Performance Of Different Implementations Research Articles

Projected performance of green infrastructure strategies for flood mitigation in the Ganges-Brahmaputra-Meghna delta

Background: The Ganges-Brahmaputra-Meghna (GBM) delta – the world’s most populous river delta – faces heightened susceptibility to the rise in flooding disasters due to climate change, impacting millions annually. Current flood management strategies are unsustainable and ineffective, and resilient flood management is needed. A promising alternative is the strategic implementation of green infrastructure (GI) applications, which have proven effective in flood management in other regions. Methods: An analysis of the region’s past and future vulnerability to flooding is conducted. Then, green infrastructure performance metrics from regions with similar climatic conditions are extrapolated for the GBM. Green roofs, permeable pavements, and rain gardens were identified as the most suitable GI types for the GBM. Finally, computer simulations were employed to analyze the performance of different implementations of GI within a model city. Results: The simulations showed that 0% green rooftop coverage, 100% permeable pavement coverage, and 40% rain garden coverage were the most feasible GI layout. This configuration resulted in the most preferable balance between cost effectiveness and reduced runoff. Green rooftops were minimized due to high installation costs relative to their retention capacity, whereas permeable pavements and rain garden coverage were maximized. Conclusions: The studies show GI’s potential for flood mitigation and resilience in the GBM region. GI initiatives align with the region's flood mitigation policies and are thus feasible to implement with aid from government incentives. Furthermore, the computer program developed for this analysis could serve as a valuable tool for assessing GI implementation limits and offering guidance to policymakers.

Quantum simulation of excited states from parallel contracted quantum eigensolvers

Computing excited-state properties of molecules and solids is considered one of the most important near-term applications of quantum computers. While many of the current excited-state quantum algorithms differ in circuit architecture, specific exploitation of quantum advantage, or result quality, one common feature is their rooting in the Schrödinger equation. However, through contracting (or projecting) the eigenvalue equation, more efficient strategies can be designed for near-term quantum devices. Here we demonstrate that when combined with the Rayleigh–Ritz variational principle for mixed quantum states, the ground-state contracted quantum eigensolver (CQE) can be generalized to compute any number of quantum eigenstates simultaneously. We introduce two excited-state (anti-Hermitian) CQEs that perform the excited-state calculation while inheriting many of the remarkable features of the original ground-state version of the algorithm, such as its scalability. To showcase our approach, we study several model and chemical Hamiltonians and investigate the performance of different implementations.

Accurate finite-difference micromagnetics of magnets including RKKY interaction: Analytical solution and comparison to standard micromagnetic codes

Within this paper we show the importance of accurate implementations of the Ruderman-Kittel-Kasuya-Yosida (RKKY) interactions for antiferromagnetically coupled ferromagnetic layers with thicknesses exceeding the exchange length. In order to evaluate the performance of different implementations of RKKY interaction, we develop a benchmark problem by deriving the analytical formula for the saturation field of two infinitely thick magnetic layers that are antiparallelly coupled. This benchmark problem shows that state of the art implementations in commonly used finite-difference codes lead to errors of the saturation field that amount to more than 20% for mesh sizes of 2 nm which is well below the exchange length of the material. In order to improve the accuracy, we develop higher order cell-based and nodal-based finite-difference codes that significantly reduce the error compared to state of the art implementations. For the second order cell-based approach and first order nodal-based approach the error of the saturation field is reduced by about a factor of 10 (2% error) for the same mesh size of 2 nm.

Performance evaluation of the three-point angular correlation function

Abstract In recent years, we have observed an increase in the diversity of the processors ecosystem. Different designs and architectures are being studied based on their performance and power characteristics. While using benchmarks for this purpose allows for reproducibility and easy understanding of the results, using real scientific applications allows researchers to realize the actual implications of each design on the overall performance of their codes. This paper analyzes the performance of different implementations of a three-point angular correlation function. This function is used in the study of Large-Scale Distribution of galaxies in a variety of computational platforms. The function is based on histogram construction and presents a large computational cost. This cost dramatically increases with the size of the datasets. We have considered two different GPUs, a set of x86 Intel machines (multi- and many-core), ARM chipsets, as well as an FPGA. We first study the best possible implementation for each platform in terms of time to solution. We then compare the power used by those platforms for a predefined number of datasets. Energy is one of the main constraints that computer architects are facing nowadays. The results will be used to evaluate the performance of this function considering those two targets – time and energy – for those platforms and to analyze the suitability of each of those platforms for this specific problem.

On using landscape metrics for landscape similarity search

Landscape similarity search involves finding landscapes from among a large collection that are similar to a query landscape. An example of such collection is a large land cover map subdivided into a grid of smaller local landscapes, a query is a local landscape of interest, and the task is to find other local landscapes within a map which are perceptually similar to the query. Landscape search and the related task of pattern-based regionalization, requires a measure of similarity – a function which quantifies the level of likeness between two landscapes. The standard approach is to use the Euclidean distance between vectors of landscape metrics derived from the two landscapes, but no in-depth analysis of this approach has been conducted. In this paper we investigate the performance of different implementations of the standard similarity measure. Five different implementations are tested against each other and against a control similarity measure based on histograms of class co-occurrence features and the Jensen–Shannon divergence. Testing consists of a series of numerical experiments combined with visual assessments on a set of 400 3km-scale landscapes. Based on the cases where visual assessment provides definitive answer, we have determined that the standard similarity measure is sensitive to the way landscape metrics are normalized and, additionally, to whether weights aimed at controlling the relative contribution of landscape composition vs. configuration are used. The standard measure achieves the best performance when metrics are normalized using their extreme values extracted from all possible landscapes, not just the landscapes in the given collection, and when weights are assigned so the combined influence of composition metrics on the similarity value equals the combined influence of configuration metrics. We have also determined that the control similarity measure outperforms all implementations of the standard measure.

Analysis of the performance of different implementations of a heuristic method to optimize forest harvest scheduling

Finding an optimal solution of forest management scheduling problems with even flow constraints while addressing spatial concerns is not an easy task. Solving these combinatorial problems exactly with mixed-integer programming (MIP) methods may be infeasible or else involve excessive computational costs. This has prompted the use of heuristics. In this paper we analyze the performance of different implementations of the Simulated Annealing (SA) heuristic algorithm for solving three typical harvest scheduling problems. Typically SA consists of searching a better solution by changing one decision choice in each iteration. In forest planning this means that one treatment schedule in a single stand is changed in each iteration (i.e. one-opt move). We present a comparison of the performance of the typical implementation of SA with the new implementation where up to three decision choices are changed simultaneously in each iteration (i.e. treatment schedules are changed in more than one stand). This may allow avoiding local optimal. In addition, the impact of SA - parameters (i.e. cooling schedule and initial temperature) are tested. We compare our heuristic results with a MIP formulation. The study case is tested in a real forest with 1000 stands and a total of 213116 decision choices. The study shows that when the combinatorial problem is very large, changing simultaneously the treatment schedule in more than one stand does not improve the performance of SA. Contrarily, if we reduce the size of the problem (i.e. reduce considerably the number of alternatives per stand) the two-opt moves approach performs better.

The R-linear convergence rate of an algorithm arising from the semi-smooth Newton method applied to 2D contact problems with friction

The goal is to analyze the semi-smooth Newton method applied to the solution of contact problems with friction in two space dimensions. The primal-dual algorithm for problems with the Tresca friction law is reformulated by eliminating primal variables. The resulting dual algorithm uses the conjugate gradient method for inexact solving of inner linear systems. The globally convergent algorithm based on computing a monotonously decreasing sequence is proposed and its R-linear convergence rate is proved. Numerical experiments illustrate the performance of different implementations including the Coulomb friction law.

Efficiency of Semi-Implicit Schemes for Anisotropic Diffusion in the Hypercube

Semi-implicit schemes have been recently shown to speed up nonlinear diffusion in hyperspectral images while increasing the accuracy of subsequent classifiers in thematic mapping. Here, we show how semi-implicit schemes can be used to implement a truly anisotropic diffusion method for hyperspectral images, and we test the performance of different implementations in terms of computational overhead, speed, numerical accuracy, and thematic mapping performance. In addition, truly anisotropic trace-based diffusion formulations, besides a more precise steering of the diffusion processes, also allow implementation by means of local oriented Gaussian masks. We show how the implementations with the highest numerical accuracy can be also the simplest and fastest while still increasing the classification performance.

Real-time priority processing on an embedded CE device

Consumer electronic products are increasingly becoming more open and flexible, which is achieved by replacing dedicate, single-function hardware components by software components running on programmable platforms. Scalable video algorithms (SVAs) using the novel principle of priority processing can guarantee real-time performance on these platforms even with limited resources. In this paper we describe the mapping of a priority-processing application on an embedded consumer platform comprising a general purpose processor and multiple stream processing elements. An application comprises one or more independent, competing priority-processing algorithms. These SVAs have a single, dedicated streaming processor at their disposal. Dynamic resource allocation is required to maximize the overall output quality of SVAs that are executed on a shared platform. To enable real-time processing of individual SVAs, we compare the performance of different implementations for dynamic-resource-allocation mechanisms. Finally, we show that priority processing achieves real-time performance even under tight resource constraints.

Compressive sensing scalp EEG signals: implementations and practical performance

Highly miniaturised, wearable computing and communication systems allow unobtrusive, convenient and long term monitoring of a range of physiological parameters. For long term operation from the physically smallest batteries, the average power consumption of a wearable device must be very low. It is well known that the overall power consumption of these devices can be reduced by the inclusion of low power consumption, real-time compression of the raw physiological data in the wearable device itself. Compressive sensing is a new paradigm for providing data compression: it has shown significant promise in fields such as MRI; and is potentially suitable for use in wearable computing systems as the compression process required in the wearable device has a low computational complexity. However, the practical performance very much depends on the characteristics of the signal being sensed. As such the utility of the technique cannot be extrapolated from one application to another. Long term electroencephalography (EEG) is a fundamental tool for the investigation of neurological disorders and is increasingly used in many non-medical applications, such as brain-computer interfaces. This article investigates in detail the practical performance of different implementations of the compressive sensing theory when applied to scalp EEG signals.

Dynamic resource allocation for real-time priority processing applications

Flexible signal processing on programmable platforms are increasingly important for consumer electronic applications and others. Scalable video algorithms (SVAs) using novel priority processing can guarantee real-time performance on programmable platforms even with limited resources. Dynamic resource allocation is required to maximize the overall output quality of independent, competing priority processing algorithms that are executed on a shared platform. In this paper, we describe basic mechanisms for dynamic resource allocation and compare the performance of different implementations on a general purpose platform.

Remote Didactic Laboratory “G. Savastano,” The Italian Experience for E-Learning at the Technical Universities in the Field of Electrical and Electronic Measurement: Architecture and Optimization of the Communication Performance Based on Thin Client Technology

The Remote Didactic Laboratory <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Laboratorio Didattico Remoto</i> -LA.DI.RE. “G. Savastano” is an e-learning measurement laboratory supported by the Italian Ministry of Education and University. It provides the students of electric and electronic measurement courses with access to remote measurement laboratories, delivering different didactic activities related to measurement experiments. The core of the software architecture is the integration of the Learning Management System (LMS) with the remotely accessible measurement laboratories through web services and thin client paradigm, providing a new approach to remote experiments on measurement instrumentation. The overview of this paper is on the different solutions concerning the thin client technology, and the solution implemented is described. This solution takes into account the delivered services to students and teachers and permits optimization of the communication performances. The results of the comparison among the performances of different implementations of the thin client paradigm highlight the advantages of the adopted solution. As a consequence, the description of the thin client protocol implemented, together with the presentation of the LMS and delivered services given in a previous paper, makes an exhaustive analysis of the software architecture of the LA.DI.RE. “G. Savastano.”

Language Support for Multi-Paradigm and Multi-Grain Parallelism on Smp-Cluster

The characteristics of large-scale parallel applications are multi-paradigm and multi-grain parallel in essence. The key factor in improving the performance of parallel application systems is to determine suitable parallel paradigms and grains according to the nature of the practical problem. Therefore, it is necessary to provide multi-paradigm and multi-grain parallel programming interface for development of large-scale parallel application systems. This paper proposes a multi-paradigm and multi-grain parallel execution model integrated coarse-grain parallelism (paralleled by macro tasks), mid-grain parallelism (paralleled by basic program blocks), and fine-grain parallelism (paralleled in repetition blocks). This model also supports the task parallel, data parallel, and sequential executing. In this paper we also discuss the programming mechanism of this model by extended OpenMP specification. The extensions include computing resource partition, defining different grain task groups, mapping from task groups to the respective processor groups, out-of-core computing, asynchronous parallel I/O , and definition of sequential relationship of tasks. We compare the performance of different implementations of benchmark, using the same numerical algorithm but employing different programming approaches, including MPI, MPI+OpenMP, and our extended OpenMP. We also discuss a case based on SMP-Cluster and network storage architecture.

Performances of Wang-Landau algorithms for continuous systems

The relative performances of different implementations of the Wang-Landau method are assessed on two classes of systems with continuous degrees of freedom, namely, two polypeptides and two atomic Lennard-Jones clusters. Parallel tempering Monte Carlo simulations serve as a reference, and we pay particular attention to the variations of the multiplicative factor f during the course of the simulation. For the systems studied, the Wang-Landau method is found to be of comparable accuracy as parallel tempering, but has significant difficulties in reproducing low-temperature transitions exhibited by the Lennard-Jones clusters at low temperature. Using a complementary order parameter and calculating a two-dimensional joint density of states significantly improves the situation, especially for the notoriously difficult LJ(38) system. However, while parallel tempering easily converges for LJ(31), we have not been able to get data of comparable accuracy with Wang-Landau multicanonical sampling.

Lessons from deregulation: Understanding electricity markets in South America

South America has been the most progressive region in the developing world in terms of deregulating the electricity industry. In this paper we compare the evolution of deregulation, from initiation to the current state, in four South American countries: Argentina, Brazil, Chile, and Colombia. These four countries are similar in many dimensions, such as culture, language and macro-economic development. They are also all depending, to a large extent, on hydro-generated electricity. All four countries have implemented different deregulated systems, allowing a unique possibility to compare the performance of different implementations of deregulation on one continent. We describe the course undertaken by these countries and the results attained so far, and also compare and contrast the development of the different electricity industries. Finally, we discuss what can be learned from these countries and what they can learn from each other.

Performance of query processing implementations in ranking-based text retrieval systems using inverted indices

Similarity calculations and document ranking form the computationally expensive parts of query processing in ranking-based text retrieval. In this work, for these calculations, 11 alternative implementation techniques are presented under four different categories, and their asymptotic time and space complexities are investigated. To our knowledge, six of these techniques are not discussed in any other publication before. Furthermore, analytical experiments are carried out on a 30 GB document collection to evaluate the practical performance of different implementations in terms of query processing time and space consumption. Advantages and disadvantages of each technique are illustrated under different querying scenarios, and several experiments that investigate the scalability of the implementations are presented.

Cluster communication protocols for parallel-programming systems

Clusters of workstations are a popular platform for high-performance computing. For many parallel applications, efficient use of a fast interconnection network is essential for good performance. Several modern System Area Networks include programmable network interfaces that can be tailored to perform protocol tasks that otherwise would need to be done by the host processors. Finding the right trade-off between protocol processing at the host and the network interface is difficult in general. In this work, we systematically evaluate the performance of different implementations of a single, user-level communication interface. The implementations make different architectural assumptions about the reliability of the network and the capabilities of the network interface. The implementations differ accordingly in their division of protocol tasks between host software, network-interface firmware, and network hardware. Also, we investigate the effects of alternative data-transfer methods and multicast implementations, and we evaluate the influence of packet size. Using microbenchmarks, parallel-programming systems, and parallel applications, we assess the performance of the different implementations at multiple levels. We use two hardware platforms with different performance characteristics to validate our conclusions. We show how moving protocol tasks to a relatively slow network interface can yield both performance advantages and disadvantages, depending on specific characteristics of the application and the underlying parallel-programming system.

VDBMS: A testbed facility for research in video database benchmarking

Real-world video-based applications require database technology that is capable of storing digital video in the form of video databases and providing content-based video search and retrieval. Methods for handling traditional data storage, query, search, retrieval, and presentation cannot be extended to provide this functionality. The VDBMS research initiative is motivated by the requirements of video-based applications to search and retrieve portions of video data based on content and by the need for testbed facilities to facilitate research in the area of video database management. In this paper we describe the VDBMS video database research platform, a system that supports comprehensive and efficient database management for digital video. Our fundamental concept is to provide a full range of functionality for video as a well-defined abstract database data type, with its own description, parameters, and applicable methods. Research problems that are addressed by VDBMS to support the handling of video data include MPEG7 standard multimedia content representation, algorithms for image-based shot detection, image processing techniques for extracting low-level visual features, a high-dimensional indexing technique to access the high-dimensional feature vectors extracted by image preprocessing, multimedia query processing and optimization, new query operators, real-time stream management, a search-based buffer management policy, and an access control model for selective, content-based access to streaming video. VDBMS also provides an environment for testing the correctness and scope of new video processing techniques, measuring the performance of algorithms in a standardized way, and comparing the performance of different implementations of an algorithm or component. We are currently developing video component wrappers with well-defined interfaces to facilitate the modification or replacement of video processing components. The ultimate goal of the VDBMS project is a flexible, extensible framework that can be used by the research community for developing, testing, and benchmarking video database technologies.

Design Alternatives for Virtual Interface Architecture and an Implementation on IBM Netfinity NT Cluster

The Virtual Interface Architecture (VIA) specification has been developed to standardize user-level network interfaces that provide low-latency, high-bandwidth communications. Few hardware and software implementations of VIA exist. Since the VIA specification is flexible, different choices exist for implementing various components of VIA such as doorbells, address translation methods, and completion queues. Although previous studies have evaluated the overall performance of different VIA implementations, there has not been a comparative study on the performance of VIA components. In this paper, we evaluate and compare the performance of different implementations of essential VIA components. We discuss the pros and cons of each design approach and describe the required support for implementing each of them. Then, we discuss an experimental implementation of the Virtual Interface Architecture for the IBM SP Switch-Connected NT cluster, one of the newest clustering platforms available. We discuss different design issues involved in this implementation. In particular, we explain how the virtual-to-physical address translation is implemented efficiently with a minimum Network Interface Card (NIC) memory requirement. We show how caching the VIA descriptors on the NIC can reduce the communication latency. We also present an efficient scheme for implementing the VIA doorbells without any hardware support. We provide a comprehensive performance evaluation study and discuss the impact of several hardware improvements on the performance of our implementation. The performance of the implemented VIA surpasses that of other existing software implementations of the VIA and is comparable to that of a hardware VIA implementation. The peak measured bandwidth for our system is 101.4MBytes/s and the one-way latency for short messages is 18.2μs.

A performance study of the ISO transport protocol

The performance of different implementations of the ISO transport protocol class 4 on top of a connectionless link-layer protocol in the presence of transmission errors is studied by means of simulation. A main goal of the study is to find robust protocol versions yielding good performance for all possible combinations of implementations. The performance measure investigated is the throughput that can be achieved in transferring files between two stations over a local area or long-distance network. The results are compared to those obtained for the ISO transport protocol class 2 on top of a connection-oriented link-layer protocol. It is assumed that data and acknowledgement frames could be lost or corrupted by transmission errors. The results show that, at the sender side, retransmit all always yields higher performance than retransmit first, and, at the receiver side, store results in higher performance than discard.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>