289 research outputs found
Portable and Accurate Collection of Calling-Context-Sensitive Bytecode Metrics for the Java Virtual Machine
Calling-context profiles and dynamic metrics at the bytecode level are important for profiling, workload characterization, program comprehension, and reverse engineering. Prevailing tools for collecting calling-context profiles or dynamic bytecode metrics often provide only incomplete information or suffer from limited compatibility with standard JVMs. However, completeness and accuracy of the profiles is essential for tasks such as workload characterization, and compatibility with standard JVMs is important to ensure that complex workloads can be executed. In this paper, we present the design and implementation of JP2, a new tool that profiles both the inter- and intra-procedural control flow of workloads on standard JVMs. JP2 produces calling-context profiles preserving callsite information, as well as execution statistics at the level of individual basic blocks of code. JP2 is complemented with scripts that compute various dynamic bytecode metrics from the profiles. As a case-study and tutorial on the use of JP2, we use it for cross-profiling for an embedded Java processor
One-flavour QCD at finite temperature
We present results, for heavy to moderate quark masses, of a study of
thermodynamic properties of 1-flavour QCD, using the multiboson algorithm.
Finite-size scaling behaviour is studied on lattices of size ,
and . It is shown that, for heavy quarks, the peak
of the Polyakov loop susceptibility grows linearly with the spatial volume,
indicating a first order phase transition. The deconfinement ratio and the
distribution of the norm of the Polyakov loop corroborate this result. For
moderately heavy quarks the first-order transition weakens and becomes a
crossover. We estimate the end point of the first-order phase transition to
occur at a quark mass of about 1.6 GeV.Comment: 3 pages, 3 PostScript figures; Talk presented at LAT9
A Quantitative Evaluation of the Contribution of Native Code to Java Workloads
Many performance analysis tools for Java focus on tracking executed bytecodes, but provide little support in determining the specific contribution of native code libraries. This paper introduces and assesses a portable approach for characterizing the amount of native code executed by Java applications. A profiling agent based on the JVM Tool Interface (JVMTI) accurately keeps track of all runtime transitions between bytecode and native code. It relies on a combination of JVMTI events, Java Native Interface (JNI) function interception, bytecode instrumentation, and hardware performance counters
Percolation and Magnetization in the Continuous Spin Ising Model
In the strong coupling limit the partition function of SU(2) gauge theory can
be reduced to that of the continuous spin Ising model with nearest neighbour
pair-interactions. The random cluster representation of the continuous spin
Ising model in two dimensions is derived through a Fortuin-Kasteleyn
transformation, and the properties of the corresponding cluster distribution
are analyzed. It is shown that for this model, the magnetic transition is
equivalent to the percolation transition of Fortuin-Kasteleyn clusters, using
local bond weights. These results are also illustrated by means of numerical
simulations
Platform-independent profiling in a virtual execution environment
Virtual execution environments, such as the Java virtual machine, promote platform-independent software development. However, when it comes to analyzing algorithm complexity and performance bottlenecks, available tools focus on platform-specific metrics, such as the CPU time consumption on a particular system. Other drawbacks of many prevailing profiling tools are high overhead, significant measurement perturbation, as well as reduced portability of profiling tools, which are often implemented in platform-dependent native code. This article presents a novel profiling approach, which is entirely based on program transformation techniques, in order to build a profiling data structure that provides calling-context-sensitive program execution statistics. We explore the use of platform-independent profiling metrics in order to make the instrumentation entirely portable and to generate reproducible profiles. We implemented these ideas within a Java-based profiling tool called JP. A significant novelty is that this tool achieves complete bytecode coverage by statically instrumenting the core runtime libraries and dynamically instrumenting the rest of the code. JP provides a small and flexible API to write customized profiling agents in pure Java, which are periodically activated to process the collected profiling information. Performance measurements point out that, despite the presence of dynamic instrumentation, JP causes significantly less overhead than a prevailing tool for the profiling of Java code
A first-order phase transition at the random close packing of hard spheres
Randomly packing spheres of equal size into a container consistently results
in a static configuration with a density of ~64%. The ubiquity of random close
packing (RCP) rather than the optimal crystalline array at 74% begs the
question of the physical law behind this empirically deduced state. Indeed,
there is no signature of any macroscopic quantity with a discontinuity
associated with the observed packing limit. Here we show that RCP can be
interpreted as a manifestation of a thermodynamic singularity, which defines it
as the "freezing point" in a first-order phase transition between ordered and
disordered packing phases. Despite the athermal nature of granular matter, we
show the thermodynamic character of the transition in that it is accompanied by
sharp discontinuities in volume and entropy. This occurs at a critical
compactivity, which is the intensive variable that plays the role of
temperature in granular matter. Our results predict the experimental conditions
necessary for the formation of a jammed crystal by calculating an analogue of
the "entropy of fusion". This approach is useful since it maps
out-of-equilibrium problems in complex systems onto simpler established
frameworks in statistical mechanics.Comment: 33 pages, 10 figure
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