Visual Analytics Challenges in Analyzing Calling Context Trees

Bergel, Alexandre; Bhatele, Abhinav; Boehme, David; Gralka, Patrick; Griffin, Kevin; Hermanns, Marc-André; Okanović, Dušan; Pearce, Olga; Vierjahn, Tom

doi:10.1007/978-3-030-17872-7_14

Cited by 8 publications

(6 citation statements)

References 22 publications

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“…To reduce visual complexity and improve readability, graph data is often visualized as trees [3,29], including the case of CCTs and call graphs [1,7,42,43]. Here, we discuss related work in the area of call graphs, tree ensembles, and graphs in general.…”

Section: Related Workmentioning

confidence: 99%

Scalable Comparative Visualization of Ensembles of Call Graphs

Kesavan

Bhatia

Bhatele

et al. 2023

IEEE Trans. Visual. Comput. Graphics

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Optimizing the performance of large-scale parallel codes is critical for efficient utilization of computing resources. Code developers often explore various execution parameters, such as hardware configurations, system software choices, and application parameters, and are interested in detecting and understanding bottlenecks in different executions. They often collect hierarchical performance profiles represented as call graphs, which combine performance metrics with their execution contexts. The crucial task of exploring multiple call graphs together is tedious and challenging because of the many structural differences in the execution contexts and significant variability in the collected performance metrics (e.g., execution runtime). In this paper, we present an enhanced version of CallFlow to support the exploration of ensembles of call graphs using new types of visualizations, analysis, graph operations, and features. We introduce ensemble-Sankey, a new visual design that combines the strengths of resource-flow (Sankey) and box-plot visualization techniques. Whereas the resource-flow visualization can easily and intuitively describe the graphical nature of the call graph, the box plots overlaid on the nodes of Sankey convey the performance variability within the ensemble. Our interactive visual interface provides linked views to help explore ensembles of call graphs, e.g., by facilitating the analysis of structural differences, and identifying similar or distinct call graphs. We demonstrate the effectiveness and usefulness of our design through case studies on large-scale parallel codes.

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Section: Related Workmentioning

confidence: 99%

Scalable Comparative Visualization of Ensembles of Call Graphs

Kesavan

Bhatia

Bhatele

et al. 2023

IEEE Trans. Visual. Comput. Graphics

Self Cite

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“…5. Some performance analysis tasks [9] require analyzing large collections of similar CCTs, e.g., when they are represented per parallel CPU, resulting in aggregative approaches. VIPACT [37] shows distributions of per-CPU data as gradient halos on nodes.…”

Section: Visualizing Calling Context Treesmentioning

confidence: 99%

Designing an Interactive, Notebook-Embedded, Tree Visualization to Support Exploratory Performance Analysis

Scully-Allison¹,

Lumsden²,

Williams³

et al. 2022

Preprint

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“…Linking between source code and call graph has also been used in applications like performance analysis [12] and software maintenance [32]. Several tree-metaphors have been used for call graphs including indentation [12,27,40], node-link diagrams [17,22,35,40], icicle timelines [18], and sunbursts [14]. As the call graph served as an auxiliary view and following design study methodology guidelines of 'satisfying rather than optimizing,' we use an indented tree and node-link view for different subgraphs of the call graph, leveraging familiarity of our users while supporting their tasks.…”

Section: Related Workmentioning

confidence: 99%

CcNav: Understanding Compiler Optimizations in Binary Code

Devkota,

Aschwanden,

Kunen

et al. 2020

Preprint

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Program developers spend significant time on optimizing and tuning programs. During this iterative process, they apply optimizations, analyze the resulting code, and modify the compilation until they are satisfied. Understanding what the compiler did with the code is crucial to this process but is very time-consuming and labor-intensive. Users need to navigate through thousands of lines of binary code and correlate it to source code concepts to understand the results of the compilation and to identify optimizations. We present a design study in collaboration with program developers and performance analysts. Our collaborators work with various artifacts related to the program such as binary code, source code, control flow graphs, and call graphs. Through interviews, feedback, and pair-analytics sessions, we analyzed their tasks and workflow. Based on this task analysis and through a human-centric design process, we designed a visual analytics system Compilation Navigator (CcNav ) to aid exploration of the effects of compiler optimizations on the program. CcNav provides a streamlined workflow and a unified context that integrates disparate artifacts. CcNav supports consistent interactions across all the artifacts making it easy to correlate binary code with source code concepts. CcNav enables users to navigate and filter large binary code to identify and summarize optimizations such as inlining, vectorization, loop unrolling, and code hoisting. We evaluate CcNav through guided sessions and semi-structured interviews. We reflect on our design process, particularly the immersive elements, and on the transferability of design studies through our experience with a previous design study on program analysis.

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Visual Analytics Challenges in Analyzing Calling Context Trees

Cited by 8 publications

References 22 publications

Scalable Comparative Visualization of Ensembles of Call Graphs

Scalable Comparative Visualization of Ensembles of Call Graphs

Designing an Interactive, Notebook-Embedded, Tree Visualization to Support Exploratory Performance Analysis

CcNav: Understanding Compiler Optimizations in Binary Code

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