On the Computational Power of Particle Methods

Classes of machines using very limited amounts of nondeterminism are studied. The P=? NP question is related to questions about classes lying within P. Complete sets for these classes are given.

This chapter describes four interdisciplinary fields originated and defined by Ashu M. G. Solo in 2011 called political engineering, public policy engineering, computational politics, and computational public policy. Political engineering is the application of engineering, computer science, mathematics, or natural science to solving problems in politics. Computational politics is the application of computer science or mathematics to solving problems in politics. Political engineering and computational politics include, but are not limited to, principles and methods for political decision-making, analysis, modeling, optimization, forecasting, simulation, and expression. Public policy engineering is the application of engineering, computer science, mathematics, or natural science to solving problems in public policy. Computational public policy is the application of computer science or mathematics to solving problems in public policy. Public policy engineering and computational public policy include, but are not limited to, principles and methods for public policy formulation, decision-making, analysis, modeling, optimization, forecasting, and simulation. The chapter describes the scope of research and development in these fields, provides examples of research and development in these fields, and provides possible university curricula for academic programs in these fields.

It is important for colleges to have a diverse applicant pool as part of their diversity and inclusion practices. This paper discusses the recent efforts of faculty and staff at Wentworth Institute of Technology’s School of Computing and Data Science (SCDS), to increase the population of international students from Africa as part of the diversity and inclusion strategies of the University. This resulted in a 2-day event hosted by SCDS, to create awareness about the school’s diversity plans. The event tagged “Virtual Open House for Nigeria” was an inaugural open house event for prospective international students, their families, and sponsors to meet the Wentworth SCDS faculty and learn about our specialties in Computer Science, Computer Networking, Cybersecurity, Applied Mathematics, Applied Computer Science, and Data Science / Business Analytics, and was hosted virtually on October 8-9 2021. Day 1 of the event featured an opportunity for prospective international students from Nigeria, as well as their parents, sponsors, or teachers, to meet the Wentworth Dean and faculty and learn about our specialties in Computer Science, Computer Networking, Cybersecurity, Applied Mathematics, Applied Computer Science, Data Science/Business Analytics, while day 2 featured Data Science and Machine Learning Workshop, as well as a session on strong application and funding tips for prospective students. This paper summarizes some of the activities by the School of Computing and Data Science at Wentworth Institute of Technology, to demonstrate its commitment to inclusiveness through recruitment agenda for international students. Thus, we discuss the day one activities, where the potential students, parents and mentors had the opportunity of interacting with Wentworth faculty and staff in any of three two-hour sessions.

Previous article Next article Bounds on Multiprocessing Timing AnomaliesR. L. GrahamR. L. Grahamhttps://doi.org/10.1137/0117039PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAbout[1] E. F. Codd, Multiprogram scheduling. I, II. Introduction and theory, Comm. ACM, 3 (1960), 347–350 10.1145/367297.367317 MR0130079 0102.34202 CrossrefISIGoogle Scholar[2] R. L. Graham, Bounds for certain multiprocessing anomalies, Bell System Tech. J., 45 (1966), 1563–1581 0168.40703 CrossrefISIGoogle Scholar[3] J. Heller, Sequencing aspects of multiprogramming, J. Assoc. Comput. Mach., 8 (1961), 426–439 MR0159443 CrossrefGoogle Scholar[4] John L. Kelley, General topology, D. Van Nostrand Company, Inc., Toronto-New York-London, 1955xiv+298 MR0070144 0066.16604 Google Scholar[5] B. Liebesman, The use of a special algebra in schedule analysis, to appear Google Scholar[6] G. K. Manacher, Production and stabilization of real-time task schedules, J. Assoc. Comput. 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Rep., 2, Operations Research Center, M.I.T., Cambridge, 1964 Google Scholar Previous article Next article FiguresRelatedReferencesCited ByDetails DAG Scheduling and Analysis on Multi-Core Systems by Modelling Parallelism and DependencyIEEE Transactions on Parallel and Distributed Systems, Vol. 33, No. 12 | 1 Dec 2022 Cross Ref The BH-mixed scheduling algorithm for DAG tasks with constrained deadlinesJournal of Systems Architecture, Vol. 131 | 1 Oct 2022 Cross Ref Streaming algorithms for multitasking scheduling with shared processingDiscrete Applied Mathematics, Vol. 320 | 1 Oct 2022 Cross Ref Checkpointing Workflows à la Young/Daly Is Not Good EnoughACM Transactions on Parallel Computing, Vol. 25 | 2 September 2022 Cross Ref Parallel Machine Scheduling Under Uncertainty: Models and Exact AlgorithmsINFORMS Journal on Computing, Vol. 68 | 17 August 2022 Cross Ref EasyFL: A Low-Code Federated Learning Platform for DummiesIEEE Internet of Things Journal, Vol. 9, No. 15 | 1 Aug 2022 Cross 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Polynomial pseudo-random number generator via cyclic phase

Pseudo random number generator based on quantum chaotic map

The purpose of the study is to assess the application of Computer science in the fractional distillation of petroleum. The study sought to: Determine the merit of using Computer science in fractional distillation of petroleum. Evaluate the cost effectiveness to the application of Computer science in fractional distillation of petroleum to the welfare of citizens. Determine if Computer science can help in controlling the natural effects of fractional distillation of petroleum on the environment. Computer science has gained wider application in so many areas of human endeavor ranging from the homes to more scientific and industrial applications, hence its application of Computer science in fractional distillation of petroleum cannot be overemphasized. Irrespective of the benefits of the application of Computer science in fractional distillation of petroleum as a whole, it has become pertinent to ask how effective and efficient its application of Computer science in fractional distillation of petroleum has been. This research work tries to investigate how effective the application of Computer science in fractional distillation of petroleum. The project exertion covered statement of the problem, purpose of the study, research questions/hypotheses were formulated to enable the researcher find out facts about the study, highlighted in division one. Subdivision two was based on the literature review of this study. The study covers the research methodology which guided the study, the next stage was based on the presentation of data and its’ analysis as well as the discussion of findings. The final stage of the research was concerned with the conclusion as well as recommendations and suggestions for further studies

Geometric Algebra (GA) has proven to be an advanced language for mathematics, physics, computer science, and engineering. This review presents a comprehensive study of works on Quaternion Algebra and GA applications in computer science and engineering from 1995 to 2020. After a brief introduction of GA, the applications of GA are reviewed across many fields. We discuss the characteristics of the applications of GA to various problems of computer science and engineering. In addition, the challenges and prospects of various applications proposed by many researchers are analyzed. We analyze the developments using GA in image processing, computer vision, neurocomputing, quantum computing, robot modeling, control, and tracking, as well as improvement of computer hardware performance. We believe that up to now GA has proven to be a powerful geometric language for a variety of applications. Furthermore, there is evidence that this is the appropriate geometric language to tackle a variety of existing problems and that consequently, step-by-step GA-based algorithms should continue to be further developed. We also believe that this extensive review will guide and encourage researchers to continue the advancement of geometric computing for intelligent machines.

As our economy and society continue to evolve, computer technology is also evolving and innovating. The emergence of computer technology has greatly facilitated human work and learning, and has brought great influence to all walks of life. For a long time, computer technology has deeply penetrated into people's production and life, and become an indispensable and important part. To a certain extent, computers have contributed to the development of the national economy, and at the same time, it has also brought a lot of convenience to the people. This initiative not only significantly improves the quality of life and productivity of the general public, but also an important indicator of the overall quality of a country's population. Through the study, it is found that with the continuous development of science and technology, the trend of combining computer technology and communication technology is becoming more and more obvious and has made certain achievements. Although the development of computer science and technology is very short, but the scope of its application for people's lives and the reform and development of related work is unparalleled by any other technology. The application of computer science and technology basically involves all aspects of domestic life, from the most basic food, clothing, housing and transportation to human communication and all kinds of production work, at the same time, computer science and technology is also the core of other technological reforms and innovations, and other technological advances relying on computer science and technology, cloud computing technology, cloud storage and its intelligent regulation and control of the new technology have achieved a certain degree of fundamental independent innovation. This research will focus on the computer science and technology, which is the core of other technological reforms and innovations. This study will systematically analyze the practical application and development of computer science and technology, and carefully sort out the main reasons for the development of computer science and technology and the future development of the market outlook.

Large-scale scientific computation and all of the disciplines that support and help validate it have been placed at the focus of Lawrence Livermore National Laboratory (LLNL) by the Advanced Simulation and Computing (ASC) program of the National Nuclear Security Administration (NNSA) and the Scientific Discovery through Advanced Computing (SciDAC) initiative of the Office of Science of the Department of Energy (DOE). The maturation of simulation as a fundamental tool of scientific and engineering research is underscored in the President's Information Technology Advisory Committee (PITAC) June 2005 finding that ''computational science has become critical to scientific leadership, economic competitiveness, and national security''. LLNL operates several of the world's most powerful computers--including today's single most powerful--and has undertaken some of the largest and most compute-intensive simulations ever performed, most notably the molecular dynamics simulation that sustained more than 100 Teraflop/s and won the 2005 Gordon Bell Prize. Ultrascale simulation has been identified as one of the highest priorities in DOE's facilities planning for the next two decades. However, computers at architectural extremes are notoriously difficult to use in an efficient manner. Furthermore, each successful terascale simulation only points out the need for much better ways of interacting with the resulting avalanche ofmore » data. Advances in scientific computing research have, therefore, never been more vital to the core missions of LLNL than at present. Computational science is evolving so rapidly along every one of its research fronts that to remain on the leading edge, LLNL must engage researchers at many academic centers of excellence. In FY 2005, the Institute for Scientific Computing Research (ISCR) served as one of LLNL's main bridges to the academic community with a program of collaborative subcontracts, visiting faculty, student internships, workshops, and an active seminar series. The ISCR identifies researchers from the academic community for computer science and computational science collaborations with LLNL and hosts them for both brief and extended visits with the aim of encouraging long-term academic research agendas that address LLNL research priorities. Through these collaborations, ideas and software flow in both directions, and LLNL cultivates its future workforce. The Institute strives to be LLNL's ''eyes and ears'' in the computer and information sciences, keeping the Laboratory aware of and connected to important external advances. It also attempts to be the ''hands and feet'' that carry those advances into the Laboratory and incorporate them into practice. ISCR research participants are integrated into LLNL's Computing Applications and Research (CAR) Department, especially into its Center for Applied Scientific Computing (CASC). In turn, these organizations address computational challenges arising throughout the rest of the Laboratory. Administratively, the ISCR flourishes under LLNL's University Relations Program (URP). Together with the other four institutes of the URP, the ISCR navigates a course that allows LLNL to benefit from academic exchanges while preserving national security. While it is difficult to operate an academic-like research enterprise within the context of a national security laboratory, the results declare the challenges well met and worth the continued effort. The pages of this annual report summarize the activities of the faculty members, postdoctoral researchers, students, and guests from industry and other laboratories who participated in LLNL's computational mission under the auspices of the ISCR during FY 2005.« less

The problem of finding a total ordering of a finite set satisfying a given set of in-between restrictions is considered. It is shown that the problem is $NP$-complete.

Background Information Systems analysis and design is a course that focuses on the development and maintenance of new and existing systems in an enterprise (Misic & Russo, 1999). This course is usually taught in an MIS program in a business school or in a computer science program in the liberal arts or engineering school. The MIS curriculum includes a course in Systems Analysis and Design (SAD Gorgone, et al., 2003). The SA&D course focuses on the earlier phases of the System Development Life Cycle (SDLC), and the course is typically delivered using either or both the procedure-centric and object-oriented paradigms. In the Applied Computer Science (ACS) Curriculum, a two-part Software Engineering (SE) course is usually offered, which consists of analysis and design in the first semester and a system development project (a capstone course) in the second semester. The College of Business established the MIS program that is discussed in this study in 1999 following an extensive review by both the faculty and IS practitioners. As part of the development of the MIS program, a focus group comprising of MIS faculty and IS practitioners was conducted to review a proposed curriculum for MIS. The idea to leverage the expertise of the well established computer science program to support the newly developed MIS program was echoed by the IS practitioners during the focused group discussion (Ehie, 2002). This viewpoint was made known to the provost of the institution by a consultant hired to review the new MIS curriculum. Based on the review, a new joint faculty position was approved for the MIS and the Computer Science departments. One-quarter of the new position was devoted to the MIS program and the new faculty member would be resident in the computer science department. The joint appointment will allow two programming courses to be taught by the ACS faculty for the MIS program. The department heads from the ACS and MIS programs, upon consultation with their respective faculty members and students, decided to offer a cross-listed course in SA&D in which both MIS and ACS students will be combined in one class. Such an unusual collaboration between two competing departments offers both challenges and opportunities. The main challenges were to ensure that the course design, bearing in mind the respective prerequisites, meets the curricula requirements to prepare both majors adequately for their subsequent system development and implementation courses and to diffuse the possible cultural tension between the two differently focused majors (Business and IS) during the class sessions. The main opportunity lies in constructively using the diversity to simulate the real-world situation, where students with different academic background work together to achieve the common course objectives. The SA&D course under the MIS program is followed by a capstone project course called Systems Implementation and Practice, which essentially caters to the curriculum requirements specified for implementing databases and distributed applications. The Applied Computer Science majors specializing in information systems in the University have a core course titled Information Systems Analysis and Design (ISA&D) in addition to Software Engineering, a project-based capstone course required by all ACS majors. Just as in SA&D, primary workflows in software development form the core of ISA&D. A second-level Information System course emphasizing the use of databases serves as the prerequisite for the ISA&D course, along with an in-depth four-semester programming knowledge. The ACS department, with input from the MIS department, hired a new faculty member that had an extensive industry experience. …

Most important computational problems nowadays are those related to processing of the large data sets and to numerical solution of the high-dimensional integral-differential equations. These problems arise in numerical modeling in quantum chemistry, material science, and multiparticle dynamics, as well as in machine learning, computer simulation of stochastic processes and many other applications related to big data analysis. Modern tensor numerical methods enable solution of the multidimensional partial differential equations (PDE) in ℝ d {\mathbb{R}^{d}} by reducing them to one-dimensional calculations. Thus, they allow to avoid the so-called “curse of dimensionality”, i.e. exponential growth of the computational complexity in the dimension size d, in the course of numerical solution of high-dimensional problems. At present, both tensor numerical methods and multilinear algebra of big data continue to expand actively to further theoretical and applied research topics. This issue of CMAM is devoted to the recent developments in the theory of tensor numerical methods and their applications in scientific computing and data analysis. Current activities in this emerging field on the effective numerical modeling of temporal and stationary multidimensional PDEs and beyond are presented in the following ten articles, and some future trends are highlighted therein.

Computer models and automata theory in biology and medicine

An interesting class of irregular algorithms is tree traversal algorithms, which repeatedly traverse various trees to perform efficient computations. Tree traversal algorithms form the algorithmic kernels in an important set of applications in scientific computing, computer graphics, bioinformatics, and data mining, etc. There has been increasing interest in understanding tree traversal algorithms, optimizing them, and applying them in a wide variety of settings. Crucially, while there are many possible optimizations for tree traversal algorithms, which optimizations apply to which algorithms is dependent on algorithmic characteristics. In this work, we present a suite of tree traversal kernels, drawn from diverse domains, called Treelogy, to explore the connection between tree traversal algorithms and state-of-the-art optimizations. We characterize these algorithms by developing an ontology based on their structural properties. The attributes extracted through our ontology, for a given traversal kernel, can aid in quick analysis of the suitability of platform- and application-specific as well as independent optimizations. We provide reference implementations of these kernels for three platforms: shared memory multicores, distributed memory systems, and GPUs, and evaluate their scalability.