Development Of High-performance Software Research Articles

Brain-computer interaction neurointerface based on artificial intelligence and its parallel programming using high-performance calculation on cluster mobile devices

The paper deals with hardware and software support for the interaction of human brain activity with the dynamic movement of the part of its upper limb based on artificial intelligence and its parallel programming using high-performance computer calculation on cluster mobile devices. The obtained results can be used as a basis for the development of high-performance software and hardware for the effective operation of brain-computer interaction neuro interfaces.

Integrating parallelism and asynchrony for high-performance software development

This article delves into the crucial roles of parallelism and asynchrony in the development of high-performance software programs. It provides an insightful exploration into how these methodologies enhance computing systems' efficiency and performance. The discussion begins with an overview of high-performance programs and their importance in modern computing, followed by a detailed analysis of parallelism, including its hardware and software aspects, various programming models, and diverse applications in fields like computational tasks, data processing, and machine learning. The article then shifts focus to asynchrony, elaborating on its implementation through callback functions, promises, and the async/await syntax. It highlights the significant benefits of asynchrony in improving program responsiveness and efficiency, especially in I/O-bound and network-intensive operations. A critical section of the article examines the combined application of parallelism and asynchrony in different domains, notably in Graphics Processing Unit (GPU) computations, distributed systems, and web development. This combination is shown to be particularly effective in handling Big Data, where rapid and efficient data processing is essential. The article concludes by emphasizing the indispensable nature of these approaches in modern software development. Parallelism and asynchrony are not merely performance enhancement tools but are fundamental in building innovative, resilient, and scalable software solutions. This comprehensive exploration underscores the ongoing relevance of these methodologies and their potential to drive further advancements in the field of high-performance computing.

Tensor Computations: Applications and Optimization (Dagstuhl Seminar 20111)

Tensors are higher-dimensional analogs of matrices, and represent a key data abstraction for many applications in computational science and data science. In contrast to the wide availability on diverse hardware platforms of high-performance numerical libraries for matrix computations, only limited software infrastructure exists today for high-performance tensor computations. Recent research developments have resulted in the formulation of many machine learning algorithms in terms of tensor computations. Tensor computations have also emerged as fundamental building blocks for many algorithms in data science and computational science. Therefore, several concurrent efforts have targeted the development of libraries, frameworks, and domain-specific compilers to support the rising demand for high-performance tensor computations. However, there is currently very little coordination among the various groups of developers. Further, the groups developing high-performance libraries/frameworks for tensor computations are still rather disconnected from the research community that develops applications using tensors as a key data abstraction. The main goal of this Dagstuhl Seminar has been to bring together the following two communities: first researchers from disciplines developing applications centered around tensor computations, and second researchers developing software infrastructure for efficient tensor computation primitives. Invitees from the former group included experts in machine learning and data analytics, and computational scientists developing tensor-based applications. Invitees from the latter group spanned experts in compiler optimization and experts in numerical methods. A very fruitful exchange of ideas across these four research communities took place, with discussions on the variety of needs and use-cases for tensor computations and the challenges/opportunities in the development of high-performance software to satisfy those needs.

Software analizador de sistemas mecánicos desarrollado en la Universidad Tecnológica de Nayarit

This research, has as its main purpose to have developed a tool of free use available to students, educators and professionals through a software that facilitates the teaching and learning process. This one was programmed with the Visual Basic language (VB), being a tool of effective and high-performance software development technologies from Microsoft. It will be able to perform various analyses of mechanical systems in transmissions, and its purpose allows the user to calculate, understand and compare the analyzes in an effective and orderly way to implement them at convenience. The contributions of the project can be granted mostly to the educational and work environment, being destined to apply engineering in pedagogical and labor sectors. The project is oriented to the needs of knowing characteristics of a mechanical system to implement its optimal functioning through this software. All this is justified from the obtaining of knowledge in the academic trainingand a rigorous investigation of mechanical systems, programming and design, the research considers information coming from professors of the university, web forums and magazines.

Getting the Right Answers for the Right Reasons: Toward Predictive Molecular Simulations of Water with Many-Body Potential Energy Functions.

The central role played by water in fundamental processes relevant to different disciplines, including chemistry, physics, biology, materials science, geology, and climate research, cannot be overemphasized. It is thus not surprising that, since the pioneering work by Stillinger and Rahman, many theoretical and computational studies have attempted to develop a microscopic description of the unique properties of water under different thermodynamic conditions. Consequently, numerous molecular models based on either molecular mechanics or ab initio approaches have been proposed over the years. However, despite continued progress, the correct prediction of the properties of water from small gas-phase clusters to the liquid phase and ice through a single molecular model remains challenging. To large extent, this is due to the difficulties encountered in the accurate modeling of the underlying hydrogen-bond network in which both number and strength of the hydrogen bonds vary continuously as a result of a subtle interplay between energetic, entropic, and nuclear quantum effects. In the past decade, the development of efficient algorithms for correlated electronic structure calculations of small molecular complexes, accompanied by tremendous progress in the analytical representation of multidimensional potential energy surfaces, opened the doors to the design of highly accurate potential energy functions built upon rigorous representations of the many-body expansion (MBE) of the interaction energies. This Account provides a critical overview of the performance of the MB-pol many-body potential energy function through a systematic analysis of energetic, structural, thermodynamic, and dynamical properties as well as of vibrational spectra of water from the gas to the condensed phase. It is shown that MB-pol achieves unprecedented accuracy across all phases of water through a quantitative description of each individual term of the MBE, with a physically correct representation of both short- and long-range many-body contributions. Comparisons with experimental data probing different regions of the water potential energy surface from clusters to bulk demonstrate that MB-pol represents a major step toward the long-sought-after "universal model" capable of accurately describing the molecular properties of water under different conditions and in different environments. Along this path, future challenges include the extension of the many-body scheme adopted by MB-pol to the description of generic solutes as well as the integration of MB-pol in an efficient theoretical and computational framework to model acid-base reactions in aqueous environments. In this context, given the nontraditional form of the MB-pol energy and force expressions, synergistic efforts by theoretical/computational chemists/physicists and computer scientists will be critical for the development of high-performance software for many-body molecular dynamics simulations.

Mental imagery and software visualization in high-performance software development teams

This paper considers the relationship between mental imagery and software visualization in professional, high-performance software development. It presents overviews of four empirical studies of professional software developers in high-performing teams: (1) expert programmers’ mental imagery, (2) how experts externalize their mental imagery as part of teamwork, (3) experts’ use of commercially available visualization software, and (4) what tools experts build themselves, how they use the tools they build for themselves, and why they build tools for themselves. Through this series of studies, the paper provides insight into a relationship between how experts reason about and imagine solutions, and their use of and requirements for external representations and software visualization. In particular, it provides insight into how experts use visualization in reasoning about software design, and how their requirements for the support of design tasks differ from those for the support of other software development tasks. The paper draws on theory from other disciplines to explicate issues in this area, and it discusses implications for future work in this field.

Native data representation: an efficient wire format for high-performance distributed computing

New trends in high-performance software development such as tool- and component-based approaches have increased the need for flexible and high-performance communication systems. When trying to reap the well-known benefits of these approaches, the question of what communication infrastructure should be used to link the various components arises. In this context, flexibility and high-performance seem to be incompatible goals. Traditional HPC-style communication libraries, such as MPI, offer good performance, but are not intended for loosely-coupled systems. Object- and metadata-based approaches like XML offer the needed plug-and-play flexibility, but with significantly lower performance. We observe that the flexibility and baseline performance of data exchange systems are strongly determined by their wire formats, or by how they represent data for transmission in heterogeneous environments. After examining the performance implications of using a number of different wire formats, we propose an alternative approach for flexible high-performance data exchange, Native Data Representation, and evaluate its current implementation in the portable binary I/O library.

Creating high performance software development teams

No abstract available.

High performance computing algorithms for land cover dynamics using remote sensing data

Global and regional land cover studies need to apply complex models on selected subsets of large volumes of multi-sensor and multi-temporal data sets that have been derived from raw instrument measurements using widely accepted pre-processing algorithms. The computational and storage requirements of most of these studies far exceed what is possible on a single workstation environment. We have been pursuing a new approach that couples scalable and open distributed heterogeneous hardware with the development of high performance software for processing, indexing and organizing remotely sensed data. Hierarchical data management tools are used to ingest raw data, create metadata and organize the archived data so as to automatically achieve computational load balancing among the available nodes and minimize input/output overheads. We illustrate our approach with four specific examples. The first is the development of the first fast operational scheme for the atmospheric correction of Landsat Thematic Mapper scenes, while the second example focuses on image segmentation using a novel hierarchical connected components algorithm. Retrieval of the global Bidirectional Reflectance Distribution Function in the red and near-infrared wavelengths using four years (1983 to 1986) of Pathfinder Advanced Very High Resolution Radiometer (AVHRR) Land data is the focus of our third example. The fourth example is the development of a hierarchical data organization scheme that allows on-demand processing and retrieval of regional and global AVHRR data sets. Our results show that substantial reductions in computational times can be achieved by the high performance computing technology.