Observable dynamic compilation

Managed language platforms such as the Java Virtual Machine rely on a dynamic compiler to achieve high performance. Despite the benefits that dynamic compilation provides, it also introduces some challenges to program profiling. Firstly, profilers based on bytecode instrumentation may yield wrong results in the presence of an optimizing dynamic compiler, either due to not being aware of optimizations, or because the inserted instrumentation code disrupts such optimizations. To avoid such perturbations, we present a technique to make profilers based on bytecode instrumentation aware of the optimizations performed by the dynamic compiler, and make the dynamic compiler aware of the inserted code. We implement our technique for separating inserted instrumentation code from base-program code in Oracle's Graal compiler, integrating our extension into the OpenJDK Graal project. We demonstrate its significance with concrete profilers. On the one hand, we improve accuracy of existing profiling techniques, for example, to quantify the impact of escape analysis on bytecode-level allocation profiling, to analyze object life-times, and to evaluate the impact of method inlining when profiling method invocations. On the other hand, we also illustrate how our technique enables new kinds of profilers, such as a profiler for non-inlined callsites, and a testing framework for locating performance bugs in dynamic compiler implementations. Secondly, the lack of profiling support at the intermediate representation (IR) level complicates the understanding of program behavior in the compiled code. This issue cannot be addressed by bytecode instrumentation because it cannot precisely capture the occurrence of IR-level operations. Binary instrumentation is not suited either, as it lacks a mapping from the collected low-level metrics to higher-level operations of the observed program. To fill this gap, we present an easy-to-use event-based framework for profiling operations at the IR level. We integrate the IR profiling framework in the Graal compiler, together with our instrumentation-separation technique. We illustrate our approach with a profiler that tracks the execution of memory barriers within compiled code. In addition, using a deoptimization profiler based on our IR profiling framework, we conduct an empirical study on deoptimization in the Graal compiler. We focus on situations which cause program execution to switch from machine code to the interpreter, and compare application performance using three different deoptimization strategies which influence the amount of extra compilation work done by Graal. Using an adaptive deoptimization strategy, we manage to improve the average start-up performance of benchmarks from the DaCapo, ScalaBench, and Octane suites by avoiding wasted compilation work. We also find that different deoptimization strategies have little impact on steady- state performance

An incremental points-to analysis with CFL-reachability

Abstract. Developing scalable and precise points-to analyses is increasingly important for analysing and optimising object-oriented programs where pointers are used pervasively. An incremental analysis for a program updates the existing analysis information after program changes to avoid reanalysing it from scratch. This can be efficiently deployed in software development environments where code changes are often small and frequent. This paper presents an incremental approach for demand-driven context-sensitive points-to analyses based on Context-Free Language (CFL) reachability. By tracing the CFL-reachable paths traversed in computing points-to sets, we can precisely identify and recompute on demand only the points-to sets affected by the program changes made. Combined with a flexible policy for controlling the granularity of traces, our analysis achieves significant speedups with little space overhead over reanalysis from scratch when evaluated with a null dereferencing client using 14 Java benchmarks.

Boosting the precision of virtual call integrity protection with partial pointer analysis for C++

© 2017 Association for Computing Machinery. We present, Vip, an approach to boosting the precision of Virtual call Integrity Protection for large-scale real-world C++ programs (e.g., Chrome) by using pointer analysis for the first time. Vip introduces two new techniques: (1) a sound and scalable partial pointer analysis for discovering statically the sets of legitimate targets at virtual callsites from separately compiled C++ modules and (2) a lightweight instrumentation technique for performing (virtual call) integrity checks at runtime. Vip raises the bar against vtable hijacking attacks by providing stronger security guarantees than the CHA-based approach with comparable performance overhead. Vip is implemented in LLVM-3.8.0 and evaluated using SPEC programs and Chrome. Statically, Vip protects virtual calls more effectively than CHA by significantly reducing the sets of legitimate targets permitted at 20.3% of the virtual callsites per program, on average. Dynamically, Vip incurs an average (maximum) instrumentation overhead of 0.7% (3.3%), making it practically deployable as part of a compiler tool chain

木を用いた構造化並列プログラミング

High-level abstractions for parallel programming are still immature. Computations on complicated data structures such as pointer structures are considered as irregular algorithms. General graph structures, which irregular algorithms generally deal with, are difficult to divide and conquer. Because the divide-and-conquer paradigm is essential for load balancing in parallel algorithms and a key to parallel programming, general graphs are reasonably difficult. However, trees lead to divide-and-conquer computations by definition and are sufficiently general and powerful as a tool of programming. We therefore deal with abstractions of tree-based computations. Our study has started from Matsuzaki’s work on tree skeletons. We have improved the usability of tree skeletons by enriching their implementation aspect. Specifically, we have dealt with two issues. We first have implemented the loose coupling between skeletons and data structures and developed a flexible tree skeleton library. We secondly have implemented a parallelizer that transforms sequential recursive functions in C into parallel programs that use tree skeletons implicitly. This parallelizer hides the complicated API of tree skeletons and makes programmers to use tree skeletons with no burden. Unfortunately, the practicality of tree skeletons, however, has not been improved. On the basis of the observations from the practice of tree skeletons, we deal with two application domains: program analysis and neighborhood computation. In the domain of program analysis, compilers treat input programs as control-flow graphs (CFGs) and perform analysis on CFGs. Program analysis is therefore difficult to divide and conquer. To resolve this problem, we have developed divide-and-conquer methods for program analysis in a syntax-directed manner on the basis of Rosen’s high-level approach. Specifically, we have dealt with data-flow analysis based on Tarjan’s formalization and value-graph construction based on a functional formalization. In the domain of neighborhood computations, a primary issue is locality. A naive parallel neighborhood computation without locality enhancement causes a lot of cache misses. The divide-and-conquer paradigm is known to be useful also for locality enhancement. We therefore have applied algebraic formalizations and a tree-segmenting technique derived from tree skeletons to the locality enhancement of neighborhood computations.電気通信大学201

Fundamental Approaches to Software Engineering

This open access book constitutes the proceedings of the 24th International Conference on Fundamental Approaches to Software Engineering, FASE 2021, which took place during March 27–April 1, 2021, and was held as part of the Joint Conferences on Theory and Practice of Software, ETAPS 2021. The conference was planned to take place in Luxembourg but changed to an online format due to the COVID-19 pandemic. The 16 full papers presented in this volume were carefully reviewed and selected from 52 submissions. The book also contains 4 Test-Comp contributions

New techniques for adaptive program optimization

Adaptive optimization technology is a key ingredient in modern runtime systems. This technology aims at improving performance by making optimization decisions on the basis of a program’s observed behavior. Application virtual machines indeed face different and perhaps more compelling issues compared to traditional static optimizers, as dynamic language features can force the deferral of most effective optimizations until run time. In this thesis, we present novel ideas to improve adaptive optimization, focusing on two main problems: collecting fine-grained program profiles with low overhead to guide feedback-directed optimization, and supporting continuous optimization and deoptimization by diverting execution across dynamically generated code versions. We present two profiling techniques: the first works at inter-procedural level to collect calling context information for hot code portions, while the second captures cyclic-path profiles within a function’s boundaries. Both techniques rely on efficient and elegant data structures, advancing the state of the art of the theory and practice of the performance profiling literature. We then focus our attention on supporting continuous optimization through on-stack replacement (OSR) mechanisms. We devise a new OSR framework encoded entirely at intermediate-representation level, which extends the best OSR practices with the ability to perform OSR at nearly any program location. Our techniques pave the road to aggressive optimizations and debugging techniques that were not supported by previous approaches. The main technical challenge is how to automatically generate compensation code to fix the program’s state across an OSR transition between different code versions. We present a conceptual framework for OSR, distilling its essence to a core calculus with an operational semantics. Using bisimulation techniques, we describe how OSR can be correctly supported in the presence of common compiler optimizations, providing the first soundness results in this context. We implement our ideas in production systems such as Jikes RVM and the LLVM compiler toolchain, and evaluate their performance against a variety of prominent benchmarks. We investigate the end-to-end utility of our techniques in a series of case studies: we illustrate two possible applications of multi-iteration path profiling, and show how our OSR techniques advance the state of the art for MATLAB code optimization and for source-level debugging of optimized code. Part of the results of this thesis have been published in PLDI, OOPSLA, CGO, and Software Practice and Experience

An Efficient and Flexible Implementation of Aspect-Oriented Languages

Compilers for modern object-oriented programming languages generate code in a platform independent intermediate language preserving the concepts of the source language; for example, classes, fields, methods, and virtual or static dispatch can be directly identified within the intermediate code. To execute this intermediate code, state-of-the-art implementations of virtual machines perform just-in-time (JIT) compilation of the intermediate language; i.e., the virtual instructions in the intermediate code are compiled to native machine code at runtime. In this step, a declarative representation of source language concepts in the intermediate language facilitates highly efficient adaptive and speculative optimization of the running program which may not be possible otherwise. In contrast, constructs of aspect-oriented languages - which improve the separation of concerns - are commonly realized by compiling them to conventional intermediate language instructions or by driving transformations of the intermediate code, which is called weaving. This way the aspect-oriented constructs' semantics is not preserved in a declarative manner at the intermediate language level. This representational gap between aspect-oriented concepts in the source code and in the intermediate code hinders high performance optimizations and weakens features of software engineering processes like debugging support or the continuity property of incremental compilation: modifying an aspect in the source code potentially requires re-weaving multiple other modules. To leverage language implementation techniques for aspect-oriented languages, this thesis proposes the Aspect-Language Implementation Architecture (ALIA) which prescribes - amongst others - the existence of an intermediate representation preserving the aspect-oriented constructs of the source program. A central component of this architecture is an extensible and flexible meta-model of aspect-oriented concepts which acts as an interface between front-ends (usually a compiler) and back-ends (usually a virtual machine) of aspect-oriented language implementations. The architecture and the meta-model are embodied for Java-based aspect-oriented languages in the Framework for Implementing Aspect Languages (FIAL) respectively the Language-Independent Aspect Meta-Model (LIAM) which is part of the framework. FIAL generically implements the work flows required from an execution environment when executing aspects provided in terms of LIAM. In addition to the first-class intermediate representation of aspect-oriented concepts, ALIA - and the FIAL framework as its incarnation - treat the points of interaction between aspects and other modules - so-called join points - as being late-bound to an implementation. In analogy to the object-oriented terminology for late-bound methods, the join points are called virtual in ALIA. Together, the first-class representation of aspect-oriented concepts in the intermediate representation as well as treating join points as being virtual facilitate the implementation of new and effective optimizations for aspect-oriented programs. Three different instantiations of the FIAL framework are presented in this thesis, showcasing the feasibility of integrating language back-ends with different characteristics with the framework. One integration supports static aspect deployment and produces results similar to conventional aspect weavers; the woven code is executable on any standard Java virtual machine. Two instantiations are fully dynamic, where one is realized as a portable plug-in for standard Java virtual machines and the other one, called Steamloom^ALIA , is realized as a deep integration into a specific virtual machine, the Jikes Research Virtual Machine Alpern2005. While the latter instantiation is not portable, it exhibits an outstanding performance. Virtual join point dispatch is a generalization of virtual method dispatch. Thus, well established and elaborate optimization techniques from the field of virtual method dispatch are re-used with slight adaptations in Steamloom^ALIA . These optimizations for aspect-oriented concepts go beyond the generation of optimal bytecode. Especially strikingly, the power of such optimizations is shown in this thesis by the examples of the cflow dynamic property, which may be necessary to evaluate during virtual join point dispatch, and dynamic aspect deployment - i.e., the selective modification of specific join points' dispatch. In order to evaluate the optimization techniques developed in this thesis, a means for benchmarking has been developed in terms of macro-benchmarks; i.e., real-world applications are executed. These benchmarks show that for both concepts the implementation presented here is at least circa twice as fast as state-of-the-art implementations performing static optimizations of the generated bytecode; in many cases this thesis's optimizations even reach a speed-up of two orders of magnitude for the cflow implementation and even four orders of magnitude for the dynamic deployment. The intermediate representation in terms of LIAM models is general enough to express the constructs of multiple aspect-oriented languages. Therefore, optimizations of features common to different languages are available to applications written in all of them. To proof that the abstractions provided by LIAM are sufficient to act as intermediate language for multiple aspect-oriented source languages, an automated translation from source code to LIAM models has been realized for three very different and popular aspect-oriented languages: AspectJ, JAsCo and Compose*. In addition, the feasibility of translating from CaesarJ to LIAM models is shown by discussion. The use of an extensible meta-model as intermediate representation furthermore simplifies the definition of new aspect-oriented language concepts as is shown in terms of a tutorial-style example of designing a domain specific extension to the Java language in this thesis

Compilation and Code Optimization for Data Analytics

The trade-offs between the use of modern high-level and low-level programming languages in constructing complex software artifacts are well known. High-level languages allow for greater programmer productivity: abstraction and genericity allow for the same functionality to be implemented with significantly less code compared to low-level languages. Modularity, object-orientation, functional programming, and powerful type systems allow programmers not only to create clean abstractions and protect them from leaking, but also to define code units that are reusable and easily composable, and software architectures that are adaptable and extensible. The abstraction, succinctness, and modularity of high-level code help to avoid software bugs and facilitate debugging and maintenance. The use of high-level languages comes at a performance cost: increased indirection due to abstraction, virtualization, and interpretation, and superfluous work, particularly in the form of tempory memory allocation and deallocation to support objects and encapsulation. As a result of this, the cost of high-level languages for performance-critical systems may seem prohibitive. The vision of abstraction without regret argues that it is possible to use high-level languages for building performance-critical systems that allow for both productivity and high performance, instead of trading off the former for the latter. In this thesis, we realize this vision for building different types of data analytics systems. Our means of achieving this is by employing compilation. The goal is to compile away expensive language features -- to compile high-level code down to efficient low-level code