Parallel Applications Research Articles

Parallelized Event Data Management System Based on MT-SNiPER Framework and PODIO

Software framework serves as a skeleton for the offline data processing software for many high energy physics (HEP) experiments. The event data management, including the event data model (EDM), transient event store and data input/output, implements the core functionalities of the framework, and has a great impact on the performance of the entire offline software. Future HEP experiments are generating increasingly large amounts of data, bringing challenges to offline data processing. To address this issue, a common event data management system that supports efficient parallelized data processing applications has been developed based on Software for Non-collider Physics ExpeRiments (SNiPER) common software framework as well as PODIO, a common EDM toolkit for future HEP experiments. In this paper, the implementation of a parallelized event data management (PEDM) system is introduced, including the integration with MT-SNiPER and PODIO, as well as the implementation of GlobalStore to support multi-threaded event processing. Finally, the application and performance evaluation of the data management system in OSCAR (offline software of Super Tau Charm Facility) is presented.

Minimum Cost Redundancy Optimization for a Parallel Application on Engineering Systems

Minimum Cost Redundancy Optimization for a Parallel Application on Engineering Systems

Selective modal excitation in a multimode nanoslit by interference of surface plasmon waves.

Interference of surface plasmons has been widely utilized in optical metrology for applications such as high-precision sensing. In this paper, we introduce a surface plasmon interferometer with the potential to be arranged in arrays for parallel multiplexing applications. The interferometer features two grating couplers that excite surface plasmon polariton (SPP) waves traveling along a gold-air interface before converging at a gold nanoslit where they interfere. A key innovation lies in the ability to tune the interference pattern by altering the geometrical properties of the gold nanoslit such that one, two or more resonance modes are supported in the nanoslit. Our experimental results validate the approach of our design and modelling process, demonstrating the potential to fine-tune geometrical parameters such as grating coupler pitch, depth, duty cycle, and nanoslit dimensions to alter the transmitted radiation pattern and the transmittance. We demonstrate the ability of a grating coupler to induce focusing of SPP waves to an arbitrary location on chip by illuminating with a converging Gaussian beam. Additionally, we observed far-field interference patterns linked to the multimodal operation of the nanoslit.

Evaluation method of compression parallel to grain stiffness in wood and relationship between stiffness and shape of contact surface

The compressive behavior parallel to the grain is an essential parameter for the designing of multistoried and large timber buildings. However, the application of a compressive force parallel to the grain results in significant deformations near the end grain, which is referred to as the damage zone. Therefore, this study elucidates the mechanism of the damage zone and proposed a methodology to evaluate the properties of the damage zone. The cause of the damage zone was attributed to an uneven contact surface. As the contact surface shape remained non-flat even after reaching 28% of the predicted maximum load, the initial stiffness of compression parallel to the grain necessitated an assessment based on the influence of the damage zone. The Young’s modulus of the damage zone was approximately 2% of that of the middle zone and an evaluation method for the damage zone length was proposed using the strongest link model. The Young’s modulus and damage zone length evaluation methods were used to evaluate the stiffness of the specimens when compressed parallel to the grain. The proposed method could adequately evaluate the experimental values.

Innovations in mathematical modeling, AI, and optimization techniques

This special issue is dedicated to examining the rapidly evolving fields of artificial intelligence, mathematical modeling, and optimization, with particular emphasis on their growing importance in computational science. It features the most notable papers from the "Mathematical Modeling and Problem Solving" workshop at PDPTA'24, the 30th International Conference on Parallel and Distributed Processing Techniques and Applications. The issue showcases pioneering research in areas such as natural language processing, system optimization, and high-performance computing. The nine selected studies include novel AI-driven methods for chemical compound generation, historical text recognition, and music recommendation, along with advancements in hardware optimization through reconfigurable accelerators and vector register sharing. Additionally, evolutionary and hyper-heuristic algorithms are explored for sophisticated problem-solving in engineering design, and innovative techniques are introduced for high-speed numerical methods in large-scale systems. Collectively, these contributions demonstrate the significance of AI, supercomputing, and advanced algorithms in driving the next generation of scientific discovery.

Application of parallel computing technology for modelling complex dynamic objects

The paper is devoted to the development of approaches to the application of parallel algorithms in modelling complex dynamic objects. An overview of the existing principles of computer modelling based on parallel computing procedures is given. It is proposed to describe complex dynamic objects in the form of macromodels. An algorithm for parallelising computations when constructing a nonlinear macromodel of a dynamic object with a separate linear part is described. An iterative algorithm for constructing a macromodel that describes heterogeneous dynamic characteristics of an object is formulated

AsterX: a new open-source GPU-accelerated GRMHD code for dynamical spacetimes

Abstract We present AsterX, a novel open-source, modular, GPU-accelerated, fully general relativistic magnetohydrodynamic (GRMHD) code designed for dynamic spacetimes in 3D Cartesian coordinates, and tailored for exascale computing. We utilize block-structured adaptive mesh refinement (AMR) through CarpetX, the new driver for the Einstein Toolkit, which is built on AMReX, a software framework for massively parallel applications. AsterX employs the Valencia formulation for GRMHD, coupled with the Z4c formalism for spacetime evolution, while incorporating high resolution shock capturing schemes to accurately handle the hydrodynamics. AsterX has undergone rigorous testing in both static and dynamic spacetime, demonstrating remarkable accuracy and agreement with other codes in literature. Using subcycling in time, we find an overall performance gain of factor 2.5 to 4.5. Benchmarking the code through scaling tests on OLCF's Frontier supercomputer, we demonstrate a weak scaling efficiency of about 67\%-77\% on 4096 nodes compared to an 8-node performance.

Comparative assessment of microscopy, malaria rapid diagnostic test and polymerase chain reaction as malaria diagnostic tools in Adama Woreda, East shoa zone of Ethiopia: a cross-sectional study

BackgroundOne of the main challenge for controlling the morbidity and mortality related to malaria is the absence of reliable treatment and precise diagnostic tools in malaria-prone regions. Despite the number of diagnostic techniques used, and inconsistent results were found from previous studies. The aim of this study is to assess the effectiveness of 18S nested PCR(Polymerase Chain Reaction),microscopy, and CarestartTMpf/pan RDT(Rapid Diagnostic Tests) as malaria diagnostic methods using Microscopy and 18S nested PCR as reference techniques.MethodsA facilities and community based cross-sectional study was conducted in the villages of Batodegama kebele and Adama malaria control center from December 2016 to February 2017. A fingerprick blood sample was collected from each participant for the CarestartTM pf/pan RDT test, microscopy, and dry blood spot (DBS) analysis and 18S nested PCR assay. Data were analyzed using STATA11 to calculate the sensitivity, specificity, predictive values, and accuracy.ResultsAmong the 128 asymptomatic patients, 26 (20.3%) were positive for malaria nested 18S PCR, 5 (3.9%) through RDT, and 8 (6.3%) through microscopy. From 202 symptomatic Patients, 55 (27.23%), 26 (12.87%), and 28 (13.86%) individuals were positive for 18S nested PCR, RDT, and microscopy, respectively. Comparative analysis of 18S nested PCR, microscopy, and CarestartTMpf/pan RDT have similar sensitivities of 50% and specificities of 100%.for diagnosing symptomatic malaria infections. Furthermore, species level analysis showed that 18S nested PCR has a higher detection rate of 26 (20.31%) than microscopy 8 (6.25%) and CareStartTM pf/pan RDT 5 (4.1%). The CarestartTMpf/pan RDT had a sensitivity of 15.4% and specificity of 98% in detecting asymptomatic malaria infections. However, the two methods have comparable sensitivities.ConclusionsThe 18S nested PCR assay showed superior performance in all circumstances. On the other hand, the overall performance of CareStart TM pf/pan RDTs was found to be comparable to that of microscopy. This finding highlights the value of parallel application of CareStart TM pf/pan RDTs and microscopy in a resource-limited setup.

ACCELERATING IMAGE PROCESSING USING PARALLEL COMPUTATIONS IN OPENMP: DEVELOPMENT AND PERFORMANCE ANALYSIS OF A GRAPHICS EDITOR

In today’s digital world, image processing plays a crucial role in various aspects of human life. From creating visual content for social media to analyzing medical images, powerful tools for image manipulation are in constant demand. The growing requirements for image quality and processing speed make the search for efficient methods to accelerate these processes highly relevant. This paper investigates the development and implementation of a graphics editor that utilizes OpenMP parallel computing to accelerate data processing. This technology enables the efficient distribution of computational tasks across multiple processor cores, significantly improving system performance. The developed software offers a set of popular graphic effects, including negative, grayscale, sepia, blur, sharpening, and posterization. Each effect is implemented in both sequential and parallel modes using OpenMP, allowing for the comparison of different computational approaches. To evaluate the effectiveness of the proposed solution, a series of experiments were conducted on images of various sizes. These experiments involved applying each effect to images ranging from small icons to high-quality photographs. A comparative analysis of the efficiency of sequential and parallel computation methods demonstrated the significant advantages of the latter. The results of the study show a substantial acceleration of image processing when using OpenMP technology. This acceleration is particularly noticeable for computationally intensive effects such as blurring or sharpening, and when working with large images. In some cases, it was possible to achieve a significant increase in processing speed, opening up new possibilities for working with large volumes of graphic data. This research has significant practical value for software developers working on optimizing the performance of graphics editors and other image processing applications. It demonstrates how the application of modern parallel computing technologies can significantly improve the efficiency of working with graphic data, paving the way for the creation of more powerful and faster image processing tools.

Bank Lending and Policy Interactions—A Comprehensive Assessment for the G20 Countries

ABSTRACTThis study examines the joint impact from supervisory requirements, monetary policies and rescue packages on the supply of bank loans. Evidence is obtained from conceptual considerations and the empirical investigation of G20 banks over the period 1995–2021. To prepare the analysis of interactions, we first address modelling concepts and consistently identify the effects on bank lending that come from each of the regulatory approaches in isolation. Second, we empirically assess the effects that result from the parallel application of policy actions. Short‐term liquidity ratios in combination with further variables mostly associate with positive interaction effects. In contrast, the joint assessment of long‐term liquidity ratios as well as leverage ratios with other policy actions usually provides negative effects. Overall, the results suggest that unconventional monetary policy and rescue actions can stimulate bank lending only after the institutions have restored their own stability. Interactions of policy actions matter, and both regulatory authorities and bank management should consider them.

A-SiC heteromorphic immersion nanocavities enabling wide-field real-time single-molecule detection

Real-time single-molecule detection via fluorescence exhibits advantages of non-contact and specificity, especially in illustrating the dynamic heterogeneity of living substances. However, wide-field view and signal-to-noise ratio (SNR) are always contradictory in real-time single-molecule detection with fluorescence labels, owing to the limitation of the omnidirectional radiation characteristics of fluorophores. Herein, we propose a nano optical sensing device based on a-SiC heteromorphic immersion nanocavities (aHINCs), enabling wide-field real-time single-molecule imaging without sacrificing SNR. The characteristics of architectural aHINCs for far-field imaging are investigated, and the designed sensing device help adjust the emission direction of fluorescence in gold hot spots of nanocavities, allowing the fluorescence divergence angle to be adjusted to ±10°. The experimental results show the SNR reached 22, markedly strengthening the fluorescence collection efficiency. The simultaneous observation of nanocavity sites, within the same field of view of the chip, is 488 times the number of sites observed with classic detection method. Furthermore, the wide-field real-time detection of the single molecule–specific binding process of the oligo DNA complementary chain is successfully realized. The nano optical sensing device based on the aHINC shows potential for parallel real-time single-molecule detection applications.

Parallel–Serial Robotic Manipulators: A Review of Architectures, Applications, and Methods of Design and Analysis

Parallel–serial (hybrid) manipulators represent robotic systems composed of kinematic chains with parallel and serial structures. These manipulators combine the benefits of both parallel and serial mechanisms, such as increased stiffness, high positioning accuracy, and a large workspace. This study discusses the existing architectures and applications of parallel–serial robots and the methods of their design and analysis. The paper reviews around 500 articles and presents over 150 architectures of manipulators used in machining, medicine, and pick-and-place tasks, humanoids and legged systems, haptic devices, simulators, and other applications, covering both lower mobility and kinematically redundant robots. After that, the paper considers how researchers have developed and analyzed these manipulators. In particular, it examines methods of type synthesis, mobility, kinematic, and dynamic analysis, workspace and singularity determination, performance evaluation, optimal design, control, and calibration. The review concludes with a discussion of current trends in the field of parallel–serial manipulators and potential directions for future studies.

Generalized Distributed Reaction Systems

In this paper, we introduce the notion of a generalized distributed reaction system with computations following the concept of the original reaction system: the resulting products in the individual components are obtained by applying rules which take into account the objects in the components of the system as reactants and inhibitors and yield results in specified components of the system. As specific variants, we investigate (i) generalized distributed reaction systems which look at all components for the presence or absence of objects, but the resulting products are only produced in the component the rule is assigned to as well as (ii) generalized distributed reaction systems which look for the presence or absence of objects only in the component the rule is assigned to, but the resulting products can be sent to specified components within the whole system. We first show how all these variants of generalized distributed reaction systems can be flattened to a reaction system having only one component. Moreover, we show how each of these two variants, which are restricted variants of the general model, can simulate even the general model. Finally, we prove that all these variants of generalized distributed reaction systems working with the standard, total parallel application of rules can be transferred into a usual reaction system working with the sequential application of rules.

Implementation of Parallel Applications on Linear Systolic and Star Topologies by Using Multistage Omega Network

Contemporary computer architecture comprises multicomputer settings. Multiple computers provide the facility of high performance to implement multiple threads that are faster and concurrently with different processors that can execute tasks simultaneously. The challenges are as follows: cost and high performance. Certain firms have to provide funding to establish data centers that need locations, hardware, and technicians. After the passage of a period of time, such equipment requires maintenance (updating and upgrading) to take place on it. This paper tackles these challenges by passing the drawbacks of data centers. It provides an algorithm that simulates a virtual machine, as one client is to be connected with eight servers to implement two applications namely convolution and mathematical operations. To represent different topologies, the algorithm simulates supercomputer systems by applying multistage omega network topology and parallel processing. Two types of topologies execute linear systolic and star, and is implemented on transmission control protocol (TCP) and user datagram protocol (UDP) protocols. The goal of this paper is to provide a kernel that draws near a cloud computing system by exploiting the JAVA programming language with its techniques (threading, socket, socket server, Datagram socket, and datagram packet). The results offer the connection between the client and servers to be successfully simulated by using multistage omega network. The linear systolic and star topologies are simulated in virtual parallel processing.

Clinical features and survival rate of patients with ovarian granulosa cell tumor in Iran; a 10-year retrospective study

IntroductionOvarian granulosa cell tumor (OGCT) is a rare female pathology with few available demographic data. Besides, there are no comprehensive clinical characteristics regarding the OGCT in Iran. Thus, this study aimed to assess the clinical features and survival rate of OGCT patients in Iran to expand the scope of knowledge in this field.Materials and methodsIn this 10-year retrospective study (2013–2023), the cases were gathered from the oncologic clinic of women (Imam Khomeini Hospital, Tehran, Iran). The patients with definite OGCT diagnosis were selected based on the inclusion and exclusion criteria including medical history, interfering backgrounds, demographic data, histopathological assessment, clinical and para-clinical features, survival rates, and all previous medical reports for definite diagnosis of OGCT along with approved pathology samples.ResultsThe median age and BMI values of Iranian patients were 45 (19 ~ 83) years and 28.04 (19.4 ~ 48.0), respectively. The most common symptom was abdominal pain (56%) and 69.2% of cases were menopause. In 81.3% of cases, ovarian tumors were detected and metastasis was rare. Most patients (40.6%) underwent total abdominal hysterectomy and OGCT relapsing cases were seen in 13.2% of patients. The median of overall survival (OS) value using the Kaplan-Meier estimate was 52 months (95%CI:37.47–66.53), and the median of disease-free survival (DFS) was 45 months (95%CI: 28.88–61.12). There was a significant (p < 0.05) relation between chemotherapy and left oophorectomy with OS. A significant (p < 0.05) correlation was also detected among the OGCT stage and left oophorectomy with DFS.ConclusionOS and DFS values showed that the OGCT in Iranian patients can be treated in most cases using two main procedures of chemotherapy and oophorectomy. Parallel application of both procedures and associated outcomes are suggested for future studies.

Combining High-Resolution Mass Spectrometry and Chemiluminescence Analysis to Characterize the Composition and Fate of Total N-Nitrosamines in Wastewater Treatment Plants.

Monitoring the prevalence and persistence of N-nitrosamines and their precursors in wastewater treatment plants (WWTPs) and effluent-receiving aquatic compartments is a priority for utilities practicing wastewater recycling or exploiting wastewater-impacted source waters. In this work, we developed an analytical framework that combines liquid chromatography-high-resolution mass spectrometry (LC-HRMS) with acidic triiodide-chemiluminescence analysis to characterize the composition and fate of total N-nitrosamines (TONO) and their precursors along the treatment trains of eight WWTPs in New York. Through the parallel application of LC-HRMS and chemiluminescence methods, the TONO scores for 41 N-nitrosamines containing structurally diverse substituents on their amine nitrogen were derived based on their solid-phase extraction recoveries and conversion efficiencies to nitric oxide. Correcting the compositional analysis of TONO using the TONO scores of target N-nitrosamines refined the assessment of the reduction or accumulation of TONO and their precursors across treatment steps in WWTPs. Nontargeted analysis prioritized seven additional N-nitrosamines for confirmation by reference standards, including three previously uncharacterized species: N-nitroso-tert-butylphenylamine, N-nitroso-2-pyrrolidinmethanol, and N-nitrosodesloratadine, although they only served as minor components of TONO. Overall, our study establishes an adaptable methodological framework for advancing the quantitative and qualitative analysis of specific and unknown components of TONO across water treatment and reuse scenarios.

Proteomic analysis of peripheral blood mononuclear cells in first episode psychosis – Protein and peptide-centered approaches to elucidate potential diagnostic biomarkers

Diagnosing patients suffering from psychotic disorders is far from being achieved with molecular support, despite all the efforts to study these disorders from different perspectives. Characterizing the proteome of easily obtainable blood specimens, such as the peripheral blood mononuclear cells (PBMCs), has particular interest in biomarker discovery and generating pathophysiological knowledge. This approach has been explored in psychiatry, and while generating valuable information, it has not translated into meaningful biomarker discovery. In this project, we report the proof-of-concept of a methodology that aims to explore further information obtained with classical proteomics approaches that is easily overlooked. PBMC samples from first-episode psychosis and control subjects were subjected to a SWATH-MS approach, and the classical protein relative quantification was performed, where 389 proteins were found to be important to distinguish the two groups. Individual analysis of the quantified peptides was also performed, highlighting peptides of unchanged proteins that were significantly altered. With the combination of protein- and peptide-centered proteomics approaches, it is possible to highlight that information about proteoforms, namely regulation at the peptide level possibly due to post-translational modifications, is routinely overlooked and that its diagnostic potential should be further explored. SignificanceOur exploratory findings highlight the potential of MS-based proteomics strategies, combining protein- and peptide-centered approaches, to aid clinical decision-making in first-episode psychosis, helping to establish early biomarkers for schizophrenia and other psychotic disorders. Particularly, the less popular peptide-centered approach allows the identification/measurement of overlooked modulated peptides that may have potential biomarker characteristics. The application in parallel of protein- and peptide-centered strategies is transversal to research of other diseases, potentially allowing a more comprehensive characterization of the metabolic/pathophysiological alterations related to a specific disease.

Abstractions for C++ code optimizations in parallel high-performance applications

Many computational problems consider memory throughput a performance bottleneck, especially in the domain of parallel computing. Software needs to be attuned to hardware features like cache architectures or concurrent memory banks to reach a decent level of performance efficiency. This can be achieved by selecting the right memory layouts for data structures or changing the order of data structure traversal. In this work, we present an abstraction for traversing a set of regular data structures (e.g., multidimensional arrays) that allows the design of traversal-agnostic algorithms. Such algorithms can easily optimize for memory performance and employ semi-automated parallelization or autotuning without altering their internal code. We also add an abstraction for autotuning that allows defining tuning parameters in one place and removes boilerplate code. The proposed solution was implemented as an extension of the Noarr library that simplifies a layout-agnostic design of regular data structures. It is implemented entirely using C++ template meta-programming without any nonstandard dependencies, so it is fully compatible with existing compilers, including CUDA NVCC or Intel DPC++. We evaluate the performance and expressiveness of our approach on the Polybench-C benchmarks.

From minimum-viable-products to full models: a step-wise development of diagnostic forward models in support of design, analysis and modelling on the ST40 tokamak

Like most magnetic confined fusion experiments, the ST40 tokamak started off with a small subset of diagnostics and gradually increased the diagnostic set to include more complex and comprehensive systems. To make the most of each operational phase, forward models of various diagnostics are used and developed to aid design, provide consistency-checks during commissioning, test analysis methods, and build workflows to constrain high-level parameters to inform interpretation, theory and modelling. For new models and new analysis workflows, minimum-viable-products are released early, and their complexity is increased in a step-wise manner, facilitating the support of all programme phases on multiple parallel applications, while enabling learning opportunities and feedback loops. In this contribution we review the philosophy, scope and architecture of the framework under development. We discuss the details of some forward models, with examples on how they are used to aid diagnostic design, to investigate analysis methodologies through synthetic data, and how they are embedded in experimental analysis workflows. We compare previously published experimental results with new, more advanced analysis workflows employing more recent, detailed models and new diagnostic data, providing confirmation of the published material from the 2021–22 experimental campaign.

Application in Parallel to U.S. Residency Training Programs in Multiple Specialties: Trends and Differences by Applicant Educational Background, 2009-2021.

The medical education community is pursuing reforms addressing unsustainable growth in the number of residency applications per applicant and application costs. Little research has examined the prevalence or contributions of parallel applications (application to residency in multiple specialties) to this growth. A retrospective analysis of Electronic Residency Application Service® data provided by the Association of American Medical Colleges was conducted. The percentage of applicants applying to ≥1 specialty, mean number of specialties applied, number of submitted applications, and percentage of applicants to each specialty who were parallel applying were determined. MD, DO, and international (U.S. international medical graduate [IMG] and IMG) applicants were included. The sample contained 586,246 applicant records from 459,704 unique applicants. The percentage of applicants who parallel applied decreased from 41.3% to 35.4% between 2009 and 2021. DO applicants were the only group for whom the percentage parallel applying increased (30.6% vs. 32.1%). IMG (60.4% vs. 49.1%) or USIMG applicants (69.6% vs. 63.1%) were groups with the greatest percentage of applicants parallel applying each year (2009-2021). The mean number of specialties applied to when parallel applying also decreased from 2.96 in 2009 to 2.79 in 2021, overall. Between 2009 and 2021, mean number of applications increased for all applicant types amongst both single-specialty applicant and parallel-applying applicants. Among applicants who were single-specialty applying, mean number of applications grew from 38.6 in 2009 to 74.6 in 2021 and from 95.2 to 149.8 for parallel-applying applicants. All applicant groups experienced decreases in percentages parallel applying except for DO applicants. Parallel application appears to be common and slowly declining, and does not appear to significantly contribute to increasing numbers of applications per candidate. Efforts to control the growth of applications per applicant should continue to focus on applicants' numbers of applications submitted to each specialty.