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Emerging from the MIST: A Connector Tool for Supporting Programming by Non-programmers
Get PDFSoftware development is an iterative process. As user re-quirements emerge software applications must be extended to support the new requirements. Typically, a programmer will add new code to an existing code base of an application to provide a new functionality. Previous research has shown that such extensions are easier when application logic is clearly separated from the user interface logic. Assuming that a programmer is already familiar with the existing code base, the task of writing the new code can be considered to be split into two sub-tasks: writing code for the application logic; that is, the actual functionality of the application; and writing code for the user interface that will expose the functionality to the end user.
The goal of this research is to reduce the effort required to create a user interface once the application logic has been created, toward supporting scientists with minimal pro-gramming knowledge to be able to create and modify pro-grams. Using a Model View Controller based architecture, various model components which contain the application logic can be built and extended. The process of creating and extending the views (user interfaces) on these model components is simplified through the use of our Malleable Interactive Software Toolkit (MIST), a tool set an infrastructure intended to simplify the design and extension of dynamically reconfigurable interfaces.
This paper focuses on one tool in the MIST suite, a connec-tor tool that enables the programmer to evolve the user interface as the application logic evolves by connecting related pieces of code together; either through simple drag-and-drop interactions or through the authoring of Python code. The connector tool exemplifies the types of tools in the MIST suite, which we expect will encourage collabora-tive development of applications by allowing users to inte-grate various components and minimizing the cost of de-veloping new user interfaces for the combined compo-nents
Visualizing the Results of a Complex Hybrid Dynamic-Static Analysis
Get PDFComplex static or hybrid static-dynamic analyses produce large quantities of structured data. In the past, this data was generally intended for use by compilers or other software tools that used the produced information to transform the application being analyzed. However, it is becomingly increasingly common for the results of these analyses to be used directly by humans. For example, in our own prior work we have developed a hybrid dynamic-static escape analysis intended to help developers identify sources of object churn within large framework-base applications. In order to facilitate human use of complex analysis results, visualizations need to be developed that allow a user to browse these results and to identify the points of interest within these large data sets. In this paper we present Hi-C, a visualization tool for our hybrid escape analysis that has been implemented as an Eclipse plugin. We show how Hi-C can help developers identify sources of object churn in a large framework-based application and how we have used the tool to assist in understanding the results of a complex analysis
User-Behavior Based Detection of Infection Onset
Get PDFA major vector of computer infection is through exploiting software or design flaws in networked applications such as the browser. Malicious code can be fetched and executed on a victim’s machine without the user’s permission, as in drive-by download (DBD) attacks. In this paper, we describe a new tool called DeWare for detecting the onset of infection delivered through vulnerable applications. DeWare explores and enforces causal relationships between computer-related human behaviors and system properties, such as file-system access and process execution. Our tool can be used to provide real time protection of a personal computer, as well as for diagnosing and evaluating untrusted websites for forensic purposes. Besides the concrete DBD detection solution, we also formally define causal relationships between user actions and system events on a host. Identifying and enforcing correct causal relationships have important applications in realizing advanced and secure operating systems. We perform extensive experimental evaluation, including a user study with 21 participants, thousands of legitimate websites (for testing false alarms), as well as 84 malicious websites in the wild. Our results show that DeWare is able to correctly distinguish legitimate download events from unauthorized system events with a low false positive rate (< 1%)
Extending the 5S Framework of Digital Libraries to support Complex Objects, Superimposed Information, and Content-Based Image Retrieval Services
Get PDFAdvanced services in digital libraries (DLs) have been developed and widely used to address the required capabilities of an assortment of systems as DLs expand into diverse application domains. These systems may require support for images (e.g., Content-Based Image Retrieval), Complex (information) Objects, and use of content at fine grain (e.g., Superimposed Information). Due to the lack of consensus on precise theoretical definitions for those services, implementation efforts often involve ad hoc development, leading to duplication and interoperability problems. This article presents a methodology to address those problems by extending a precisely specified minimal digital library (in the 5S framework) with formal definitions of aforementioned services. The theoretical extensions of digital library functionality presented here are reinforced with practical case studies as well as scenarios for the individual and integrative use of services to balance theory and practice. This methodology has implications that other advanced
services can be continuously integrated into our current extended framework whenever they are identified. The theoretical definitions and case study we present may impact future development efforts and a wide range of digital library researchers, designers, and developers
Load-Varying LINPACK: A Benchmark for Evaluating Energy Efficiency in High-End Computing
Get PDFFor decades, performance has driven the high-end computing (HEC) community. However, as highlighted in recent exascale studies that chart a path from petascale to exascale computing, power consumption is fast becoming the major design constraint in HEC. Consequently, the HEC community needs to address this issue in future petascale and exascale computing systems.
Current scientific benchmarks, such as LINPACK and SPEChpc, only evaluate HEC systems when running at full throttle, i.e., 100% workload, resulting in a focus on performance and ignoring the issues of power and energy consumption. In contrast, efforts like SPECpower evaluate the energy efficiency of a compute server at varying workloads. This is analogous to evaluating the energy efficiency (i.e., fuel efficiency) of an automobile at varying speeds (e.g., miles per gallon highway versus city). SPECpower, however, only evaluates the energy efficiency of a single compute server rather than a HEC system; furthermore, it is based on SPEC's Java Business Benchmarks (SPECjbb) rather than a scientific benchmark. Given the absence of a load-varying scientific benchmark to evaluate the energy efficiency of HEC systems at different workloads, we propose the load-varying LINPACK (LV-LINPACK) benchmark. In this paper, we identify application parameters that affect performance and provide a methodology to vary the workload of LINPACK, thus enabling a more rigorous study of energy efficiency in supercomputers, or more generally, HEC
Deterministic Global Optimization of Flapping Wing Motion for Micro Air Vehicles
Get PDFThe kinematics of a flapping plate is optimized by combining the unsteady vortex lattice
method with a deterministic global optimization algorithm. The design parameters are the
amplitudes, the mean values, the frequencies, and the phase angles of the flapping motion.
The results suggest that imposing a delay between the different oscillatory motions and
controlling the way through which the wing rotates at the end of each half stroke would
enhance the lift generation. The use of a general unsteady numerical aerodynamic model
(UVLM) and the implementation of a deterministic global optimization algorithm provide
guidance and a baseline for future efforts to identify optimal stroke trajectories for micro air vehicles with higher fidelity models
Proceedings of the Fifth Annual Virginia Tech Center for Human-Computer Interaction Research Experience for Undergraduates (REU) Symposium
Get PDFVirginia Tech's Center for Human-Computer Interaction presents the project abstracts for the REU 2010 symposium. The REU (Research Experience for Undergraduates) program provides undergraduate students from various universities with the opportunity to spend eight weeks at Virginia Tech, working with our faculty and graduate students on research projects using the state-of-the-art technology and laboratories assembled here. The REU program is sponsored primarily by the National Science Foundation (IIS-0851774, IIS-0552732). Additional support was provided by the NSF (CNS-0540509), and the VT CS Department CSRC
Parallel Load Balancing Strategies for Ensembles of Stochastic Biochemical Simulations
Get PDFThe evolution of biochemical systems where some chemical species are present with only a small number of molecules, is strongly influenced by discrete and stochastic effects that cannot be accurately captured by continuous and deterministic models. The budding yeast cell cycle provides an excellent example of the need to account for stochastic effects in biochemical reactions. To obtain statistics of the cell cycle progression, a stochastic simulation algorithm must be run thousands of times with different initial conditions and parameter values. In order to manage the computational expense involved, the large ensemble of runs needs to be executed in parallel. The CPU time for each individual task is unknown before execution, so a simple strategy of assigning an equal number of tasks per processor can lead to considerable work imbalances and loss of parallel efficiency. Moreover, deterministic analysis approaches are ill suited for assessing the effectiveness of load balancing algorithms in this context. Biological models often require stochastic simulation. Since generating an ensemble of simulation results is computationally intensive, it is important to make efficient use of computer resources. This paper presents a new probabilistic framework to analyze the performance of dynamic load balancing algorithms when applied to large ensembles of stochastic biochemical simulations. Two particular load balancing strategies (point-to-point and all-redistribution) are discussed in detail. Simulation results with a stochastic budding yeast cell cycle model conï¬rm the theoretical analysis. While this work is motivated by cell cycle modeling, the proposed analysis framework is general and can be directly applied to any ensemble simulation of biological systems where many tasks are mapped onto each processor, and where the individual compute times vary considerably among tasks
Second order adjoints for solving PDE-constrained optimization problems
Get PDFInverse problems are of utmost importance in many fields of science and engineering. In the
variational approach inverse problems are formulated as PDE-constrained optimization problems,
where the optimal estimate of the uncertain parameters is the minimizer of a certain cost
functional subject to the constraints posed by the model equations. The numerical solution
of such optimization problems requires the computation of derivatives of the model output
with respect to model parameters. The first order derivatives of a cost functional (defined
on the model output) with respect to a large number of model parameters can be calculated
efficiently through first order adjoint sensitivity analysis. Second order adjoint models
give second derivative information in the form of matrix-vector products between the Hessian
of the cost functional and user defined vectors. Traditionally, the construction of second
order derivatives for large scale models has been considered too costly. Consequently, data
assimilation applications employ optimization algorithms that use only first order derivative
information, like nonlinear conjugate gradients and quasi-Newton methods.
In this paper we discuss the mathematical foundations of second order adjoint sensitivity
analysis and show that it provides an efficient approach to obtain Hessian-vector products. We
study the benefits of using of second order information in the numerical optimization process
for data assimilation applications. The numerical studies are performed in a twin experiment
setting with a two-dimensional shallow water model. Different scenarios are considered with
different discretization approaches, observation sets, and noise levels. Optimization algorithms
that employ second order derivatives are tested against widely used methods that require
only first order derivatives. Conclusions are drawn regarding the potential benefits and the
limitations of using high-order information in large scale data assimilation problems
Iso-energy-efficiency: An approach to power-constrained parallel computation
Get PDFFuture large scale high performance supercomputer systems require high energy efficiency to achieve exaflops computational power and beyond. Despite the need to understand energy efficiency in high-performance systems, there are few techniques to evaluate energy efficiency at scale. In this paper, we propose a system-level iso-energy-efficiency model to analyze, evaluate and predict energy-performance of data intensive parallel applications with various execution patterns running on large scale power-aware clusters. Our analytical model can help users explore the effects of machine and application dependent characteristics on system energy efficiency and isolate efficient ways to scale system parameters (e.g. processor count, CPU power/frequency, workload size and network bandwidth) to balance energy use and performance. We derive our iso-energy-efficiency model and apply it to the NAS Parallel Benchmarks on two power-aware clusters. Our results indicate that the model accurately predicts total system energy consumption within 5% error on average for parallel applications with various execution and communication patterns. We demonstrate effective use of the model for various application contexts and in scalability decision-making