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About 10,000 papers for “performance visualization”

Optical System Performance Visualization

Marie Ct Robert, Robert J. Pagano A, Michael A. Stevenson Ab · 1999

Advances in computer technology have dramatically increased raytrace speeds in optical engineering software. Increases in raytrace speed have, in turn, led to new methods for evaluating optical system performance. Designers traditionally evaluate imaging system performance with spot diagrams, MTF plots, ray aberration plots, and distortion plots. These tools are invaluable for two reasons: 1) they provide the information experienced designers need to make design decisions, and 2) they require only a coarse sampling of rays. However, these tools are an indirect representation of imaging system performance. The designer must "wait and see" how the lens performs in situ. With today's computers and optical engineering software, it is now possible to evaluate imaging system performance visually as well as numerically -- prior to lens fabrication. This paper will discuss the benefits of visual characterization for various practical optical systems. Distortion, diffraction, imagery with three...

Cited by 0

Visualization of performance measures.

John K. Tsotsos (7435094), Iuliia Kotseruba (7542311), Calden Wloka (7542314) · Figshare · 2019

<p>Two examples are shown. The original stimulus image is on the left with the subject’s fixation point marked. The middle image gives the ground truth mask where if the saliency algorithm produces a predicted , our measure A will count a positive hit. The right image shows the extent of the human parafovea, the dashed circle, centered at subject’s fixation and superimposed on the GTM. Measure B will count a prediction as a hit if it falls within the marked area. Measure C and D will count a prediction as hit if measure B is a hit and the percentage of GTM area within the parafovea is sufficiently large. For these examples, 25% of the elk GTM area lies within the parafovea while the deer is 91% within. The elk image would lead to a ‘hit’ only for measures A and B whereas all the measures would count the deer as a hit.</p>

Cited by 0Open access

Visualization and Optimal Performance

Erik Peper · Bulletin of Miscellaneous Information (Royal Gardens Kew) · 2019

Wheaton, Illinois: Theosophical Society in America, 1982. (3 hours, 16 minutes) Visualization is a tool for healing and growth. A presentation of The Theosophical Society in America.

Cited by 0Open access

Swim performance visualization capability

Krishnan Balakrishnan, Steven Bodie, Duncan Thomson · 2015

The System Wide Information Management (SWIM) program within the FAA is a key infrastructure program of the Next Generation Air Transportation System (NextGen), responsible for implementing and providing governance to a Service Oriented Architecture (SOA) framework in order to enable effective sharing of information. This implementation is an ongoing evolution that requires different components at geographically different locations, developed by different entities at different times. In order to effectively plan and deploy its infrastructure, SWIM program needs to take into consideration aspects of implementation and schedule of various user programs. They must also predict future National Airspace System (NAS) Enterprise Messaging Service (NEMS) performance in order to effectively budget for and make decisions about the roll-out schedule of the Enterprise Service Bus (ESB) and present these decisions and associated rationale to the executive Capital Investment Team (CIT) on an annual basis. In this paper, we describe a software performance visualization tool that has been developed to study the performance of the ESB. We frame the issues and provide clear rationale for the need for such a tool and also describe the design principles on which this tool has been developed. Further, we present three typical use cases for this tool and conclude by suggesting other areas where this methodology can be applied.

Cited by 0

Performance Visualization at ExaScale

University of California Office of the President · California Digital Library · 2012

As petascale systems are coming on-line and exascale computing is on the horizon, scaling scientific applications to fully utilize these resources is becoming an ever increasing challenge. Understanding the intricate interplay between a simulation code, its load balancing, and its complex, transient communication patterns requires an in-depth analysis of a wide variety of performance characteristics. In this project we propose to develop new visualization and analysis techniques for all the different types of performance data begin collected as well as their relationships amongst them. Visualization is ideally suited to bridge the gap between the initial data collection and the design of an application specific analysis by enabling an efficient and intuitive exploration of the space of potentially interesting connections and correlations. Given an appropriate visualization humans are highly adept in spotting patterns and forming new hypotheses. However, visualizing performance data in an intuitive fashion is challenging as the much of the data is defined on abstract, non-spatial domains such as the communication graph or the complicated network topologies of modern hardware. Furthermore, there exist a veritable deluge of data as systems approach million way parallelism and highlighting small yet crucial anomalies becomes critical. Finally, any one aspect of performance data rarely provides the necessary insights but instead multiple aspect such as communication, flop counts, and crucial events in the simulation must be analyzed in tandem.

Cited by 0Open access

Integrating Visualization (and Visualization Experts) with Performance Analysis

Katherine E. Isaacs · 2022

Identifying and understanding poor performance is an increasingly difficult task due to the growing complexity and scale of target applications and systems. Visualization is an important tool for exploratory and comprehension-centered goals, leading to development of visualizations and visual tools from both the performance analysis and visualization communities. However, there are several obstacles to wide-spread adoption of these visual tools and techniques, such as scale and ease-of-use. Furthermore, the challenge of visualizing such large and complex data often takes precedence over the other challenges that must be solved to get these tools into the hands of users. Addressing these issues requires making trade-offs which in turn require a firm understanding of performance analysts' needs and workflows. Through several projects in performance visualization, I discuss observed barriers to designing and deploying performance visualization solutions as well as the perspective of visualization-focused experts in working in the performance analysis space. I then propose directions focusing on these gaps between the visual design and integration into performance analysis workflows.

Cited by 0Open access

Visualization of network performance using the AVS visualization system

R.O. Cleaver, Scott F. Midkiff · 2002

The authors describe a case study that demonstrates the integration of network monitoring with visualization. The AVS visualization package is used to graphically display the output of the tcpdump network monitor. The visualization system allows the user to simultaneously view multiple parameters and to discern relationships that may not be readily observable from numerical data or standard plots of data.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Cited by 1

Extensible parallel program performance visualization

Gary J Nutt, A.J. Griff, J.E. Mankovich et al. · 2002

Performance bugs have classically been difficult to identify in high performance programs. The problem arises because there is a broad spectrum of causes of performance degradation, and because it may be necessary to apply specialized diagnostics to search the performance space. The prototype tuning environment we are developing enables one to explore the performance space of a program using customized performance visualization techniques. It addresses the breadth problem by providing tools known to be useful for broad explorations, tools for inspecting specific performance bugs, and an ability to extend the observation platform by custom analysis and visualization. This paper describes the ParaVision tool that enables one to integrate various PICL-based performance tools into a single user environment.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Cited by 14

Performance quantification of visualization systems

Bruder, Valentin · OPUS Publication Server of the University of Stuttgart (University of Stuttgart) · 2022

Visualization is an important part of data analysis, complementing automatic data processing to provide insight in the data and understand the underlying structure or patterns. A visualization system describes a visualization algorithm running on a specific compute architecture or device. Runtime performance is crucial for visualization systems, especially in the context of ever-growing data sizes and complexity. One reason for this is the importance of interactivity, another is to provide the opportunity for a comprehensive investigation of generated data in a limited time frame. Providing the possibility of changing the perspective beyond the original focus has been shown to be particularly helpful for explorative data analysis. Performance optimization is also key to save costs during visualization on supercomputers due to the high demand for their compute time. Being able to predict runtime enables a better resource planning and optimized scheduling on such devices. The central research questions addressed in this thesis are threefold and build on each other: How can we quantify runtime performance of visualization systems? How to use this information to develop models for prediction, and ultimately: How to integrate both aspects in the application context? The goal is to gain a comprehensive understanding of the runtime performance of visualization systems and optimize them to save costs and improve the user experience. Despite many works in this direction, there are still open questions and challenges on how to reach this goal. One of these challenges is the diversity of compute architectures used for visualization, including devices from mobile devices to supercomputers. Most visualization algorithms profit from running in parallel. However, this poses another challenge in performance quantification due to the usage of multiple heterogeneous parallel hardware hierarchies. Typically, visualization algorithms deal with large data, sparse regions, and interactivity requirements. Further, they can be fundamentally different in their rendering approaches. All these aspects make a reliable performance prediction difficult. This thesis addresses those challenges and presents research on performance evaluation, modeling, and prediction of visualization systems, and how to translate these concepts to improve performance-critical applications. Assessing runtime performance plays a key role in understanding and improving it. A new framework for the extensive and systematic performance evaluation of interactive visualizations is introduced, to help gain a deeper understanding of runtime behavior and rendering parameter dependencies. Based on the current practice of runtime performance evaluation in literature, a database of performance measurements is created. A list of best practices on how to improve performance evaluation is compiled based on a statistical analysis of the data. Additionally, a frontend has been developed to visually compare the rendering performance data from multiple perspectives. With a fundamental understanding of an application's runtime behavior, performance can be modeled, and the model used for prediction. New techniques for different hardware systems are introduced that are typically used for the visualization of large data sets: desktop computers featuring dedicated graphics hardware and high-performance distributed memory systems. For the former, a method to predict performance on-line is used to dynamically tune volume rendering during runtime to guarantee interactivity. For image database generation on distributed memory systems, a hybrid approach for dynamic load balancing during in situ visualization is introduced. This work also explores how human perceptual properties can be used to improve the performance of visualization applications. Two novel techniques are introduced that adapt rendering quality to the human visual system by tracking the users gaze and changing the visualization accordingly. In this thesis, a special focus is set on volume rendering. Performance optimization makes it possible to use volume rendering to visualize data outside the typical use cases. Two visualization systems are presented that use volume rendering at their core: one for the interactive exploration of large dynamic graphs and one for the space-time visualization of gaze and stimulus data. Overall, this thesis advances the state of the art by introducing new ways to assess, model, and predict runtime performance of visualization systems that can be used to improve usability and realize cost savings. This is demonstrated through several applications.

Cited by 0Open access

Performance visualization using XML representations

Yu, Y., Beyls, K., D'Hollander, E. · Open Research Online (The Open University) · 2004

The intermediate representation (IR) forms the information exchanged among different passes of program compilation. The intermediate format proposed for extensibility and persistence is written in XML. In this way, the program transformations that were internal to the compiler become visible. The hierarchical structure of XML makes a natural representation for the abstract syntax tree (AST).&#13;\nA compiler can parse the program source into an IR, then output it as an XML document. Separated by orthogonal namespaces, other IRs are also presented in the same XML document, gathering program information such as dependence vectors, transforming matrices, iteration spaces dependence graphs and cache reuse distances. This XML document can be exchanged between the compiler and program visualizers for parallelism and locality.

Cited by 0

Performance evaluation visualization of ETHIAD.

Jiarong Lu (2485372), Bin Liao (714989), Yi Liu (36759) et al. · Figshare · 2025

<div> Ethereum has become a significant trading platform for financial activities such as Dapps, ICOs, and DeFi. However, it has also become a hub for criminal activities such as fraud, money laundering, and illicit fundraising. The construction of fraud detection models employing machine learning techniques is currently a mainstream research direction. Nevertheless, existing studies face significant challenges, including class imbalance in data samples and a lack of model interpretability. In this content, this work proposes a novel explainable model for Ethereum illicit account detection, ETHIAD (Ethereum Illicit Account Detection). Firstly, we pre-process the dataset by ADASYN oversampling and Lasso feature selection, etc., to more efficiently achieve feature modeling of transaction structures. Then, the ETHIAD model is trained using the XGboost algorithm, with an accuracy, precision, recall, F1 score, and AUC value of 99.70%, 99.51%, 99.02%, 99.26%, and 99.45%, respectively, the model outperforms the existing SOTA model by 0.05%−1.1%. Finally, we introduce SHAP framework to analyze the key influencing factors of illicit accounts from multiple perspectives, and the conclusions strongly enhance the explainability of the model. </div>

Cited by 0Open access

On the visualization of performance

Schwerdtfeger, R.H., Kuethe, E., Foerdergesellschaft Produkt-Marketing e.V., Koeln (Germany) · OpenGrey (Institut de l'Information Scientifique et Technique) · 1981

Bibliothek Weltwirtschaft Kiel C 138111 / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische Informationsbibliothek

Cited by 0

Visualization of Golf Performance Data

Singh, Shweta, Raza, Ahmed · KTH Publication Database DiVA (KTH Royal Institute of Technology) · 2024

Golf is a sport where performance metrics play a crucial role in understanding player capabilities and success. This thesis explores various visualization and machine learning techniques to analyze and interpret golf performance data. By visualizing key metrics such as wins, strokes, putting accuracy, and tee-to-green performance, this study aims to uncover insights into player performance trends, correlations between different aspects of the game, and outliers. Additionally, the analysis will highlight the importance of specific features in predicting overall performance, helping to identify which aspects of the game most significantly impact success. The findings from this analysis can inform coaches, players, and analysts in optimizing training strategies, improving performance, and making data-driven decisions in golf. The project will involve the creation of intuitive visualizations that offer actionable insights into various performance metrics. By leveraging these techniques, the project seeks to provide tailored benchmarks that account for the diverse demographics within the golfing community. This thesis endeavors to improve the accessibility and usability of golf performance data, thereby empowering elite golfers to make informed decisions regarding their training and competition strategies. Through a combination of innovative visualizations and robust benchmarks, this project aims to advance the field of golf performance analysis and contribute to the success of Swedish elite golfers on the international stage.

Cited by 0Open access