting the case for aggresive compilation in JIT compilers.

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Silva, Anderson Faustino da, and Vitor Costa. "Our Experiences with Optimizations in Sun's Java Just-In-Time Compilers." JUCS - Journal of Universal Computer Science 12, no. (7) (2006): 788–810. https://doi.org/10.3217/jucs-012-07-0788.

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Modern Java Compilers, such as Sun's HotSpot compilers, implement a number of optimizations, ranging from high-level program transformations to low-level architecure dependent operations such as instruction scheduling. In a Just-in-Time (JIT) environment, the impact of each optimization must be weighed against its cost in terms of total runtime. Towards better understanding the usefulness of individual optimizations, we study the main optimizations available on Sun HotSpot compilers for a wide range of scientific and non-scientific benchmarks, weighing their cost and benefits in total runtime.

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Știrb, Iulia, and Gilbert-Rainer Gillich. "A Low-Level Virtual Machine Just-In-Time Prototype for Running an Energy-Saving Hardware-Aware Mapping Algorithm on C/C++ Applications That Use Pthreads." Energies 16, no. 19 (2023): 6781. http://dx.doi.org/10.3390/en16196781.

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Low-Level Virtual Machine (LLVM) compiler infrastructure is a useful tool for building just-in-time (JIT) compilers, besides its reliable front end represented by a clang compiler and its elaborated middle end containing different optimizations that improve the runtime performance. This paper specifically addresses the part of building a JIT compiler using an LLVM with the scope of obtaining the hardware architecture details of the underlying machine such as the number of cores and the number of logical cores per processing unit and providing them to the NUMA-BTLP static thread classification

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Singh, Raju, and Anand Mehta. "Leveraging Partially Context-Sensitive Profiles for Enhanced AOT Compilation: A Review." International Journal of Engineering and Advanced Technology 14, no. 1 (2024): 6–9. http://dx.doi.org/10.35940/ijeat.a4538.14011024.

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In the realm of compiler optimization, just-in-time (JIT) compilation dynamically adjusts code execution based on runtime profiling, contrasting with the static approach of ahead-of-time (AOT) compilation. While JIT benefits from real-time profiling data, AOT lacks this advantage, necessitating innovative strategies to enhance performance without runtime feedback. This review article explores the integration of partially context-sensitive profiles into AOT compilation, offering insights into optimizing statically compiled programs through advanced profiling techniques. Also, it explores the ut

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Raju, Singh. "Leveraging Partially Context-Sensitive Profiles for Enhanced AOT Compilation: A Review." International Journal of Engineering and Advanced Technology (IJEAT) 14, no. 1 (2024): 6–9. https://doi.org/10.35940/ijeat.A4538.14011024.

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<strong>Abstract: </strong>In the realm of compiler optimization, just-in-time (JIT) compilation dynamically adjusts code execution based on runtime profiling, contrasting with the static approach of ahead-of-time (AOT) compilation. While JIT benefits from real-time profiling data, AOT lacks this advantage, necessitating innovative strategies to enhance performance without runtime feedback. This review article explores the integration of partially context-sensitive profiles into AOT compilation, offering insights into optimizing statically compiled programs through advanced profiling technique

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Agosta, Giovanni, Stefano Crespi Reghizzi, Gerlando Falauto, and Martino Sykora. "JIST: Just-In-Time Scheduling Translation for Parallel Processors." Scientific Programming 13, no. 3 (2005): 239–53. http://dx.doi.org/10.1155/2005/127158.

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The application fields of bytecode virtual machines and VLIW processors overlap in the area of embedded and mobile systems, where the two technologies offer different benefits, namely high code portability, low power consumption and reduced hardware cost. Dynamic compilation makes it possible to bridge the gap between the two technologies, but special attention must be paid to software instruction scheduling, a must for the VLIW architectures. We have implemented JIST, a Virtual Machine and JIT compiler for Java Bytecode targeted to a VLIW processor. We show the impact of various optimizations

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Serrano, Manuel. "Of JavaScript AOT compilation performance." Proceedings of the ACM on Programming Languages 5, ICFP (2021): 1–30. http://dx.doi.org/10.1145/3473575.

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The fastest JavaScript production implementations use just-in-time (JIT) compilation and the vast majority of academic publications about implementations of dynamic languages published during the last two decades focus on JIT compilation. This does not imply that static compilers (AoT) cannot be competitive; as comparatively little effort has been spent creating fast AoT JavaScript compilers, a scientific comparison is lacking. This paper presents the design and implementation of an AoT JavaScript compiler, focusing on a performance analysis. The paper reports on two experiments, one based on

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Shelke, Rahul, Aditya Kuwar, and M. Ramachandran. "A Study on Just in Time Application in Flexible Manufacturing System." 1 7, no. 1 (2021): 1–5. http://dx.doi.org/10.46632/jemm/7/1/1.

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Just-in-time 'management philosophy not process. Originally it referred to the production of goods to meet customer demand exactly, over time, quality and quantity, whether the 'customer' was the final consumer of the product or other ongoing process in the production line. A just-in-time (JIT) innovation management system that aligns green orders from direct providers with production schedules. JIT’s innovation program is opposed to intervention strategies, in which manufacturers hold sufficient lists to have sufficient product to meet the growing market demand. It is necessary to create a JI

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Zang, Zhiqiang, Fu-Yao Yu, Aditya Thimmaiah, August Shi, and Milos Gligoric. "Java JIT Testing with Template Extraction." Proceedings of the ACM on Software Engineering 1, FSE (2024): 1129–51. http://dx.doi.org/10.1145/3643777.

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We present LeJit, a template-based framework for testing Java just-in-time (JIT) compilers. Like recent template-based frameworks, LeJit executes a template---a program with holes to be filled---to generate concrete programs given as inputs to Java JIT compilers. LeJit automatically generates template programs from existing Java code by converting expressions to holes, as well as generating necessary glue code (i.e., code that generates instances of non-primitive types) to make generated templates executable. We have successfully used LeJit to test a range of popular Java JIT compilers, reveal

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Wang, Hanzhang, Wei Peng, Wenwen Wang, Yunping Lu, Pen-Chung Yew, and Weihua Zhang. "JavART: A Lightweight Rule-Based JIT Compiler using Translation Rules Extracted from a Learning Approach." Proceedings of the ACM on Programming Languages 9, OOPSLA1 (2025): 113–42. https://doi.org/10.1145/3720418.

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The balance between the compilation/optimization time and the produced code quality is very important for Just-In-Time (JIT) compilation. Time-consuming optimizations can cause delayed deployment of the optimized code, and thus more execution time needs to be spent either in the interpretation or less optimized code, leading to a performance drag. Such a performance drag can be detrimental to mobile and client-side devices such as those running Android, where applications are often shorting-running, frequently restarted and updated. To tackle this issue, this paper presents a lightweight learn

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D'Souza, Matt, James You, Ondřej Lhoták, and Aleksandar Prokopec. "TASTyTruffle: Just-in-Time Specialization of Parametric Polymorphism." Proceedings of the ACM on Programming Languages 7, OOPSLA2 (2023): 1561–88. http://dx.doi.org/10.1145/3622853.

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Parametric polymorphism enables programmers to express algorithms independently of the types of values that they operate on. The approach used to implement parametric polymorphism can have important performance implications. One popular approach, erasure, uses a uniform representation for generic data, which entails primitive boxing and other indirections that harm performance. Erasure destroys type information that could be used by language implementations to optimize generic code. We present TASTyTruffle, an implementation for a subset of the Scala programming language. Instead of JVM byteco

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Barrière, Aurèle, Sandrine Blazy, and David Pichardie. "Formally Verified Native Code Generation in an Effectful JIT: Turning the CompCert Backend into a Formally Verified JIT Compiler." Proceedings of the ACM on Programming Languages 7, POPL (2023): 249–77. http://dx.doi.org/10.1145/3571202.

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Modern Just-in-Time compilers (or JITs) typically interleave several mechanisms to execute a program. For faster startup times and to observe the initial behavior of an execution, interpretation can be initially used. But after a while, JITs dynamically produce native code for parts of the program they execute often. Although some time is spent compiling dynamically, this mechanism makes for much faster times for the remaining of the program execution. Such compilers are complex pieces of software with various components, and greatly rely on a precise interplay between the different languages

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Clemente-López, Daniel, Esteban Tlelo-Cuautle, Luis-Gerardo de la Fraga, José de Jesús Rangel-Magdaleno, and Jesus Manuel Munoz-Pacheco. "Poincaré maps for detecting chaos in fractional-order systems with hidden attractors for its Kaplan-Yorke dimension optimization." AIMS Mathematics 7, no. 4 (2022): 5871–94. http://dx.doi.org/10.3934/math.2022326.

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<abstract><p>The optimization of fractional-order (FO) chaotic systems is challenging when simulating a considerable number of cases for long times, where the primary problem is verifying if the given parameter values will generate chaotic behavior. In this manner, we introduce a methodology for detecting chaotic behavior in FO systems through the analysis of Poincaré maps. The optimization process is performed applying differential evolution (DE) and accelerated particle swarm optimization (APSO) algorithms for maximizing the Kaplan-Yorke dimension ($ D_{KY} $) of two case studies

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Alam, Marzia, Mehreen Saleem Gul, and Tariq Muneer. "Radiation View Factor for Building Applications: Comparison of Computation Environments." Energies 12, no. 20 (2019): 3826. http://dx.doi.org/10.3390/en12203826.

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Computation of view factors is required in several building engineering applications where radiative exchange takes place between surfaces such as ground and vertical walls or ground and sloping thermal or photovoltaics collectors. In this paper, view factor computations are performed for bifacial solar photovoltaic (PV) collectors based on the finite element method (FEM) using two programming languages known as Microsoft Excel-Visual Basic for Applications (VBA) and Python. The aim is to determine the computer response time as well as the performance of the two languages in terms of accuracy

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16

Osborne, Ianna, Jim Pivarski, Ioana Ifrim, Angus Hollands, and Henry Schreiner. "Awkward Just-In-Time (JIT) Compilation: A Developer’s Experience." EPJ Web of Conferences 295 (2024): 06003. http://dx.doi.org/10.1051/epjconf/202429506003.

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Awkward Array is a library for performing NumPy-like computations on nested, variable-sized data, enabling array-oriented programming on arbitrary data structures in Python. However, imperative (procedural) solutions can sometimes be easier to write or faster to run. Performant imperative programming requires compilation; JIT-compilation makes it convenient to compile in an interactive Python environment. Various functions in Awkward Arrays JIT-compile a user’s code into executable machine code. They use several different techniques, but reuse parts of each others’ implementations. We discuss

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LEE, BU-SUNG, YAN GU, WENTONG CAI, and ALFRED HENG. "PERFORMANCE EVALUATION OF JPVM." Parallel Processing Letters 09, no. 03 (1999): 401–10. http://dx.doi.org/10.1142/s0129626499000372.

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PVM for Java (JPVM) is a parallel programming environment that provides a set of Parallel Virtual Machine (PVM)-like class libraries developed using Java. JPVM inherits the attributes of Java, especially Java support of heterogeneous system. However, it also has the disadvantage of poor performance when compared to native codes. Java performance has been considerably improved with the recent introduction of Just in Time (JIT) compilers. This paper evaluates JPVM, with and without JIT compilation, using some well-known parallel processing benchmarks. It will also highlight some of the areas tha

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Ling, Jerry, and Tamás Gál. "High-performance end-user analysis in pure Julia programming language." EPJ Web of Conferences 295 (2024): 06012. http://dx.doi.org/10.1051/epjconf/202429506012.

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We present tools for high-performance analysis written in pure Julia, a just-in-time (JIT) compiled dynamic programming language with a high-level syntax and performance. The packages we present center around UnROOT.jl, a pure Julia ROOT file I/O package that is optimized for speed, lazy reading, flexibility and thread safety. We discuss what affects performance in Julia, the challenges, and their solutions during the development of UnROOT.jl. We highlight type stability as a challenge and discuss its implication whenever any “compilation” happens (incl. Numba, Jax, C++) as well as Julia’s spe

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Anand, Aditya, Solai Adithya, Swapnil Rustagi, et al. "Optimistic Stack Allocation and Dynamic Heapification for Managed Runtimes." Proceedings of the ACM on Programming Languages 8, PLDI (2024): 296–319. http://dx.doi.org/10.1145/3656389.

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The runtimes of managed object-oriented languages such as Java allocate objects on the heap, and rely on automatic garbage collection (GC) techniques for freeing up unused objects. Most such runtimes also consist of just-in-time (JIT) compilers that optimize memory access and GC times by employing escape analysis: an object that does not escape (outlive) its allocating method can be allocated on (and freed up with) the stack frame of the corresponding method. However, in order to minimize the time spent in JIT compilation, the scope of such useful analyses is quite limited, thereby restricting

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Lu, Kuan, Zhihui Yang, Sai Wu, Ruichen Xia, Dongxiang Zhang, and Gang Chen. "Adda: Towards Efficient in-Database Feature Generation via LLM-based Agents." Proceedings of the ACM on Management of Data 3, no. 3 (2025): 1–27. https://doi.org/10.1145/3725262.

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Integrating machine learning (ML) analytics into existing database management systems (DBMSs) not only eliminates the need for costly data transfers to external ML platforms but also ensures compliance with regulatory standards. While some DBMSs have integrated functionalities for training and applying ML models for analytics, these tasks still present challenges, particularly due to limited support for automatic feature engineering (AutoFE), which is crucial for optimizing ML model performance. In this paper, we introduce Adda, an agent-driven in-database feature generation tool designed to a

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Zhang, Qiang, Lei Xu, and Baowen Xu. "Python meets JIT compilers: A simple implementation and a comparative evaluation." Software: Practice and Experience, September 5, 2023. http://dx.doi.org/10.1002/spe.3267.

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AbstractDeveloping a just‐in‐time (JIT) compiler can be a daunting task, especially for a language as flexible as Python. While PyPy, powered with JIT compilation, can often outperform the official pure interpreter, CPython, by a noteworthy margin, its popularity remains far from comparable to that of CPython due to some issues. Given that an easier‐to‐deploy and better‐compatible JIT compiler would benefit more Python users, we have developed comPyler, a simple JIT compiler functioning as a CPython extension and intended to convert frequently interpreted CPython bytecode into equivalent machi

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Welsh, Ciaran, Jin Xu, Lucian Smith, Matthias König, Kiri Choi, and Herbert M. Sauro. "libRoadRunner 2.0: A High Performance SBML Simulation and Analysis Library." Bioinformatics, December 8, 2022. http://dx.doi.org/10.1093/bioinformatics/btac770.

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Abstract Motivation This paper presents libRoadRunner 2.0, an extensible, high-performance, cross-platform, open-source software library for the simulation and analysis of models expressed using the Systems Biology Markup Language (SBML). Results libRoadRunner is a self-contained library, able to run either as a component inside other tools via its C ++, C and Python APIs, or interactively through its Python or Julia interface. libRoadRunner uses a custom Just-In-Time (JIT) compiler built on the widely-used LLVM JIT compiler framework. It compiles SBML-specified models directly into native mac

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Basso, Matteo, Aleksandar Prokopec, Andrea Rosà, and Walter Binder. "Optimization-Aware Compiler-Level Event Profiling." ACM Transactions on Programming Languages and Systems, April 10, 2023. http://dx.doi.org/10.1145/3591473.

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Tracking specific events in a program’s execution, such as object allocation or lock acquisition, is at the heart of dynamic analysis. Despite the apparent simplicity of this task, quantifying these events is challenging due to the presence of compiler optimizations. Profiling perturbs the optimizations that the compiler would normally do—a profiled program usually behaves differently than the original one. In this article, we propose a novel technique for quantifying compiler-internal events in the optimized code, reducing the profiling perturbation on compiler optimizations. Our technique ac

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Vukasovic, Maja, and Aleksandar Prokopec. "Exploiting Partially Context-Sensitive Profiles to Improve Performance of Hot Code." ACM Transactions on Programming Languages and Systems, September 13, 2023. http://dx.doi.org/10.1145/3612937.

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Availability of profiling information is a major advantage of just-in-time (JIT) compilation. Profiles guide the compilation order and optimizations, thus substantially improving program performance. Ahead-of-time (AOT) compilation can also utilize profiles, obtained during separate profiling runs of the programs. Profiles can be context-sensitive, i.e., each profile entry is associated with a call-stack. To ease profile collection and reduce overheads, many systems collect partially context-sensitive profiles, which record only a call-stack suffix. Despite prior related work, partially contex

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Li, Cong, Yanyan Jiang, Chang Xu, and Zhendong Su. "Validating JIT Compilers via Compilation Space Exploration." ACM Transactions on Computer Systems, February 14, 2025. https://doi.org/10.1145/3715102.

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We introduce the concept of compilation space as a new pivot for the comprehensive validation of just-in-time (JIT) compilers in modern language virtual machines (LVMs). The compilation space of a program, encompasses a wide range of equivalent JIT-compilation choices, which can be cross-validated to ensure the correctness of the program’s JIT compilations. To thoroughly explore the compilation space in a lightweight and LVM-agnostic manner, we strategically mutate test programs with JIT-relevant but semantics-preserving code constructs, aiming to provoke diverse JIT compilation optimizations.

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Hartley, Tim. "Just In Time Compilation on ARM – A Closer Look at Call Site Code Consistency." ACM Transactions on Architecture and Code Optimization, July 6, 2022. http://dx.doi.org/10.1145/3546568.

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The increase in computational capability of low-power Arm architectures has seen them diversify from their more traditional domain of portable battery powered devices into data center servers, personal computers, and even Supercomputers. Thus, managed languages (Java, Javascript, etc.) that require a managed runtime environment (MRE) need to be ported to the Arm architecture, requiring an understanding of different design trade-offs. This paper studies how the lack of strong hardware support for Self Modifying Code (SMC) in low-power architectures (e.g. absence of cache coherence between instr

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Ducasse, Quentin, Pascal Cotret, and Loïc Lagadec. "War on JITs: Software-Based Attacks and Hybrid Defenses for JIT Compilers - A Comprehensive Survey." ACM Computing Surveys, April 19, 2025. https://doi.org/10.1145/3731598.

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Programming Language Virtual Machines (VMs) are composed of several components that together execute and manage languages efficiently. They are deployed in virtually all computing systems through modern web browsers. However, vulnerabilities in any VM component pose a significant threat to security and privacy. In this paper, we present a survey of software attacks on Just-In-Time (JIT) compilers, which dynamically produce optimized code at run time. We first present an overview and categorization of software attacks and their vectors as presented in the literature, identifying three main atta

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Wang, Chaoming, Tianqiu Zhang, Xiaoyu Chen, Sichao He, Shangyang Li, and Si Wu. "BrainPy, a flexible, integrative, efficient, and extensible framework for general-purpose brain dynamics programming." eLife 12 (December 22, 2023). http://dx.doi.org/10.7554/elife.86365.

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Elucidating the intricate neural mechanisms underlying brain functions requires integrative brain dynamics modeling. To facilitate this process, it is crucial to develop a general-purpose programming framework that allows users to freely define neural models across multiple scales, efficiently simulate, train, and analyze model dynamics, and conveniently incorporate new modeling approaches. In response to this need, we present BrainPy. BrainPy leverages the advanced just-in-time (JIT) compilation capabilities of JAX and XLA to provide a powerful infrastructure tailored for brain dynamics progr

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Silberberg, Mauro, Henning Hermjakob, Rahuman S. Malik-Sheriff, and Hernán E. Grecco. "Poincaré and SimBio: a versatile and extensible Python ecosystem for modeling systems." Bioinformatics, July 30, 2024. http://dx.doi.org/10.1093/bioinformatics/btae465.

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Abstract Motivation Chemical reaction networks (CRNs) play a pivotal role in diverse fields such as systems biology, biochemistry, chemical engineering, and epidemiology. High-level definitions of CRNs enables to use various simulation approaches, including deterministic and stochastic methods, from the same model. However, existing Python tools for simulation of CRN typically wrap external C/C ++ libraries for model definition, translation into equations and/or numerically solving them, limiting their extensibility and integration with the broader Python ecosystem. Results In response, we dev

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Briand, Luc, Hervé Jourdren, and Marc Pérache. "Julia versus C++ Kokkos for performance portable Cartesian CFD solvers on heterogeneous architectures." International Journal of High Performance Computing Applications, May 20, 2025. https://doi.org/10.1177/10943420251341179.

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Looking for high performance hydrocode simulations on heterogeneous architectures, we detail a performance portable implementation of a second-order accurate 2-D Cartesian explicit CFD solver using Julia’s Just-in-Time (JIT) compilation. In this work, a custom abstraction layer is used targeting two Julia packages, Polyester.jl for efficient shared memory multithreading on CPUs and KernelAbstractions.jl for appropriate backends on GPUs. Using very same optimizations and data structures than those used with Julia, comparisons to static C++ Kokkos compilation are then provided, including speedup

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Hope, Cathy, and Bethaney Turner. "The Right Stuff? The Original Double Jay as Site for Youth Counterculture." M/C Journal 17, no. 6 (2014). http://dx.doi.org/10.5204/mcj.898.

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On 19 January 1975, Australia’s first youth station 2JJ (Double Jay) launched itself onto the nation’s airwaves with a NASA-style countdown and You Only Like Me ‘Cause I’m Good in Bed by Australian band Skyhooks. Refused airtime by the commercial stations because of its explicit sexual content, this song was a clear signifier of the new station’s intent—to occupy a more radical territory on Australian radio. Indeed, Double Jay’s musical entrée into the highly restrictive local broadcasting environment of the time has gone on to symbolise both the station’s role in its early days as an enfant t

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Highmore, Ben. "Listlessness in the Archive." M/C Journal 15, no. 5 (2012). http://dx.doi.org/10.5204/mcj.546.

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1. Make a list of things to do2. Copy list of things left undone from previous list3. Add items to list of new things needing to be done4. Add some of the things already done from previous list and immediately cross off so as to put off the feeling of an interminable list of never accomplishable tasks5. Finish writing list and sit back feeling an overwhelming sense of listlessnessIt started so well. Get up: make list: get on. But lists can breed listlessness. It can’t always be helped. The word “list” referring to a sequence of items comes from the Italian and French words for “strip”—as in a

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Stalcup, Meg. "What If? Re-imagined Scenarios and the Re-Virtualisation of History." M/C Journal 18, no. 6 (2016). http://dx.doi.org/10.5204/mcj.1029.

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Image 1: “Oklahoma State Highway Re-imagined.” CC BY-SA 4.0 2015 by author, using Wikimedia image by Ks0stm (CC BY-SA 3 2013). Introduction This article is divided in three major parts. First a scenario, second its context, and third, an analysis. The text draws on ethnographic research on security practices in the United States among police and parts of the intelligence community from 2006 through to the beginning of 2014. Real names are used when the material is drawn from archival sources, while individuals who were interviewed during fieldwork are referred to by their position rank or titl

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