Extending the Functionality of Score-P Through Plugins: Interfaces and Use Cases

Schöne, Robert; Tschüter, Ronny; Ilsche, Thomas; Schuchart, Joseph; Hackenberg, Daniel; Nagel, Wolfgang E.

doi:10.1007/978-3-319-56702-0_4

Cited by 15 publications

(7 citation statements)

References 19 publications

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“…The READEX Runtime Library (RRL) will be based on Score-P and will be implemented as a substrate plugin [16]. Substrate plugins may access all management information and events generated from the instrumentation, e.g., through compiler, library, or user instrumentation.…”

Section: Readex Runtime Librarymentioning

confidence: 99%

The READEX formalism for automatic tuning for energy efficiency

et al. 2017

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Energy efficiency is an important aspect of future exascale systems, mainly due to rising energy cost. Although High performance computing (HPC) applications are compute centric, they still exhibit varying computational characteristics in different regions of the program, such as compute-, memory-, and I/O-bound code regions. Some of today's clusters already offer mechanisms to adjust the system to the resource requirements of an application, e.g., by controlling the CPU frequency. However, manually tuning for improved energy efficiency is a tedious and painstaking task that is often neglected by application developers. The European Union's Horizon 2020 project READEX (Runtime Exploitation of Application Dynamism for Energyefficient eXascale computing) aims at developing a tools-aided approach for improved energy efficiency of current and future HPC applications. To reach this goal, the READEX project combines technologies from two ends of the compute spectrum, embedded systems and HPC, constituting a split design-time/runtime methodology. dynamic auto-tuning of fine-grained application regions using the systems scenario methodology, which was originally developed for improving the energy efficiency in embedded systems. This paper introduces the concepts of the READEX project, its envisioned implementation, and preliminary results that demonstrate the feasibility of this approach.

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Section: Readex Runtime Librarymentioning

confidence: 99%

The READEX formalism for automatic tuning for energy efficiency

et al. 2017

Self Cite

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“…The former, Score-P, is a performance measurement infrastructure for profiling, event tracing, and online analysis of parallel applications, with a strong focus on user code instrumentation by the insertion of calls to the measurement system into the application, either fully automatically at compile-time, or with a certain amount of control handed to the software developer. Score-P makes use of a common plugin interface [25] to standardize the gathering of metrics, so additional metrics can be easily added. The traces generated with Score-P are used by a number of analysis tools, including Scalasca [9], Vampir [44], and TAU [33].…”

Section: A Glance At Analysis Techniquesmentioning

confidence: 99%

Experiences on the characterization of parallel applications in embedded systems with Extrae/Paraver

Munera

Royuela

Llort

et al. 2020

49th International Conference on Parallel Processing - ICPP

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Cutting-edge functionalities in embedded systems require the use of parallel architectures to meet their performance requirements. This imposes the introduction of a new layer in the software stacks of embedded systems: the parallel programming model. Unfortunately, the tools used to analyze embedded systems fall short to characterize the performance of parallel applications at a parallel programming model level, and correlate this with information about non-functional requirements such as real-time, energy, memory usage, etc. HPC tools, like Extrae, are designed with that level of abstraction in mind, but their main focus is on performance evaluation. Overall, providing insightful information about the performance of parallel embedded applications at the parallel programming model level, and relate it to the non-functional requirements, is of paramount importance to fully exploit the performance capabilities of parallel embedded architectures. This paper contributes to the state-of-the-art of analysis tools for embedded systems by: (1) analyzing the particular constraints of embedded systems compared to HPC systems (e.g., static setting, restricted memory, limited drivers) to support HPC analysis tools; (2) porting Extrae, a powerful tracing tool from the HPC domain, to the GR740 platform, a SoC used in the space domain; and (3) augmenting Extrae with new features needed to correlate the parallel execution with the following non-functional requirements: energy, temperature and memory usage. Finally, the paper presents the usefulness of Extrae to characterize OpenMP applications and its non-functional requirements, evaluating different aspects of the applications running in the GR740. CCS CONCEPTS • Software and its engineering → Parallel programming languages; Empirical software validation; Software performance; • Computer systems organization → Embedded systems; • Hardware → Power estimation and optimization; Temperature monitoring.

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“…Finally, the tool is also equipped with an API, which allows the user to extend its functionalities through plugins [11]. The combined solution proposed by this paper takes indeed the form of such a plugin.…”

Section: Performance Measurementmentioning

confidence: 99%

Enhancing the in Situ Visualization of Performance Data in Parallel CFD Applications

Alves

Knüpfer

2020

JSFI

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This paper continues the work initiated by the authors on the feasibility of using ParaView as visualization software for the analysis of parallel CFD codes' performance. Current performance tools are unable to show their data on top of complex simulation geometries (e.g. an aircraft engine). In our previous paper, a plugin for the open-source performance tool Score-P has been introduced, which intercepts an arbitrary number of manually selected code regions (mostly functions) and send their respective measurements-amount of executions and cumulative time spent-to ParaView (through its in situ library, Catalyst), as if they are any other flow-related variable. This paper adds to such plugin the capacity to also show communication data (messages sent between MPI ranks) on top of the CFD mesh. Testing is done again with Rolls-Royce's in-house CFD code, Hydra. The plugin's original feature (regions' measurements) is here revisited, in a bigger test-case, which is also used to illustrate the new feature (communication data). The benefits and overhead of the tool are discussed.

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Extending the Functionality of Score-P Through Plugins: Interfaces and Use Cases

Cited by 15 publications

References 19 publications

The READEX formalism for automatic tuning for energy efficiency

The READEX formalism for automatic tuning for energy efficiency

Experiences on the characterization of parallel applications in embedded systems with Extrae/Paraver

Enhancing the in Situ Visualization of Performance Data in Parallel CFD Applications

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