Ronny Brendel

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The paper presents methods for instrumentation and measurement of applications’ memory allocation behavior over time. It provides some background about possible performance problems related to memory allocation as well as to memory allocator libraries. Then, different methods for data acquisition and representation are discussed. Finally, memory allocation(More)
Performance optimization, especially in the field of HPC, is an integral part of today's software development process. One powerful way of optimizing applications is to analyze their event traces. Yet, the comparison of traces of multiple application runs is cumbersome. The impact of optimizations in the source code or the usage of different compiler flags(More)
The probability density of the envelope of crystal oscillator oscillations is studied at low drives when self-excitation becomes not available due to the large and nonlinear friction of a piezoelectric resonator that occurs after a long storage. We show that the effect know as "sleeping sickness" is accompanied with the noise-induced oscillations at a new(More)
We present a symbolic-numeric method dedicated to the simulation of ultra stable quartz, oscillators entirely in the frequency domain including the nonlinear parts of the circuit. The main idea is to replace, by symbolic computation, the nonlinear differential system describing the oscillator by a system of nonlinear equations of Fourier coefficients whose(More)
The identification of performance bottlenecks in parallel applications is a challenging task. Without some form of performance measurement tool, this task lacks any guidance and purely relies on trial-and-error. At the same time, data sets from parallel performance measurements are often large and overwhelming. We provide an effective solution to(More)
The increasing complexity of high performance computing systems creates high demands on performance tools and human analysts due to an unmanageable volume of data gathered for performance analysis. A promising approach for reducing data volume is classification of data from multiple processes into groups of similar behavior to aid in analyzing application(More)
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