Modern Hardware Research Articles

Determination of the Probability of Failure of a RAID-Type Optical Disks Array over Several Years of Storage

The problem of determining the probability of information loss on a RAID array of optical disks (the probability of loss of readability of a RAID array) during long-term storage in an electronic archive is considered. Knowledge of this value is necessary to determine a number of parameters (in particular, the number of spare copies of information) when designing electronic information archives built on modern hardware and software solutions such as robotic optical disk libraries, in which the physical unit of information storage is a cartridge (a block of several optical disks), on which a RAID array can be created. It is usually impossible to replace single disks in a cartridge. A model for calculating the probability of failure of an array of RAID optical disks over a long storage time is constructed. An example of calculating this probability for real source data is shown. Recommendations are given on the interpretation of the results obtained in relation to the design of future archives.

Assessing the robustness and scalability of the accelerated pseudo-transient method

Abstract. The development of highly efficient, robust and scalable numerical algorithms lags behind the rapid increase in massive parallelism of modern hardware. We address this challenge with the accelerated pseudo-transient (PT) iterative method and present a physically motivated derivation. We analytically determine optimal iteration parameters for a variety of basic physical processes and confirm the validity of theoretical predictions with numerical experiments. We provide an efficient numerical implementation of PT solvers on graphical processing units (GPUs) using the Julia language. We achieve a parallel efficiency of more than 96 % on 2197 GPUs in distributed-memory parallelisation weak-scaling benchmarks. The 2197 GPUs allow for unprecedented tera-scale solutions of 3D variable viscosity Stokes flow on 49953 grid cells involving over 1.2 trillion degrees of freedom (DoFs). We verify the robustness of the method by handling contrasts up to 9 orders of magnitude in material parameters such as viscosity and arbitrary distribution of viscous inclusions for different flow configurations. Moreover, we show that this method is well suited to tackle strongly nonlinear problems such as shear-banding in a visco-elasto-plastic medium. A GPU-based implementation can outperform direct-iterative solvers based on central processing units (CPUs) in terms of wall time, even at relatively low spatial resolution. We additionally motivate the accessibility of the method by its conciseness, flexibility, physically motivated derivation and ease of implementation. This solution strategy thus has a great potential for future high-performance computing (HPC) applications, and for paving the road to exascale in the geosciences and beyond.

ВИКОРИСТАННЯ ВЕБ-ОРІЄНТОВАНИХ СЕРЕДОВИЩ ПІД ЧАС ВИВЧЕННЯ КОМП’ЮТЕРНОГО ДИЗАЙНУ УЧНЯМИ СТАРШОЇ ШКОЛИ ІНФОРМАТИЧНОГО ПРОФІЛЮ

With the development of modern technologies, computer hardware and various software, there are rapid and high-quality changes in data processing technologies. Web-oriented technologies, which are the advanced technologies of the information society, play the role of a leading tool for informatization of education. The development of software used in the study of computer design. The article substantiates the need to use web-based learning environments in the process of studying computer design by high school students of informative high school. During the study of computer science at school, it is planned to perform educational tasks both in lessons at school and at home. Providing all students with access to unified software is problematic because everyone has different computers, including different operating systems. Starting from March 12, 2020, student learning has been taking place remotely for a long time. Most computer science teachers have faced the problem of how to unify software for mastering educational material in computer science lessons. One way to solve this problem is to use web-based environments. Types of computer design are considered and in accordance with the age characteristics of students and learning objectives selected web-based software which greatly simplifies the organization and implementation of the educational process. When using web-based environments, you do not need additional knowledge to configure them, because the use of such environments is independent of the technical characteristics of the computer, and only requires an Internet connection. Keywords: computerization of education, computer design, computer graphics, web-based environment, information and communication technologies.

Modern Methods, Software and Hardware to Authenticate the Users of Computer Systems and Networks

The aim of the work is to review and analyze the existing methods, software and hardware for identifying and authenticating the users of computer systems and networks, and to define their promising development lines. The authentication methods and means used to control both local and remote access of users to computer resources are considered. Special attention is paid to multi-factor authentication in controlling remote access. The advantages and disadvantages of the considered methods and means in terms of ensuring reliable user authentication are noted. Despite the continuing widespread use of password authentication, its insufficient protection against password guessing attacks and password interceptions when the passwords are transmitted over the network urgently calls for a need of shifting to more reliable authentication methods. A version of local authentication is proposed that uses a handshake model based on a function specified in tabular form for calculating the response to a random request, which does not require the use of additional devices. Two methods for multi-factor authentication of users performing remote access are proposed: based on the knowledge of their interests and habits when working in the Internet and on the basis of a person whose image is transmitted to the authentication server in a one-time encrypted form (the encryption key is generated based on the user's private key and random admixture). These two solutions can be implemented using open source software and without involvement of third-party paid services. As a result of the performed analysis, the most effective methods and means for identification and authentication of users of various information systems have been defined. The obtained results can be used to enhance the security of computer systems and networks against unauthorized access to their resources. Ensuring the security of information and software systems is a must in improving the quality of such systems.

Algorithms for Windowed Aggregations and Joins on Distributed Stream Processing Systems

Window aggregations and windowed joins are central operators of modern real-time analytic workloads and significantly impact the performance of stream processing systems.This paper gives an overview of state-of-the-art research in this area conducted by the Berlin Institute for the Foundations of Learning and Data (BIFOLD) and the Technische Universität Berlin. To this end, we present different algorithms for efficiently processing windowed operators and discuss techniques for distributed stream processing. Recently, several approaches have leveraged modern hardware for windowed stream processing, which we will also include in this overview. Additionally, we describe the integration of windowed operators into various stream processing systems and diverse applications that use specialized window operations.

Aggressive phenotype editing by modulated immune cells

IntroductionIn human society increased aggressiveness is one of the main social and health problems. Immune cells have a regulatory effect on the central nervous system functions, including regulation of behavior.Objectives The aim of the study was to investigate the effect of in vitro neuroleptic-modulated immune cells transplantation on behavioral phenotype and brain cytokines in aggressive syngeneic recipients.Methods (CBAxC57Bl/6) F1 aggressive male mice, developed in conditions of social confrontation, were undergoing the transplantation of syngeneic immune cells with in vitro chlorpromazine-modulated functional activity. Recipient’s behavioral phenotyping was performed using modern hardware and software complex EthoVision XT. The brain cytokines content was assessed by ELISA.ResultsIt was found that repeated experience of aggression, accompanied by victories, leads to a change in male mice behavior, which manifests itself by increased motor activity, irritability, severe anxiety, and the appearance of stereotypies. Transplantation of chlorpromazine-modulated splenocytes in aggressive recipient was accompanied by decreased motor activity in the Open Field, increased open arm activity in Plus Maze, reflects anti-anxiety behavior; decreased time spent close to the partition and the total duration of attacks after removal of the partitionin in resident-intruder test, reflects decreased aggressive motivation. Behavioral changes in recipients were accompanied with cytokines brain changes: decreased IL-1β, IL-2, IL-6, INFγ in the hippocampus; increased IL-4 and decreased INFγ in the hypothalamus; decreased IL-1β in the frontal cortex.Conclusions Chlorpromazine - modulated immune cells have a positive aggressive behavior editing effect being involved in the central mechanisms underlying the development of aggressive reactions.DisclosureNo significant relationships.

Hercules against data series similarity search

We propose Hercules, a parallel tree-based technique for exact similarity search on massive disk-based data series collections. We present novel index construction and query answering algorithms that leverage different summarization techniques, carefully schedule costly operations, optimize memory and disk accesses, and exploit the multi-threading and SIMD capabilities of modern hardware to perform CPU-intensive calculations. We demonstrate the superiority and robustness of Hercules with an extensive experimental evaluation against state-of-the-art techniques, using many synthetic and real datasets, and query workloads of varying difficulty. The results show that Hercules performs up to one order of magnitude faster than the best competitor (which is not always the same). Moreover, Hercules is the only index that outperforms the optimized scan on all scenarios, including the hard query workloads on disk-based datasets.

HarrisZ+: Harris corner selection for next-gen image matching pipelines

Due to its role in many computer vision tasks, image matching has been subjected to an active investigation by researchers, which has lead to better and more discriminant feature descriptors and to more robust matching strategies, also thanks to the advent of the deep learning and the increased computational power of the modern hardware. Despite of these achievements, the keypoint extraction process at the base of the image matching pipeline has not seen equivalent progresses. This paper presents HarrisZ$^+$, an upgrade to the HarrisZ corner detector, optimized to synergically take advance of the recent improvements of the other steps of the image matching pipeline. HarrisZ$^+$ does not only consists of a tuning of the setup parameters, but introduces further refinements to the selection criteria delineated by HarrisZ, so providing more, yet discriminative, keypoints, which are better distributed on the image and with higher localization accuracy. The image matching pipeline including HarrisZ$^+$, together with the other modern components, obtained in different recent matching benchmarks state-of-the-art results among the classic image matching pipelines. These results are quite close to those obtained by the more recent fully deep end-to-end trainable approaches and show that there is still a proper margin of improvement that can be granted by the research in classic image matching methods.

A Framework for Calculating WCET Based on Execution Decision Diagrams

Due to the dynamic behaviour of acceleration mechanisms such as caches and branch predictors, static Worst-case Execution Time (WCET) analysis methods tend to scale poorly to modern hardware architectures. As a result, a trade-off must be found between the duration and the precision of the analysis, leading to an overestimation of the WCET bounds. In turn, this reduces the schedulability and resource usage of the system. In this article, we present a new data structure to speed up the analysis: the eXecution Decision Diagram (XDD), which is an ad hoc extension of Binary Decision Diagrams tailored for WCET analysis problems. We show how XDDs can be used to represent efficiently execution states in a modern hardware platform. Moreover, we propose a new process to build the Integer Linear Programming system of the Implicit Path Enumeration Technique using XDD. We use benchmark applications to demonstrate how the use of an XDD substantially increases the scalability of WCET analysis and the precision of the obtained WCET.

PECULIARITIES OF MASTERING TECHNOLOGIES OF WORKING WITH MULTIMEDIA IN LESSONS OF INFORMATICS IN PRIMARY SCHOOL

The article is devoted to the problem of mastering the technologies of working with multimedia tools in computer science lessons by junior schoolchildren. The author emphasizes that today information and communication technologies have become an integral part of our lives. Its open up a huge range of opportunities to enrich the educational process in a modern school. One of such information technology tools is multimedia and mastering the technology of working with multimedia tools in computer science lessons (and in primary school in particular) is becoming increasingly important. Multimedia provides a system of integrated interaction of visual and audio effects under the control of interactive software using modern hardware and software in a single digital reproduction. A special place among them is occupied by a multimedia presentation, which has significant advantages in the educational process: it allows you to organize and store information, simplifies work during the demonstration of visual material, allows it to detail, vary, increase interest in learning and more. With the help of a multimedia presentation, it is possible to ensure the successful perception and assimilation of information by students by combining the message of educational material with its presentation. Mastering the technology of working with a multimedia presentation should begin at an early school age. This is evidenced by the relevant educational state documents (State Standard of Primary Education, Standard programs of primary school). The teacher has to solve several tasks: to give younger students some theoretical foundations on the essence of a multimedia presentation, to acquaint them with the program of creating and editing presentations, to teach them to create and demonstrate slide presentations. Mastering a multimedia presentation in computer science lessons in primary school makes it easier for primary school students to learn the laws, develops the ability to operate with images – to summarize, compare, transform and transform them.

HISOBLASH VA INFOKOMMUNIKATSIYA QURILMALARI ENERGIYA TA'MINOTI MONITORINGINING APPARAT-DASTURIY VOSITALARI

The paper reviews the use of multidimensional measuring and control variables and their modern hardware and software in conversion of power sources to secondary signals in the power supply processes of computing and infocommunication devices, the principles of monitoring them, receiving signals to ensure smooth and quality operation of devices. It also elucidates the principle of construction, model and software of working and transmitting media on an appropriate basis. The developed power supply control device is based on the ongoing processes and functional modules selected when the device was assembled. According to the main objective of the study, a monitoring algorithm and software package were developed based on the built-in system architecture. The implemented model was used to describe integration processes taking place between the hardware and software for monitoring, in detail. The research enabled developing and introducing models of IDEF database destined for collection and processing of statistical data in monitoring processes of a software package. Practical results from generation of sources of electricity and its use in enterprises by month, year and day, are presented in the form of graphs and tables.

A Novel Optimized Travel Planner

In 1959, Dijkstra announced a method for determining the shortest path between two nodes in a network. This algorithm has received much attention because it can deal with various real-life problems. The algorithm is a greedy type. Other types of algorithms are also created and compared. Application-related changes are made to the original algorithm. The time complexity of the algorithm increases at the expense of space complexity. Space is more complex with modern hardware so you can implement such an algorithm.

Features of the Formation of an “Information Flight Model” by Simulators of an Aviation Simulator

Currently, flight simulators are being developed to train pilots in the professional piloting of an aircraft in “special cases of flight”. This is due to the need to teach the pilot the professional skills of piloting an aircraft in situations that are dangerous to reproduce in real flight. An aviation simulator is a combination of several imitators that simulate information about the behavior of all units of the aircraft and information about the interaction of the airframe of the aircraft with the atmosphere, depending on the control actions transmitted by the pilot through the simulators of the flight simulator controls. It is believed that the quality of information models synthesized by simulators is determined by the capabilities of modern software and hardware elements, or used mechanical units. It is impossible to create a complete model of any node; therefore, each imitator synthesizes, in addition to true information, additional false information. It is impossible to exclude false information. Therefore, when developing aviation simulators, a number of training situations are determined. The article discusses the features of assessing the degree of participation of information from two groups imitators in the formation of the components of a cognitive model that allows a pilot to fly an aircraft.

VPIC 2.0: Next Generation Particle-in-Cell Simulations

VPIC is a general purpose Particle-in-Cell simulation code for modeling plasma phenomena such as magnetic reconnection, fusion, solar weather, and laser-plasma interaction in three dimensions using large numbers of particles. VPIC's capacity in both fidelity and scale makes it particularly well-suited for plasma research on pre-exascale and exascale platforms. In this paper we demonstrate the unique challenges involved in preparing the VPIC code for operation at exascale, outlining important optimizations to make VPIC efficient on accelerators. Specifically, we show the work undertaken in adapting VPIC to exploit the portability-enabling framework Kokkos and highlight the enhancements to VPIC's modeling capabilities to achieve performance at exascale. We assess the achieved performance-portability trade-off through a suite of studies on nine different varieties of modern pre-exascale hardware. Our performance-portability study includes weak-scaling runs on three of the top ten TOP500 supercomputers, as well as a comparison of low-level system performance of hardware from four different vendors.

Kokkos 3: Programming Model Extensions for the Exascale Era

As the push towards exascale hardware has increased the diversity of system architectures, performance portability has become a critical aspect for scientific software. We describe the Kokkos Performance Portable Programming Model that allows developers to write single source applications for diverse high-performance computing architectures. Kokkos provides key abstractions for both the compute and memory hierarchy of modern hardware. We describe the novel abstractions that have been added to Kokkos version 3 such as hierarchical parallelism, containers, task graphs, and arbitrary-sized atomic operations to prepare for exascale era architectures. We demonstrate the performance of these new features with reproducible benchmarks on CPUs and GPUs.

Artificial Intelligence Technologies for COVID-19 De Novo Drug Design.

The recent covid crisis has provided important lessons for academia and industry regarding digital reorganization. Among the fascinating lessons from these times is the huge potential of data analytics and artificial intelligence. The crisis exponentially accelerated the adoption of analytics and artificial intelligence, and this momentum is predicted to continue into the 2020s and beyond. Drug development is a costly and time-consuming business, and only a minority of approved drugs generate returns exceeding the research and development costs. As a result, there is a huge drive to make drug discovery cheaper and faster. With modern algorithms and hardware, it is not too surprising that the new technologies of artificial intelligence and other computational simulation tools can help drug developers. In only two years of covid research, many novel molecules have been designed/identified using artificial intelligence methods with astonishing results in terms of time and effectiveness. This paper reviews the most significant research on artificial intelligence in de novo drug design for COVID-19 pharmaceutical research.

Multi-relation Graph Summarization

Graph summarization is beneficial in a wide range of applications, such as visualization, interactive and exploratory analysis, approximate query processing, reducing the on-disk storage footprint, and graph processing in modern hardware. However, the bulk of the literature on graph summarization surprisingly overlooks the possibility of having edges of different types. In this article, we study the novel problem of producing summaries of multi-relation networks, i.e., graphs where multiple edges of different types may exist between any pair of nodes. Multi-relation graphs are an expressive model of real-world activities, in which a relation can be a topic in social networks, an interaction type in genetic networks, or a snapshot in temporal graphs. The first approach that we consider for multi-relation graph summarization is a two-step method based on summarizing each relation in isolation, and then aggregating the resulting summaries in some clever way to produce a final unique summary. In doing this, as a side contribution, we provide the first polynomial-time approximation algorithm based on the k -Median clustering for the classic problem of lossless single-relation graph summarization. Then, we demonstrate the shortcomings of these two-step methods, and propose holistic approaches, both approximate and heuristic algorithms, to compute a summary directly for multi-relation graphs. In particular, we prove that the approximation bound of k -Median clustering for the single relation solution can be maintained in a multi-relation graph with proper aggregation operation over adjacency matrices corresponding to its multiple relations. Experimental results and case studies (on co-authorship networks and brain networks) validate the effectiveness and efficiency of the proposed algorithms.

CPU and GPU real-time filtering methods for dense surface metrology using general matrix to matrix multiplications

Filtering is a required task in surface metrology for the identification of the components relevant for automated quality control. The calculation of real-time features about the surface is crucial to determining the mechanical and physical properties of the inspected product. The computation efficiency of the filtering operations is a major challenge in surface metrology, as current sensors provide massive volumes of data at very high acquisition rates. To overcome the challenges, this work presents different real-time filtering solutions comparing the performance on the CPU and on the GPU, using modern hardware. The proposed framework is focused on filtering techniques that can be expressed using a finite impulse response (FIR) kernel that includes the Gaussian kernel, the most common filtering technique recommended by ISO and ASME standards. This research work proposes variations of the double FIFO and double circular filters. The filters are transformed into a series of general matrix to matrix multiplications, which can be run extremely efficiently on different architectures. The proposed filtering approach provides superior performance compared with previous works. Additionally, tests are carried out to quantify the performance of the GPU in terms of data transfer and computation capabilities in order to diminish the penalty imposed by data transfer from main memory to the GPU in real-time operations. Based on the results, an efficient batch filtering technique is proposed that can be run on the GPU faster than the CPU even for small profile and kernel sizes, offloading this task from the host CPU for optimal system and application response.

The leaky semicolon: compositional semantic dependencies for relaxed-memory concurrency

Program logics and semantics tell a pleasant story about sequential composition: when executing (S1;S2), we first execute S1 then S2. To improve performance, however, processors execute instructions out of order, and compilers reorder programs even more dramatically. By design, single-threaded systems cannot observe these reorderings; however, multiple-threaded systems can, making the story considerably less pleasant. A formal attempt to understand the resulting mess is known as a “relaxed memory model.” Prior models either fail to address sequential composition directly, or overly restrict processors and compilers, or permit nonsense thin-air behaviors which are unobservable in practice. To support sequential composition while targeting modern hardware, we enrich the standard event-based approach with preconditions and families of predicate transformers. When calculating the meaning of (S1; S2), the predicate transformer applied to the precondition of an event e from S2 is chosen based on the set of events in S1 upon which e depends. We apply this approach to two existing memory models.

LaRA 2: parallel and vectorized program for sequence\u2013structure alignment of RNA sequences

BackgroundThe function of non-coding RNA sequences is largely determined by their spatial conformation, namely the secondary structure of the molecule, formed by Watson–Crick interactions between nucleotides. Hence, modern RNA alignment algorithms routinely take structural information into account. In order to discover yet unknown RNA families and infer their possible functions, the structural alignment of RNAs is an essential task. This task demands a lot of computational resources, especially for aligning many long sequences, and it therefore requires efficient algorithms that utilize modern hardware when available. A subset of the secondary structures contains overlapping interactions (called pseudoknots), which add additional complexity to the problem and are often ignored in available software.ResultsWe present the SeqAn-based software LaRA 2 that is significantly faster than comparable software for accurate pairwise and multiple alignments of structured RNA sequences. In contrast to other programs our approach can handle arbitrary pseudoknots. As an improved re-implementation of the LaRA tool for structural alignments, LaRA 2 uses multi-threading and vectorization for parallel execution and a new heuristic for computing a lower boundary of the solution. Our algorithmic improvements yield a program that is up to 130 times faster than the previous version.ConclusionsWith LaRA 2 we provide a tool to analyse large sets of RNA secondary structures in relatively short time, based on structural alignment. The produced alignments can be used to derive structural motifs for the search in genomic databases.