Performance Analysis Tools Research Articles

Data Analysis and Model Validation of Natural Gas Transmission Pipeline With Compressor Station

Abstract Data from the distributed control system (DCS) or supervisory control and data acquisition (SCADA) system provide useful information critical to the evaluation of the performance and transportation efficiency of a gas pipeline system with compressor stations. The pipeline performance data provide correction factors for compressors as part of the operation optimization of natural gas transmission pipelines. This paper presents methods, procedures, and an example of model validation-based performance analysis of a gas pipeline based on actual system operational data. An analysis approach based on statistical methods is demonstrated with actual DCS gas pipeline measurement data. These methods offer practical ways to validate the pipeline hydraulics model using the DCS data. The validated models are then used as performance analysis tools in assessing the pipeline hydraulics parameters that influence the pressure drop in the pipeline such as corrosion (inside diameter change), roughness changes, or basic sediment and water deposition.

Simulation Tool for Tuning and Performance Analysis of Robust, Tracking, Disturbance Rejection and Aggressiveness Controller

The RTD-A (robust, tracking, disturbance rejection and aggressiveness) controller is a novel control scheme that substitutes the classical proportional integral derivative (PID) controller. This novel controller’s performance depends on the four controller tuning parameters (θR, θT, θD and θA). The tuning of RTD-A controller is more transparent than classic PID controllers. The RTD-A tuning parameters values lies between ZERO and ONE. Availability of a tool to design optimal parameters for this controller and evaluating the performance on a given system is necessary for the researchers. In this paper, the new simulation tool is presented to deal with the RTD-A control scheme. There are four graphical user interface tools included in the proposed tool and working of each tool is explained in detail. To demonstrate the proposed tool, two examples, which involve a liquid level control application and an air pressure control application, are presented in this work. The performance of the RTD-A controller is compared with PID controller. RTD-A controllers are tuned using optimization algorithms and their performances are observed and analyzed in both cases under deterministic and uncertain conditions.

An efficient real-time data collection framework on petascale systems

High efficiency data collection remains a great challenge for HPC reliability and resilience, yet may pave the way to overcome the barrier before fault prediction. Not only for increasing scalability up to exascale systems but even for contemporary supercomputer architectures does it require substantial efforts to efficiently collect and analyze data that contains system fault information within the framework of faults prediction. In this term, the article mainly focuses on efficient data collection and data preprocessing, preferring to optimize an effective framework to improve the efficiency of data collection in petascale system. The core of our framework includes a data collection acceleration layer scheduled by H2FS, a further detailed information get by performance analysis tool, as well as a new method for log template extraction, which all attribute to a more efficient and convenient framework for the real-time data collection. Hereafter, we conducted extensive tests based on a petascale system to verify the solution, and the experimental results demonstrate to be effectiveness and scalability of our framework.

Experimental and numerical investigations on dynamic characteristics of gear-roller-bearing system

In the present study, dynamic characteristics of gear-roller-bearing system is investigated by use of experimental test and theoretical modeling. In terms of experiment, a new test set-up dedicated to offset press is developed to measure the acceleration within a wide range of speed. After the completion of data acquisition, the vibration signals obtained from different conditions are analyzed both in time domain and frequency domain, thereby capturing the source of vibration excitation. For theoretical modeling, a novel dynamic model of gear-roller-bearing system including time-varying properties and contact nonlinearities is proposed based on the fundamental idea of finite element method, divided into the helical gear pair model, dynamic model of roller and shaft, bearing elements, shoulder iron and rubber contact elements. The unconditionally stable algorithm, known as Newmark-β method, is employed to solve the governing equations, and then the validity of mathematical model in predicting dynamic response is demonstrated by comparison with experimental results. Experimental and numerical results indicate that the proposed method can be utilized as a useful tool for parameter design and performance analysis of gear-roller-bearing system.

Comparative Analysis of Analytical and Discrete-Event Simulation Models of Assembly Line Systems

Abstract System-wide performance analysis of manufacturing setup helps a company to stay competitive. This can be done by selecting appropriate performance analysis tool which can save time and effort. As a problem assembly line systems are difficult to completely model and analyze using either of analytical or discrete-event simulation (DES) models. The main objective of this study is to analyze the distinct modeling capabilities of analytical modeling approach and DES approach so as to take their respective primacy for analysis of particular pertinent parameters suitable for Tana Communication (TC assembly line). Both analytical and discrete-event simulation models are developed for TC production process using decomposition approach and AnyLogic software. The results from the two models for work in process, queue cycle time, cycle time and resource utilization have high degree of agreement. By making reassignment of operators from the idle stage to the bottleneck stage the system waiting time and work in process is reduced by 12% and 13% respectively from the proposed model.

PAPI software-defined events for in-depth performance analysis

The methodology and standardization layer provided by the Performance Application Programming Interface (PAPI) has played a vital role in application profiling for almost two decades. It has enabled sophisticated performance analysis tool designers and performance-conscious scientists to gain insights into their applications by simply instrumenting their code using a handful of PAPI functions that “just work” across different hardware components. In the past, PAPI development had focused primarily on hardware-specific performance metrics. However, the rapidly increasing complexity of software infrastructure poses new measurement and analysis challenges for the developers of large-scale applications. In particular, acquiring information regarding the behavior of libraries and runtimes—used by scientific applications—requires low-level binary instrumentation, or APIs specific to each library and runtime. No uniform API for monitoring events that originate from inside the software stack has emerged. In this article, we present our efforts to extend PAPI’s role so that it becomes the de facto standard for exposing performance-critical events, which we refer to as software-defined events (SDEs), from different software layers. Upgrading PAPI with SDEs enables monitoring of both types of performance events—hardware- and software-related events—in a uniform way, through the same consistent PAPI. The goal of this article is threefold. First, we motivate the need for SDEs and describe our design decisions regarding the functionality we offer through PAPI’s new SDE interface. Second, we illustrate how SDEs can be utilized by different software packages, specifically, by showcasing their use in the numerical linear algebra library MAGMA-Sparse, the tensor algebra library TAMM that is part of the NWChem suite, and the compiler-based performance analysis tool Byfl. Third, we provide a performance analysis of the overhead that results from monitoring SDEs and discuss the trade-offs between overhead and functionality.

Решение прикладных задач с использованием DVM-системы

DVM-system was designed to create parallel programs of scientific-technical computations in C-DVMH and Fortran-DVMH languages. These languages use the same model of parallel programming (DVMH-model) and are the extensions of standard C and Fortran languages by parallelism specifications, implemented as compiler directives. DVMH-model allows creating efficient parallel programs for heterogeneous computational clusters, the nodes of which use as computing devices not only universal multi-core processors but also can use attached accelerators (GPUs or Intel Xeon Phi coprocessors). This article describes the experience of parallelizing various application programs using DVM-system. The method of incremental or partial parallelization, the system's capabilities for working with unstructured grids, new tools for mapping MPI-programs to multi-core processors and accelerators are considered. The efficiency of parallel DVMH-programs on heterogeneous computing clusters K-10, K-100, Lomonosov and MVS-10P is investigated. The main advantages of DVM-approach for the development of parallel programs are described. The main features of DVM-system tools for performance analysis and functional debugging of parallel programs are presented. The directions for further development of DVM-system are determined.

Novel ETX-Based Metrics for Overhead Reduction in Dynamic Ad Hoc Networks

In recent years most of wireless ad hoc networks usually include a larger number of mobile nodes. To take this into account, routing protocols, initially proposed for static networks, need to be upgraded. Higher network performance can be achieved if a suitable routing metric is included, such as frequently used Expected Transmission Count (ETX). However, with ETX metric routing overhead is increased making it unusable for networks with a large number of mobile nodes. Therefore, we proposed ETX-based routing metrics called Light ETX (L-ETX), Light Reverse ETX (LR-ETX), and Power Light Reverse ETX (PLR-ETX) that reduce overhead and improve other network performances. In order to test the impact of proposed metrics on the network performance, all three metrics are implemented in the Network Simulator 3 (NS-3) within Ad hoc On Distance Vector (AODV) routing protocol. Since the NS-3 lacks standardized tools for network performance analysis, we developed Network Performance Analysis Framework (NPAF) and use it to compare the proposed metrics. NPAF provides support for network analysis based on key performance indicators such as throughput, packet delivery ratio (PDR), useful traffic ratio (UTR), end-to-end (E2E) delay, jitter, etc. NS-3 source code extensions are publicly available.

Long-Term Memory Harris’ Hawk Optimization for High Dimensional and Optimal Power Flow Problems

Harris’ hawk optimization (HHO) is a recent addition to population-based metaheuristic paradigm, inspired from hunting behavior of Harris’ hawks. It has demonstrated promising search behavior while employed on various optimization problems, however the diversity of search agents can be further enhanced. This paper represents a novel modified variant with a long-term memory concept, hence called long-term memory HHO (LMHHO), which provides information about multiple promising regions in problem landscape, for improvised search results. With this information, LMHHO maintains exploration up to a certain level even until search termination, thus produces better results than the original method. Moreover, the study proves that appropriate tools for in-depth performance analysis can help improve search efficiency of existing metaheuristic algorithms by making simple yet effective modification in search strategy. The diversity measurement and exploration-exploitation investigations prove that the proposed LMHHO maintains trade-off balance between exploration and exploitation. The proposed approach is investigated on high-dimensional numerical optimization problems, including classic benchmark and CEC’17 functions; also, on optimal power flow problem in power generation system. The experimental study suggests that LMHHO not only outperforms the original HHO but also various other established and recently introduced metaheuristic algorithms. Although, the research can be extended by implementing more efficient memory archive and retrieval approaches for enhanced results.

On Haskell and energy efficiency

BackgroundRecent work has studied diverse affecting factors on software energy efficiency. ObjectiveThis paper attempts to shed light on the energy behavior of programs written in a lazy, purely functional programming language, Haskell. MethodologyWe conducted two in-depth and complementary studies to analyze the energy efficiency of programs from two different perspectives: strictness and concurrency. ResultsWe found that small changes can make a big difference. In one benchmark, under a specific configuration, choosing the MVar data sharing primitive over TMVar can yield 60% energy savings. In another benchmark, TMVar can yield up to 30% savings over MVar. Thus, tools that support developers in refactoring a program to switch between primitives can be very useful. In addition, the relationship between energy consumption and performance is not always clear. In sequential benchmarks, high performance is an accurate proxy for low energy consumption. However, for one of our concurrent benchmarks, the variants with the best performance also exhibited the worst energy consumption. We report on deviating cases. ConclusionsTo support developers, we have extended existing performance analysis tools to also gather and present data about energy consumption. Furthermore, we provide a set of guidelines to help Haskell developers save energy.

The Ongoing Evolution of OpenMP

This paper presents an overview of the past, present and future of the OpenMP application programming interface (API). While the API originally specified a small set of directives that guided shared memory fork-join parallelization of loops and program sections, OpenMP now provides a richer set of directives that capture a wide range of parallelization strategies that are not strictly limited to shared memory. As we look toward the future of OpenMP, we immediately see further evolution of the support for that range of parallelization strategies and the addition of direct support for debugging and performance analysis tools. Looking beyond the next major release of the specification of the OpenMP API, we expect the specification eventually to include support for more parallelization strategies and to embrace closer integration into its Fortran, C and, in particular, C++ base languages, which will likely require the API to adopt additional programming abstractions.

Understanding memory access patterns using the BSC performance tools

The growing gap between processor and memory speeds results in complex memory hierarchies as processors evolve to mitigate such divergence by taking advantage of the locality of reference. In this direction, the BSC performance analysis tools have been recently extended to provide insight relative to the application memory accesses depicting their temporal and spatial characteristics, correlating with the source-code and the achieved performance simultaneously. These extensions rely on the Precise Event-Based Sampling (PEBS) mechanism available in recent Intel processors to capture information regarding the application memory accesses. The sampled information is later combined with the Folding technique to represent a detailed temporal evolution of the memory accesses and in conjunction with the achieved performance and the source-code counterpart. The results obtained from the combination of these tools help not only application developers but also processor architects to understand better how the application behaves and how the system performs. In this paper, we describe a tighter integration of the sampling mechanism into the monitoring package. We also demonstrate the value of the complete workflow by exploring already optimized state--of--the--art benchmarks, providing detailed insight of their memory access behavior. We have taken advantage of this insight to apply small modifications that improve the applications' performance.

Roofline analysis with Cray performance analysis tools (CrayPat) and roofline‐based performance projections for a future architecture

SummaryThe roofline analysis model is a visually intuitive performance model used to understand hardware performance limitations as well as potential benefits of optimizations for science and engineering applications. Intel Advisor has provided a useful roofline analysis feature since its version 2017 update 2, but it is not widely compatible with other compilers and chip‐architectures. As an alternative, we have employed Cray Performance Analysis Tools (CrayPat) that are more flexible for multiple compilers and architectures. First, we present our procedure for measuring a reliable computational intensity for roofline analysis. We performed several numerical studies for validation via manually derived reference data as well as data from Intel Advisor. Second, we provide roofline analysis results on Blue Waters for several HPC benchmarks and sparse linear algebra libraries. In addition, we present an example of roofline‐based performance projection for a future system.

건물 에너지 성능 해석도구별 건축재료 물성정보의 비교

건물 에너지 성능 해석도구별 건축재료 물성정보의 비교

STEPS OF VERIFICATION AND VALIDATION ROUTE AIMED AT OBTAINING THE SOC MODEL ABLE TO PERFORM TARGET TASKS AND ALGORITHMS WITH SPECIFIED CHARACTERISTICS

In order to ensure the convergence of SoC design based on its performance on real applications the entire route of SoC development starting with the architectural design to the qualification tests for topological netlist should be focused on the early localization of performance issues and the confirmation of consumer characteristics of SoC before its tapeout. The article describes some of the details of of SoC verification flow, based on the convergence of performance requirements. Also the results of the work of tools used in research of SoC and its components at various abstraction levels are presented. Verification flow is based on the usage of templated test environments and unified performance analysis tools. Method of description of input stimuluses based on graphs is proposed. This method allows recovering the scenarios which discovered errors and simulateing of real traffic. Steps of system verification and validation route, oriented to the SoC model capable to perform targeted objectives and algorithms with preset characteristics are proposed. An example of a system verified by principle of performance metrics control is given.

Cuckoo search as a tool for optimal design of PM brushless DC motor

PurposeThe purpose of this paper is to perform an optimal design of a single-phase permanent magnet brushless DC motor (SPBLDCM) by using efficiency of the motor as an objective function. In the design procedure of the motor, a cuckoo search (CS) algorithm is used as an optimization tool.Design/methodology/approachFor the purpose of this research work, a computer program for optimal design of electrical machines based on the CS optimization has been developed. Based on the design characteristics of SPBLDCM, some of the motor parameters are chosen to be constant and others variable. A comparative analysis of the initial motor model and the CS model based on the value of the objective function, as well as the values of the optimization parameters, is performed and presented.FindingsBased on the comparative data analysis of both motor models, it can be concluded that the main objective of the optimization is realized, and it is achieved by an improvement of the efficiency of the motor.Practical implicationsThe optimal design approach of SPBLDCM presented in this research work can be also implemented on other electrical machines and devices using the same or even other objective functions.Originality/valueAn optimization technique using CS as an optimization tool has been developed and applied in the design procedure of SPBLDCM. According to the results, it can be concluded that the CS algorithm is a suitable tool for design optimization of SPBLDCM and electromagnetic devices in general. The quality of the CS model has been proved through the data analysis of the initial and optimized solution. The quality of the CS solution has been also proved by comparative analysis of the two motor models using FEM as a performance analysis tool.

Finite element modelling approach for precast reinforced concrete beam-to-column connections under cyclic loading

In this paper, a finite element modelling approach is developed for the analysis of the cyclic behavior of precast beam-to-column connections. In particular, the modelling takes into account the compression-softening of concrete, the bond-slip effect in the critical regions and the representation of the post-cast concrete interface. A newly developed softened damage-plasticity model, which can reproduce the typical cyclic behavior of reinforced concrete, is adopted for concrete. Meanwhile, to reflect the significant bond-slip effect between concrete and reinforcement bars, the M-P stress-strain model is modified to account for the slippage by assuming the bar strain is the sum of the bar deformation and the slip, while the anchorage slip is theoretically derived and validated through benchmarking the pull-out tests. Additionally, a concrete layer between the precast concrete and the cast-in-situ concrete is incorporated to reflect the features of the interface. The proposed numerical modelling approach is validated through simulation of both interior and exterior precast beam-to-column connection tests. The validated models are subsequently employed to investigate the influences of key factors such as the compression-softening and the bond-slip effect on the analysis of the cyclic behavior of the precast beam-to-column connections. Results demonstrate that the proposed model is capable of reproducing the typical behavior of precast beam-to-column connections and can serve as an effective tool for the seismic performance analysis and investigation of design parameters of precast connections.

A review of microgrid development in the United States – A decade of progress on policies, demonstrations, controls, and software tools

Microgrids have become increasingly popular in the United States. Supported by favorable federal and local policies, microgrid projects can provide greater energy stability and resilience within a project site or community. This paper reviews major federal, state, and utility-level policies driving microgrid development in the United States. Representative U.S. demonstration projects are selected and their technical characteristics and non-technical features are introduced. The paper discusses trends in the technology development of microgrid systems as well as microgrid control methods and interactions within the electricity market. Software tools for microgrid design, planning, and performance analysis are illustrated with each tool’s core capability. Finally, the paper summarizes the successes and lessons learned during the recent expansion of the U.S. microgrid industry that may serve as a reference for other countries developing their own microgrid industries.

Network Measurement and Performance Analysis at Server Side

Network performance diagnostics is an important topic that has been studied since the Internet was invented. However, it remains a challenging task, while the network evolves and becomes more and more complicated over time. One of the main challenges is that all network components (e.g., senders, receivers, and relay nodes) make decision based only on local information and they are all likely to be performance bottlenecks. Although Software Defined Networking (SDN) proposes to embrace a centralize network intelligence for a better control, the cost to collect complete network states in packet level is not affordable in terms of collection latency, bandwidth, and processing power. With the emergence of the new types of networks (e.g., Internet of Everything, Mission-Critical Control, data-intensive mobile apps, etc.), the network demands are getting more diverse. It is critical to provide finer granularity and real-time diagnostics to serve various demands. In this paper, we present EVA, a network performance analysis tool that guides developers and network operators to fix problems in a timely manner. EVA passively collects packet traces near the server (hypervisor, NIC, or top-of-rack switch), and pinpoints the location of the performance bottleneck (sender, network, or receiver). EVA works without detailed knowledge of application or network stack and is therefore easy to deploy. We use three types of real-world network datasets and perform trace-driven experiments to demonstrate EVA’s accuracy and generality. We also present the problems observed in these datasets by applying EVA.

A run control framework to streamline profiling, porting, and tuning simulation runs and provenance tracking of geoscientific applications

Abstract. Geoscientific modeling is constantly evolving, with next-generation geoscientific models and applications placing large demands on high-performance computing (HPC) resources. These demands are being met by new developments in HPC architectures, software libraries, and infrastructures. In addition to the challenge of new massively parallel HPC systems, reproducibility of simulation and analysis results is of great concern. This is due to the fact that next-generation geoscientific models are based on complex model implementations and profiling, modeling, and data processing workflows. Thus, in order to reduce both the duration and the cost of code migration, aid in the development of new models or model components, while ensuring reproducibility and sustainability over the complete data life cycle, an automated approach to profiling, porting, and provenance tracking is necessary. We propose a run control framework (RCF) integrated with a workflow engine as a best practice approach to automate profiling, porting, provenance tracking, and simulation runs. Our RCF encompasses all stages of the modeling chain: (1) preprocess input, (2) compilation of code (including code instrumentation with performance analysis tools), (3) simulation run, and (4) postprocessing and analysis, to address these issues. Within this RCF, the workflow engine is used to create and manage benchmark or simulation parameter combinations and performs the documentation and data organization for reproducibility. In this study, we outline this approach and highlight the subsequent developments scheduled for implementation born out of the extensive profiling of ParFlow. We show that in using our run control framework, testing, benchmarking, profiling, and running models is less time consuming and more robust than running geoscientific applications in an ad hoc fashion, resulting in more efficient use of HPC resources, more strategic code development, and enhanced data integrity and reproducibility.