Jikes Research Virtual Machine Research Articles

Finding Good Compilation Plans: A Strategy to Enhance an Adaptive Optimization System

An important component of virtual machines is the adaptive optimization system, which decides what methods to optimize and what compiler optimization set to enable. In this context, this paper presents the development of an auto-tuning adaptive optimization system (a strategy to find good compiler optimizations), in order to obtain the best possible performance; that is, the reduction of runtime. Such system was implemented over the Jikes Research Virtual Machine, and the results indicate that the proposal is capable of achieving 11% better average performance, at a cost of less than 10% of the total runtime.

Exploring multi-threaded Java application performance on multicore hardware

While there have been many studies of how to schedule applications to take advantage of increasing numbers of cores in modern-day multicore processors, few have focused on multi-threaded managed language applications which are prevalent from the embedded to the server domain. Managed languages complicate performance studies because they have additional virtual machine threads that collect garbage and dynamically compile, closely interacting with application threads. Further complexity is introduced as modern multicore machines have multiple sockets and dynamic frequency scaling options, broadening opportunities to reduce both power and running time. In this paper, we explore the performance of Java applications, studying how best to map application and virtual machine (JVM) threads to a multicore, multi-socket environment. We explore both the cost of separating JVM threads from application threads, and the opportunity to speed up or slow down the clock frequency of isolated threads. We perform experiments with the multi-threaded DaCapo benchmarks and pseudojbb2005 running on the Jikes Research Virtual Machine, on a dual-socket, 8-core Intel Nehalem machine to reveal several novel, and sometimes counter-intuitive, findings. We believe these insights are a first but important step towards understanding and optimizing managed language performance on modern hardware.

Acculock: accurate and efficient detection of data races

SUMMARYThis paper introduces a new dynamic data race detector, ACCULOCK, to detect data races in Java programs. ACCULOCK is the first hybrid detector that combines lockset and epoch‐based happens‐before for race detection. ACCULOCK analyzes a program execution by reasoning about the subset of the happens‐before relation observed with lock acquires and releases excluded, thereby making it less sensitive to thread interleaving than pure happens‐before detectors. When this relaxed happens‐before relation is violated, ACCULOCK applies a new lockset algorithm to verify the locking discipline by distinguishing reads and writes, thereby making it more immune to false positives than pure lockset detectors. In addition, ACCULOCK is designed to achieve these design objectives by maintaining comparable instrumentation overheads (in both time and space) to that of FASTTRACK, the fastest happens‐before detector available (at least for Java programs). All these properties of ACCULOCK have been validated and confirmed by comparing it against FASTTRACK and five other (pure happens‐before, pure lockset, or hybrid) detectors, which are implemented in the Jikes Research Virtual Machine using a collection of large benchmark programs from a variety of applications. Furthermore, porting ACCULOCK and FASTTRACK to a different platform, RoadRunner, and repeating our experiments yield similar observations in terms of their effectiveness in race detection and instrumentation overheads. Copyright © 2012 John Wiley & Sons, Ltd.

A checkpointing‐enabled and resource‐aware Java Virtual Machine for efficient and robust e‐Science applications in grid environments

SUMMARYObject‐oriented programming languages presently are the dominant paradigm of application development (e.g., Java, .NET). Lately, increasingly more Java applications have long (or very long) execution times and manipulate large amounts of data/information, gaining relevance in fields related with e‐Science (with Grid and Cloud computing). Significant examples include Chemistry, Computational Biology and Bio‐informatics, with many available Java‐based APIs (e.g., Neobio).Often, when the execution of such an application is terminated abruptly because of a failure (regardless of the cause being a hardware of software fault, lack of available resources, etc.), all of its work already performed is simply lost, and when the application is later re‐initiated, it has to restart all its work from scratch, wasting resources and time, while also being prone to another failure and may delay its completion with no deadline guarantees.Our proposed solution to address these issues is through incorporating mechanisms for checkpointing and migration in a JVM. These make applications more robust and flexible by being able to move to other nodes, without any intervention from the programmer. This article provides a solution to Java applications with long execution times, by extending a JVM (Jikes research virtual machine) with such mechanisms. Copyright © 2011 John Wiley & Sons, Ltd.

Mobile JikesRVM: A framework to support transparent Java thread migration

Today’s complex applications must face the distribution of data and code among different network nodes. Computation in distributed contexts is demanding increasingly powerful languages and execution environments, able to provide programmers with appropriate abstractions and tools. Java is a wide-spread language that allows developers to build complex software, even distributed, but it cannot handle the migration of computations (i.e. threads), due to intrinsic limitations of many traditional JVMs. After analyzing the approaches in the literature, this paper presents our thread migration framework (called Mobile JikesRVM), implemented on top of the IBM Jikes Research Virtual Machine (RVM): exploiting some of the innovative techniques in the JikesRVM, we implemented an extension of its scheduler that allows applications to easily capture the state of a running thread and makes it possible to restore it elsewhere (i.e. on a different hardware architecture or operating system), but still with a version of the framework installed). Our thread serialization mechanism provides support for both proactive and reactive migration, available also for multi-threaded Java applications, and tools to deal with the problems of resource relocation management. With respect to previous approaches, we implemented Mobile JikesRVM without recompiling its JVM (Java Virtual Machine) source code, but simply extending JikesRVM functionalities with a full Java package to be imported when thread migration is needed.

A simple and efficient algorithm for cycle collection

The lack of collecting cyclic garbage is generally considered the major weakness of reference counting. Reference counted systems handle this problem by incorporating either a global tracing collector, or a "partial" tracing collector that considers only the cycle candidates but needs several traces on them. In particular, the latter has become a preferred one as it has better scalability and locality (no need to scan the entire heap). This paper presents a new "lightweight" cyclic reference counting algorithm, which is based on partial tracing and deals with the cycle problem in a simpler and more efficient way. By exploiting the lightweight hypothesis that considers a single sub-graph, instead of individual cycles, as the basic unit of cycle collection, the algorithm can detect garbage cycles in a single trace. In addition, we propose a technique for eliminating redundant scans over garbage objects, thus improving the efficiency of the algorithm. The pseudocode and its correctness proof are also presented. Finally, an implementation based on Jikes Research Virtual Machine is provided to demonstrate the effectiveness of the new algorithm.

Understanding the behavior of compiler optimizations

AbstractCompiler optimizations are difficult to implement and add complexity to a compiler. For this reason, compiler writers are selective about implementing them: they implement only the ones that they believe will be beneficial. To support compiler writers in this, we describe a method for measuring the cost and benefits of compiler optimizations, both individually and in synergy with other optimizations. We demonstrate our method by presenting results for the optimizations implemented in the Jikes Research Virtual Machine on the PowerPC and IA32 platforms. Copyright © 2006 John Wiley & Sons, Ltd.

Yama: a scalable generational garbage collector for Java in multiprocessor systems

The current state-of-the-art generational garbage collector pauses all the program threads when it performs young and old generation garbage collection. As the number of program threads increases, the delay due to garbage collection also increases, thus restricting the scalability of the collector. In order to improve the scalability and reduce the pause time, an on-the-fly generational garbage collector called Yama is proposed for multiprocessor systems. This uses the on-the-fly deferred reference counting in the young generation and the DLG (Doligez Leroy Gonthier) on-the-fly mark and sweep garbage collector in the old generation. We have proposed and experimented with two novel variations of the on-the-fly deferred reference counting called Chitragupt1 and Chitragupt2 in the young generation. Yama does not pause all the application threads simultaneously. An adaptive tenuring policy based on object reference count and survival rate is also proposed. Yama has been implemented in the IBM Jikes RVM (research virtual machine). The above claims are supported with experimental results for standard benchmark programs. The results show that Yama has an extremely low pause time in both the young and the old generation. The pause time reduction results in better response times for the user programs.

Phase-based visualization and analysis of Java programs

Extant Java Virtual Machines (JVMs) apply dynamic compiler optimizations adaptively, based on the partial execution of the program, with the goal of improving performance. Understanding and characterizing program behavior is of vital importance to such systems. Recent research, primarily in the area of computer architecture, has identified potential optimization opportunities in the repeating patterns in the time-varying behavior of programs. In view of this, we believe that by considering time-varying, i.e., phase, behavior in Java programs, adaptive JVMs can enable performance that exceeds current levels. To enable analysis and visualization of phase behavior in Java programs and to facilitate optimization development, we have implemented a freely available, offline, phase analysis framework within the IBM Jikes Research Virtual Machine (JikesRVM) for Java. The framework couples existing techniques into a unifying set of tools for data collection, processing, and analysis of dynamic phase behavior in Java programs. The framework enables optimization developers to significantly reduce analysis time and to target adaptive optimization to parts of the code that will recur with sufficient regularity. We use the framework to evaluate phase behavior in the SpecJVM benchmark suite and discuss optimizations that are enabled by the framework.

The Jikes Research Virtual Machine project: Building an open-source research community

This paper describes the evolution of the Jikes™ Research Virtual Machine project from an IBM internal research project, called Jalapeño, into an open-source project. After summarizing the original goals of the project, we discuss the motivation for releasing it as an open-source project and the activities performed to ensure the success of the project. Throughout, we highlight the unique challenges of developing and maintaining an open-source project designed specifically to support a research community.

Efficiently Adapting Java Binaries in Limited Memory Contexts

This paper presents a compilation framework that allows executable code to be shared across different Java Virtual Machine (JVM) instances. Current compliant JVMs for servers are burdened with large memory footprints (because of the size of the increasingly complicated compilers) and high startup costs, while compliant JVMs for embedded devices typically rely on interpretation. This paper describes a quasi-static approach that allows execution of a read-only version of the code, enabling compiled Java binaries to be embedded in ROM in an embedded environment or shared across multiple applications in a server environment. We have implemented this approach in the Quicksilver quasi-static compiler for the Jikes RVM (Jikes Research Virtual Machine). On the SPECjvm98 benchmark suite, our approach gives writable memory space savings of between 82–89% over that of our previous (non-sharable, non-ROMable) quasi-static approach, while delivering performance that is typically within 1–7% of that approach, and is competitive with the performance of the Jikes RVM adaptive optimization system.

Leveraging strong agent mobility for Aglets with the Mobile JikesRVM framework

Mobility enables agents to migrate among several hosts, becoming active entities of networks. Java is today one of the most exploited languages to build mobile agent systems, thanks to its object-oriented support, portability and network facilities. Nevertheless, Java does not support strong mobility , i. e. the possibility of relocating running threads along with their execution state; challenges arising from implementing strong mobility upon the JVM has led to the choice of a weaker form of agent mobility (i. e.  weak mobility ): although in many agent scenarios (e.g. in simple reactive agents) weak mobility could be enough, it usually complicates programming parallel and distributed applications, as it forces developers to structure their agent-based programs as sort of FSMs (Finite State Machine). In this paper, we present our Mobile JikesRVM framework to enable strong Java thread migration, based on the IBM Jikes Research Virtual Machine. Moreover, we show how it is possible (and often desirable) to exploit such a framework to enrich a Mobile Agent Platform, like the IBM Aglets, with strong agent mobility and to leverage software agents potential in parallel and distributed computing.