MPI Operations Analysis

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Figure 6.23 – KAAPI Scenario D with an application composed of 188 processes.

Figure 6.24 – Behavior of the EP application of the NAS Benchmark using treemaps and the aggregation technique.

Chapter 7

Conclusion and Future Work

Traditional visualization schemes for the analysis of parallel applications are designed to handle monitoring data collected at small scale and in regular environments. The necessity of visual-ization techniques for the analysis of parallel applications on highly distributed systems, such as grids, motivated this work. Two particular problems of the traditional analysis of applications have been identified in this thesis.

The first one is the impact of the network interconnection on the execution of parallel appli-cations. This impact must be outlined in the analysis in order to better understand and improve the application performance. Traditional visualization techniques, such as the space-time repre-sentation, are widely used for the analysis of applications. These techniques, however, cannot show in the same screen the network topology and the monitoring data from the application.

This might lead to wrong conclusions during the detection of performance issues of applica-tions. The second problem is the visualization scalability of traditional techniques. Usually, the number of monitored entities that can be analyzed on the same screen is often limited to the vertical size of computer screens. Space-time representations are a clear example of this matter, being not well suited to grid applications composed of thousands of processes.

The main idea behind this thesis is to explore information visualization techniques that can be used to visualize parallel applications. Our first approach is the three dimensional visualiza-tion, where the base of this visualization is used to detail the resource/application organizavisualiza-tion, and the third axis to show the evolution of the application through time. We have implemented three different base configurations within the 3D approach: the representation of the network interconnection with application behavior; the representation of the application communication pattern and another to observe processes balance on the resources.

The second approach is the visual aggregation model, where the scalability problems of traditional visualization tools are solved through a combination of the treemap technique and the Time-Slice algorithm. This algorithm takes into account intervals of time to generate values and inject them in a hierarchical organization of the application being analyzed. This structure is then passed out to the treemap technique that renders the visualization. The visualization scalability is achieved through the aggregation model, where the levels of the hierarchy are explored to create intermediary information that can be used to help the analysis from the most detailed view to the most general one.

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Both approaches are implemented in a prototype called Triva, developed using a 3D render-ing engine called Ogre, GraphViz, some of the Pajé components, and an implementation of the squarified treemaps from scratch. The prototype has a reading mechanism that links it with the DIMVisual integration library, capable of integrating monitoring data from different sensors and formats. Synthetic traces, but also real trace data from KAAPI and MPI applications are used to validate the approaches and the implementation. KAAPI traces used in this thesis were collected in the Grid’5000 platform. Although the prototype validation is attached to these traces, the use of the generic Pajé file format allows the extension of the benefits brought by the implementa-tion to other fields and applicaimplementa-tions, from resource visualizaimplementa-tion to other types of communicaimplementa-tion libraries.

The obtained results are promising. The three-dimensional visualization, analyzed in the results Chapter, allows a better understanding of applications communications in contrast with the network topology. We were able to show in different time slices that the work stealing could benefit from more locality, since the current implementation of KAAPI do not take into account network information to perform work stealing requests. On the other hand, the results obtained with the visual aggregation model implementation allowed the visualization of the states of 100 thousand processors, generated synthetically. The treemaps defined by the Time-Slice algorithm were also generated using real trace data from KAAPI and MPI applications. We were able to identify in KAAPI traces different aspects, such as a different behavior in stealing mechanisms presented by some processes, load-balancing efficiency considering all the execution time, and the analysis of a large-scale KAAPI application, composed of almost 3 thousand processes in Grid’5000.

In summary, the main achievements of this thesis are the proposal of the 3D approach, the visual aggregation model combined with the Time-Slice technique and the Triva prototype im-plementation. Other achievements include the interaction between KAAPI and the prototype, allowing the analysis of KAAPI work stealing activities.

Next Section presents the publications that came from this thesis. Section 7.2 discusses the perspectives and implications of this thesis.

7.1 Publications

Some results of the thesis were published in the following papers:

• Visual Mapping of Program Components to Resources Representation: a 3D Analy-sis of Grid Parallel Applications. The 21st Symposium on Computer Architecture and High Performance Computing, SBAC-PAD. 2009. IEEE Press. Sao Paulo, Brazil.

– This paper presents the use of the three-dimensional approach to map parallel ap-plications components on top of a resource representation. The paper describes the abstract model that generate this 3D configuration, showing at the end some exam-ples of KAAPI parallel applications visualized together with the Grid’5000 network topology.