Analysis and development of Java Grande benchmarks

Mathew, J. A.; Coddington, Paul; Hawick, K. A.

doi:10.1145/304065.304101

Cited by 51 publications

(33 citation statements)

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“…To give a first evaluation of typical performance improvements achieved by the DLA compilation we have considered two well known scientific benchsuite (JavaGrande [16] and Scimark [20]) as target. The DLA technique has been implemented into our dynamic compiler, called Intermediate Language Distributed Just In Time (ILDJIT) [7], briefly described by Figure 3.…”

Section: Resultsmentioning

confidence: 99%

Dynamic Look Ahead Compilation: A Technique to Hide JIT Compilation Latencies in Multicore Environment

Campanoni

Sykora

Agosta

et al. 2009

Lecture Notes in Computer Science

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Abstract. Object-code virtualization, commonly used to achieve software portability, relies on a virtual execution environment, typically comprising an interpreter used for initial execution of methods, and a JIT for native code generation. The availability of multiple processors on current architectures makes it attractive to perform dynamic compilation in parallel with application execution. The major issue is to decide at runtime which methods to compile ahead of execution, and how much time to invest in their optimization. This research introduces an abstract model, termed Dynamic Look Ahead (DLA) compilation, which represents the available information on method calls and computational weight as a weighted graph. The graph dynamically evolves as computation proceeds. The model is then instantiated by specifying criteria for adaptively choosing the method compilation order. The DLA approach has been applied within our dynamic compiler for .NET. Experimental results are reported and analyzed, for both synthetic programs and benchmarks. The main finding is that a careful choice of method-selection criteria, based on light-weight program analysis and execution tracing, is essential to mask compilation times and to achieve higher overall performances. On multi-processors, the DLA approach is expected to challenge the traditional virtualization environments based on bytecode interpretation and JITing, thus bridging the gap between ahead-of-time and just-in-time translation.

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Section: Resultsmentioning

confidence: 99%

Dynamic Look Ahead Compilation: A Technique to Hide JIT Compilation Latencies in Multicore Environment

Campanoni

Sykora

Agosta

et al. 2009

Lecture Notes in Computer Science

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“…In addition, we analyzed four distributable applications: a re-implemented distributable version of SPECjbb2005 which we call SPECjbb2005*, a DNA database matching application [KN05], and distributable versions of the Monte Carlo and Molecular Dynamic benchmarks from the Java Grande suite [MCH99,Gra]. SPECjbb2005* differs from SPECjbb2005 by distributing the contents of certain key data structures across the "warehouses" of the benchmark to avoid unnecessary non-local accesses.…”

Section: Classificationmentioning

confidence: 99%

Class Transformations for Transparent Distribution of Java Applications.

McGachey¹,

Hosking²,

Moss³

2011

JOT

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The indirection of object accesses is a common theme for target domains as diverse as transparent distribution, persistence, and program instrumentation. Virtualizing accesses to fields and methods (by redirecting calls through accessor and indirection methods) allows interposition of arbitrary code, extending the functionality of an application beyond that intended by the original developer.We present class modifications performed by our RuggedJ transparent distribution platform for standard Java virtual machines. RuggedJ abstracts over the location of objects by implementing a single object model for local and remote objects. However the implementation of this model is complicated by the presence of native and system code; classes loaded by Java's bootstrap class loader can be rewritten only in a limited manner, and so cannot be modified to conform to RuggedJ's complex object model. We observe that system code comprises the majority of a given Java application: an average of 78% in the applications we study. We consider the constraints imposed upon pervasive class transformation within Java, and present a framework for systematically rewriting arbitrary applications. Our system accommodates all system classes, allowing both user and system classes alike to be referenced using a single object model.

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“…The micro-benchmarks provided by the Java Grande benchmark suite [11] were employed to characterise the performance of the various fundamental Java operations on both core types under Hera-JVM 3 . Figure 6 shows the difference in performance between the core types for each of the micro-benchmarks included in section one of the Java Grande Suite.…”

Section: Micro-benchmarksmentioning

confidence: 99%

Hera-JVM

McIlroy

Sventek

2010

Proceedings of the ACM International Conference on Object Oriented Programming Systems Languages and Applications

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Heterogeneous multi-core processors, such as the IBM Cell processor, can deliver high performance. However, these processors are notoriously difficult to program: different cores support different instruction set architectures, and the processor as a whole does not provide coherence between the different cores' local memories.We present Hera-JVM, an implementation of the Java Virtual Machine which operates over the Cell processor, thereby making this platforms more readily accessible to mainstream developers. Hera-JVM supports the full Java language; threads from an unmodified Java application can be simultaneously executed on both the main PowerPCbased core and on the additional SPE accelerator cores. Migration of threads between these cores is transparent from the point of view of the application, requiring no modification to Java source code or bytecode. Hera-JVM supports the existing Java Memory Model, even though the underlying hardware does not provide cache coherence between the different core types.We examine Hera-JVM's performance under a series of real-world Java benchmarks from the SpecJVM, Java Grande and Dacapo benchmark suites. These benchmarks show a wide variation in relative performance on the different core types of the Cell processor, depending upon the nature of their workload. Execution of these benchmarks on Hera-JVM can achieve speedups of up to 2.25x by using one of the Cell processor's SPE accelerator cores, compared to execution on the main PowerPC-based core. When all six SPE cores are exploited, parallel workloads can achieve speedups of up to 13x compared to execution on the single PowerPC core.

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Analysis and development of Java Grande benchmarks

Cited by 51 publications

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Dynamic Look Ahead Compilation: A Technique to Hide JIT Compilation Latencies in Multicore Environment

Dynamic Look Ahead Compilation: A Technique to Hide JIT Compilation Latencies in Multicore Environment

Class Transformations for Transparent Distribution of Java Applications.

Hera-JVM

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