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Message Passing Interface (MPI) is the de facto standard for parallel programming, and collective operations in MPI are widely utilized by numerous scientific applications. The efficiency of these collective operations greatly impacts the performance of parallel applications. With the increasing scale and heterogeneity of HPC systems, the network environment has become more complex. The network states vary widely and dynamically between node pairs, and this makes it more difficult to design efficient collective communication algorithms. In this paper, we propose a method to optimize collective operations by using real-time measured network states, specifically focusing on the binomial tree algorithm. Our approach employs a low-overhead method to measure the network states, and the binomial tree with small latency is constructed based on the measurement result. Additionally, we take into account the disparities between the two underlying MPI peer-to-peer communication protocols, eager and rendezvous, and design tailored binomial tree construction algorithms for each protocol. We have implemented hierarchical MPI_Bcast, MPI_Reduce, MPI_Gather and MPI_Scatter, utilizing our network states-aware binomial tree algorithm at the inter-node level. The benchmark results demonstrate that our algorithm effectively enhances performance in small and medium message communication when compared to the default binomial tree algorithm in Open MPI. Specifically, for MPI_Bcast, we observe an average performance improvement of over 15.5% when the message size is less than 64KB. Similarly, for MPI_Reduce, there is an average performance improvement of over 12.1% when the message is below 2KB. In addition, there is an average performance improvement of over 10% for MPI_Gather when the message ranging from 64B to 512B. For MPI_Scatter, our algorithm achieved performance improvement only for certain message sizes. [ABSTRACT FROM AUTHOR]

Many asset-intensive organizations implement risk management strategies to mitigate potential hazards associated with physical asset failures, such as infrastructure deterioration or mechanical breakdown. As these physical assets' risks can be treated with maintenance activities, properly evaluating the performance of maintenance management is of interest for risk management. Accordingly, this paper proposes a framework for the determination of Maintenance Performance Indicators (MPIs) to support the risk management of physical assets. The proposed framework included four main processes: Integrate performance evaluation guidelines, Review the maintenance management strategy, Define the performance indicators, and Assess maintenance across the MPIs. The ISO 55000 series for asset management and the Balanced Scorecard (BSC) approach were the guidelines considered. The ISO 55001 standard provides three assessment domains for performance evaluation: asset portfolio, asset management, and asset management system. The BSC approach identifies four performance evaluation perspectives that were integrated to address the requirements of one of these asset management domains. Then, the MPIs were defined for each of the performance evaluation domains in line with the maintenance management strategy toward the risk management of physical assets. Through a case study, the proposed framework was demonstrated considering the operational context of a Brazilian hydroelectric power plant. As a result, the proposed framework was shown to be consistent in systematically determining the MPIs that support risk management in organizations. [ABSTRACT FROM AUTHOR]

The development of new exascale supercomputers has dramatically increased the need for fast, high-performance networking technology. Efficient network topologies, such as Dragonfly+, have been introduced to meet the demands of data-intensive applications and to match the massive computing power of GPUs and accelerators. However, these supercomputers still face performance variability mainly caused by the network that affects system and application performance. This study comprehensively analyzes performance variability on a large-scale HPC system with Dragonfly+ network topology, focusing on factors such as communication patterns, message size, job placement locality, MPI collective algorithms, and overall system workload. The study also proposes an easy-to-measure metric for estimating network background traffic generated by other users, which can be used to estimate the performance of our job accurately. The insights gained from this study contribute to improving performance predictability, enhancing job placement policies and MPI algorithm selection, and optimizing resource management strategies in supercomputers. [ABSTRACT FROM AUTHOR]

The discovery of Allele-Specific Methylation (ASM) is an important research field in biology as it regulates genomic imprinting, which has been identified as the cause of some genetic diseases. Nevertheless, the high computational cost of the bioinformatic tools developed for this purpose prevents their application to large-scale datasets. Hence, much faster tools are required to further progress in this research field. In this work we present PARamrfinder, a parallel tool that applies a statistical model to identify ASM in data from high-throughput short-read bisulfite sequencing. It is based on the state-of-the-art sequential tool amrfinder, which is able to detect ASM at regional level from Bisulfite Sequencing (BS-Seq) experiments in the absence of Single Nucleotide Polymorphism information. PARamrfinder provides the same Allelically Methylated Regions as amrfinder but at significantly reduced runtime thanks to exploiting the compute capabilities of common multicore CPU clusters and MPI RMA operations to attain an efficient dynamic workload balance. As an example, our tool is up to 567 times faster for real data experiments on a cluster with 8 nodes, each one containing two 16-core processors. The source code of PARamrfinder, as well as a reference manual, is available at https://github.com/UDC-GAC/PARamrfinder. [ABSTRACT FROM AUTHOR]

In this research, we present the pure open multi-processing (OpenMP), pure message passing interface (MPI), and hybrid MPI/OpenMP parallel solvers within the dynamic explicit central difference algorithm for the coining process to address the challenge of capturing fine relief features of approximately 50 microns. Achieving such precision demands the utilization of at least 7 million tetrahedron elements, surpassing the capabilities of traditional serial programs previously developed. To mitigate data races when calculating internal forces, intermediate arrays are introduced within the OpenMP directive. This helps ensure proper synchronization and avoid conflicts during parallel execution. Additionally, in the MPI implementation, the coins are partitioned into the desired number of regions. This division allows for efficient distribution of computational tasks across multiple processes. Numerical simulation examples are conducted to compare the three solvers with serial programs, evaluating correctness, acceleration ratio, and parallel efficiency. The results reveal a relative error of approximately 0.3% in forming force among the parallel and serial solvers, while the predicted insufficient material zones align with experimental observations. Additionally, speedup ratio and parallel efficiency are assessed for the coining process simulation. The pureMPI parallel solver achieves a maximum acceleration of 9.5 on a single computer (utilizing 12 cores) and the hybrid solver exhibits a speedup ratio of 136 in a cluster (using 6 compute nodes and 12 cores per compute node), showing the strong scalability of the hybrid MPI/OpenMP programming model. This approach effectively meets the simulation requirements for commemorative coins with intricate relief patterns. [ABSTRACT FROM AUTHOR]

We present two magnetic particle imaging (MPI) systems with bore sizes of 75 mm and 100 mm, respectively, using three-dimensionally arranged permanent magnets for excitation and frequency mixing magnetic detection (FMMD) coils for detection. A rotational and a translational stage were combined to move the field free line (FFL) and acquire the MPI signal, thereby enabling simultaneous overall translation and rotational movement. With this concept, the complex coil system used in many MPI systems, with its high energy consumption to generate the drive field, can be replaced. The characteristic signal of superparamagnetic iron oxide (SPIO) nanoparticles was generated via movement of the FFL and acquired using the FMMD coil. The positions of the stages and the occurrence of the f1 + 2f2 harmonics were mapped to reconstruct the spatial location of the SPIO. Image reconstruction was performed using Radon and inverse Radon transformations. As a result, the presented method based on mechanical movement of permanent magnets can be used to measure the MPI, even for samples as large as 100 mm. Our research could pave the way for further technological developments to make the equipment human size, which is one of the ultimate goals of MPI. [ABSTRACT FROM AUTHOR]

Background: Sarcopenia is associated with adverse health outcomes. Understanding the association between sarcopenia, multidimensional frailty, and prognosis is essential for improving patient care. The aim of this study was to assess the prevalence and prognostic signature of sarcopenia in an acute hospital setting co-led by internists and geriatricians. Methods: Sarcopenia was assessed by applying the European Working Group on Sarcopenia in Older People (EWGSOP2) algorithm, including the SARC-F score, handgrip strength, bioelectrical impedance analysis (BIA), and Timed Up and Go (TUG) test, to 97 older multimorbid inpatients (76.5 ± 6.8 years, 55% women). The patients underwent a Comprehensive Geriatric Assessment (CGA) including an evaluation of Geriatric Syndromes (GSs) and Resources (GR) and prognosis calculation using the CGA-based Multidimensional Prognostic Index (MPI), European Quality of life—5 Dimensions (EQ-5D-5L) scale, Rosenberg Self-Esteem Scale (RSES), and Geriatric Depression Scale (GDS). Information on survival and rehospitalizations was collected 1, 3, and 6 months after discharge. Results: Sarcopenia was present in 63% (95% CI: 54–72%) of patients and categorized as probable (31%), confirmed (13%), and severe sarcopenia (18%). Sarcopenic patients showed significantly higher median MPI-values (p < 0.001), more GSs (p = 0.033), fewer GR (p = 0.003), lower EQ-5D-5L scores (p < 0.001), and lower RSES scores (p = 0.025) than non-sarcopenic patients. Six months after discharge, being sarcopenic at baseline was predictive of falls (p = 0.027) and quality of life (p = 0.043), independent of age, gender, and MPI. Conclusions: Sarcopenia is highly prevalent in older hospitalized multimorbid patients and is associated with poorer prognosis, mood, and quality of life up to 6 months after discharge, independent of age, sex, and MPI as surrogate markers of biological age. [ABSTRACT FROM AUTHOR]

Collective communication APIs equip MPI vendors with the necessary context to optimize cluster-wide operations on the basis of theoretical complexity models and characteristics of the involved interconnects. Modern HPC runtime systems with a programmability focus can perform dependency analysis to eliminate the need for manual communication entirely. Profiting from optimized collective routines in this context often requires global analysis of the implicit point-to-point communication pattern or tight constrains on the data access patterns allowed inside kernels. The Celerity API provides a high degree of freedom for both runtime implementors and application developers by tieing transparent work assignment to data access patterns through user-defined range-mapper functions. Canonically, data dependencies are resolved through an intra-node coherence model and inter-node point-to-point communication. This paper presents Collective Pattern Discovery (CPD), a fully distributed, coordination-free method for detecting collective communication patterns on parallelized task graphs. Through extensive scheduling and communication microbenchmarks as well as a strong scaling experiment on a compute-intensive application, we demonstrate that CPD can achieve substantial performance gains in the Celerity model. [ABSTRACT FROM AUTHOR]

Message matching within MPI is an important performance consideration for applications that utilize two-sided semantics. In this work, we present an instrumentation of the CrayMPI library that allows the collection of detailed message-matching statistics as well as an implementation of hashed matching in software. We use this functionality to profile key DOE applications with complex communication patterns to determine under what circumstances an application might benefit from hardware offload capabilities within the NIC to accelerate message matching. We find that there are several applications and libraries that exhibit sufficiently long match list lengths to motivate a Binned Message Matching approach.

Applying malleability to HPC systems can increase their productivity without degrading or even improving the performance of running applications. This paper presents Proteo, a configurable framework that allows to design benchmarks to study the effect of malleability on a system, and also incorporates malleability into a real application. Proteo consists of two modules: SAM allows to emulate the computational behavior of iterative scientific MPI applications, and MaM is able to reconfigure a job during execution, adjusting the number of processes, redistributing data, and resuming execution. An in-depth study of all the possibilities shows that Proteo is able to behave like a real malleable or non-malleable application in the range [0.85, 1.15]. Furthermore, the different methods defined in MaM for process management and data redistribution are analyzed, concluding that asynchronous malleability, where reconfiguration and application execution overlap, results in a 1.15 × speedup. [ABSTRACT FROM AUTHOR]

A comparative analysis of the rapid intensification (RI) of super cyclonic storms Chapala (2015) and Kyarr (2019) in the Arabian Sea is conducted using the North Indian Ocean tropical cyclone data, microwave sounding images, the NOAA OISST data and the ERA5 reanalysis data. Results show that the subtropical westerly jet stream and the Southern Hemisphere anticyclonic circulation led to the formation of an obvious double-channel outflow from the northern and southern sides of the two storm centers, and the substantial inflow appeared at the eastern boundary layer of both storms. These promoted the vertical ascent motion and release of the latent heat of condensation. A warm sea surface is a necessary but not dominant factor for the RI of cyclonic storms in the Arabian Sea. During the RI of Chapala and Kyarr, the deep vertical wind shear was less than 10 m s−1; moreover, the mid-level humidity conditions favored the RI of the two cyclonic storms. Chapala had a single warm core, whereas Kyarr had double warm cores in the vertical direction. The impacts of the latent heat of fusion is more obvious for Chapala, and the potential vorticity in its inner core increases from 4.4 PVU to 8.8 PVU, whereas the potential vorticity and vorticity in the inner core of Kyarr do not change significantly. Microwave detection images show that both Chapala and Kyarr were accompanied by the formation of eyewalls during the RI phase, and the radius of maximum wind decreased and the maximum wind speed increased during the eyewall-thinning process. Both Chapala and Kyarr passed through a positive anomaly region of maximum potential intensity during the RI phase, which increases the possibility to develop to higher intensity after genesis.

Purpose: We evaluated the impact on cardiovascular outcome of coronary revascularization-induced changes in ischemic total perfusion defect (ITPD) and myocardial flow reserve (MFR) as assessed by 82Rb positron emission tomography (PET)/computed tomography (CT) imaging. Methods: The study included 102 patients referred to 82Rb PET/CT myocardial perfusion imaging before and after coronary revascularization. All patients were followed for the occurrence of cardiovascular events (cardiac death, nonfatal myocardial infarction, repeated revascularization, and heart failure) after the second imaging study. Results: During a median follow-up of 20 months, 21 events occurred. The clinical characteristics were comparable between patients with and without events. In the overall study population, after revascularization, there was a significant reduction (P < 0.001) of ITPD, while hyperemic myocardial blood flow (MBF) (P < 0.01) and MFR (P < 0.05) significantly improved. Event rate was higher in patients with ITPD (P < 0.005) or MFR (P < 0.001) worsening compared to those with unchanged or improved ITPD or MFR. At Cox univariable analysis, ITPD and MFR worsening resulted in predictors of events (both P < 0.05). Patients with worsening of both ITPD and MFR had the worst event-free survival (log-rank 32.9, P for trend < 0.001). Conclusions: In patients with stable CAD, worsening of ITPD and MFR after revascularization procedures is associated with higher risk of cardiovascular events. Follow-up MPI with 82Rb PET/CT may improve risk stratification in patients submitted to coronary revascularization. [ABSTRACT FROM AUTHOR]

Background: Congenital heart diseases (CHD) account for one third of all congenital anomalies. Doppler and Tissue Doppler evaluate cardiac performance and diagnose CHD. Study aim: evaluation ventricular functions in congenital heart diseases using tricuspid plane systolic excursion TAPSI and tissue Doppler-derived left ventricular myocardial performance index MPI. Methods: The study was performed at Pediatric Cardiology Unit of Zagazig University Hospitals on 70 age and sex matched children classified into case group included 35 patients with CHD and control group included 35 healthy children underwent complete history, conventional echocardiographic and tissue Doppler examination. Results: There was increase in cases regarding interventricular septum (IVS) and decrease in left ventricular diameter at end diastole (LVDd), left ventricular diameter at end systole (LVDs), right pulmonary artery diameter (RPA) and left atrium diameter more than control group with no difference in between regarding: posterior wall diameter (PW), fractional shortening (FS), main pulmonary artery diameter, left pulmonary artery diameter (LPA) and aorta diameter. There was a highly significant decrease in TAPSE in case more than control group and significant decrease in ejection time (ET) with no significant difference between case and control group regarding LV MPI. Conclusions: TAPSE is lower in cases compared with control group indicating longitudinal RV dysfunction. The value of LV MPI was slightly higher than that of control that need further studies with a larger number of patients.LV FS did not show any abnormality in cases pointing out ability of tissue Doppler echocardiography to measure segmental LV dysfunction compared to conventional echocardiography. [ABSTRACT FROM AUTHOR]

While the computational power of HPC clusters breached through the exascale milestone, it highlighted the need for some critical features like fault management. The current de facto standard for inter-process communication at scale, MPI, lacks proper fault management functionalities, precluding result production in the presence of faults. Many efforts have already addressed the problem, with the ULFM extension and Reinit proposal being the two works receiving the most attention. While powerful and effective, they require expertise from the user and significantly impact the application code. For this reason, we presented the Legio fault resilience framework, which can introduce graceful degradation properties in MPI applications with minimal changes. This work summarises the development and evolution of Legio, highlighting successful use cases and providing some tips for users who want to leverage it for their executions. [ABSTRACT FROM AUTHOR]

Today, various applications in different domains increasingly rely on high-performance computing (HPC) to accomplish computations swiftly. Integrating one or more programming models alongside the used programming language enhances system parallelism, thereby improving its performance. However, this integration can introduce runtime errors such as race conditions, deadlocks, or livelocks. Some of these errors may go undetected using conventional testing techniques, necessitating the exploration of additional methods for enhanced reliability. Formal methods, such as temporal logic, can be useful for detecting runtime errors since they have been widely used in real-time systems. Additionally, many software systems must adhere to temporal properties to ensure correct functionality. Temporal logics indeed serve as a formal frame that takes into account the temporal aspect when describing changes in elements or states over time. This paper proposes a temporal-logic-based testing tool utilizing instrumentation techniques designed for a dual-level programming model, namely, Message Passing Interface (MPI) and Open Multi-Processing (OpenMP), integrated with the C++ programming language. After a comprehensive study of temporal logic types, we found and proved that linear temporal logic is well suited as the foundation for our tool. Notably, while the tool is currently in development, our approach is poised to effectively address the highlighted examples of runtime errors by the proposed solution. This paper thoroughly explores various types and operators of temporal logic to inform the design of the testing tool based on temporal properties, aiming for a robust and reliable system. [ABSTRACT FROM AUTHOR]

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By means of probabilistic graphical models, in this paper, we present a new framework for exploring relationships among indicators commonly included in the Multidimensional Poverty Index (MPI). In particular, we propose an Ising model with covariates for modeling the MPI as an undirected graph. First, we prove why Ising models are consistent with the theoretical distribution of MPI indicators. Then, a comparison between our estimates and the association measures typically used in the literature is provided. Finally, we show how undirected graphs can complement the MPI policy-relevant properties, apart from discovering further insightful patterns that can be useful for policy purposes. This novel approach is illustrated with an empirical application for the global MPI indicators of Guinea and Ecuador, taking living areas and monetary poverty as covariates, respectively. [ABSTRACT FROM AUTHOR]

Yushen Jin,1 Zhongquan Cheng,2 Zhu Yuan,2 Yang Du,3 Jie Tian,3 Bing Shao1,4 1Beijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning, Beijing Centre for Disease Prevention and Control, Beijing, 100013, People’s Republic of China; 2Department of General Surgery, Capital Medical University, Beijing Friendship Hospital, Beijing, 100050, People’s Republic of China; 3CAS Key Laboratory of Molecular Imaging, Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, People’s Republic of China; 4College of Veterinary Medicine, China Agricultural University, Beijing, 100193, People’s Republic of ChinaCorrespondence: Bing Shao; Jie Tian, Email shaobingch@sina.com; jietian@ia.ac.cnPurpose: Liver cancer is considered as the third leading cause of cancer-related deaths, with hepatocellular carcinoma (HCC) accounting for approximately 90% of liver cancers. Improving the treatment of HCC is a serious challenge today. The primary objective of this study was to construct SP94-Fe3O4@ICG&DOX nanoparticles and investigate their potential diagnosis and treatment effect benefits on HCC.Methods: Firstly, we synthesized and characterized SP94-Fe3O4@ICG&DOX nanoparticles and confirmed their in vitro release behavior, photothermal and photodynamic performance. Moreover, the in vivo imaging capability was also observed. Finally, the inhibitory effects on Hepa1-6 in vitro and in vivo were observed as well as biosafety.Results: SP94-Fe3O4@ICG&DOX nanoparticles have a size of ~22.1 nm, with an encapsulation efficiency of 45.2% for ICG and 42.7% for DOX, showing excellent in vivo MPI and fluorescence imaging capabilities for precise tumor localization, and synergistic photo-chemotherapy (pH- and thermal-sensitive drug release) against tumors under irradiation. With the assistance of a fluorescence molecular imaging system or MPI scanner, the location and contours of the tumor were clearly visible. Under a constant laser irradiation (808 nm, 0.6 W/cm2) and a set concentration (50 μg/mL), the temperature of the solution could rapidly increase to ~45 °C, which could effectively kill the tumor cells. It could be effectively uptaken by HCC cells and significantly inhibit their proliferation under the laser irradiation (100% inhibition rate for HCC tumors). And most importantly, our nanoparticles exhibited favorable biocompatibility with normal tissues and cells.Conclusion: This versatile agent can serve as an intelligent and promising nanoplatform that integrates multiple accurate diagnoses, precise positioning of cancer tissue, and effective coordination with synergistic tumor photodynamic therapy. Keywords: porous hollow structure, magnetic particle imaging, fluorescence imaging, synergistic treatment, theranostics

Efficient data movement between nodes in a data center is essential for optimal performance of distributed workloads. With advancements in computing interconnection and memory, new opportunities have emerged. We propose a novel inter-node architecture and protocol called Flexible Memory Units (FMU) that uses optically disaggregated memory. FMUs can be dynamically allocated to different nodes during runtime using optical switches. The primary objective of FMUs is to use the disaggregated memory as temporary buffers during inter-node communication. We have implemented Simplecomm, an open-source simulator, to evaluate real MPI benchmarks using FMU. Our evaluation demonstrates significant speedups of up to $5.18\times $ in communication-bound applications and $1.22\times $ on computing-intensive applications, compared to a 100 Gbps InfiniBand interconnect.

In this paper we identify the causes of numerical non-reproducibility in the unstructured mesh computational motif, a class of algorithms commonly used for the solution of PDEs. We introduce a number of parallel and distributed algorithms to address nondeterminism in the order of floating-point computations, in particular, a new graph coloring scheme that produces identical coloring results regardless of how many parts the graph is partitioned to. We implement these in the OP2 domain specific language (DSL) and show how it can be automatically deployed to any application that uses OP2 without user intervention. We contrast differences in results without reproducibility and then demonstrate how bitwise reproducibility can be gained using our methods on a variety of applications including a production CFD application used at Rolls-Royce. We evaluate the performance and overheads of enforcing bitwise reproducibility on a cluster of CPUs and GPUs. [ABSTRACT FROM AUTHOR]

Summary: To accelerate the communication between nodes, supercomputers are now equipped with multiple network adapters per node, also referred to as HCAs (Host Channel Adapters), resulting in a "multi‐rail"/"multi‐HCA" network. For example, the ThetaGPU system at Argonne National Laboratory (ANL) has eight adapters per node; with this many networking resources available, utilizing all of them becomes non‐trivial. The Message Passing Interface (MPI) is a dominant model for high‐performance computing clusters. Not all MPI collectives utilize all resources, and this becomes more apparent with advances in bandwidth and adapter count in a given cluster. In this work, we provide a thorough performance analysis of existing multirail solutions and their implications on collectives and present the necessity for further enhancement. Specifically, we propose novel designs for hierarchical, multi‐HCA‐aware Allgather. The proposed designs fully utilize all the available network adapters within a node and provide high overlap between inter‐node and intra‐node communication. At the micro‐benchmark level, we see large inter‐node improvements up to 62% and 61% better than HPC‐X and MVAPICH2‐X for 1024 processes. Because Allgather is used in Ring‐Allreduce, our designs also improve its performance by 56% and 44% compared to HPC‐X and MVAPICH2‐X, respectively. At the application level, our enhanced Allgather shows 1.98×$$ 1.98\times $$ and 1.42×$$ 1.42\times $$ improvement in a matrix‐vector multiplication kernel when compared to HPC‐X and MVAPICH2‐X, and Allreduce performs up to 7.83% better in deep learning training against MVAPICH2‐X. [ABSTRACT FROM AUTHOR]

The numerical solution of the Helmholtz equations is challenging to compute when the wave numbers contained in the governing equation are large. In this paper, we present a parallel algorithm for this problem. A class of sixth-order hybrid compact finite-difference schemes for the Helmholtz equations is presented based on the Taylor expansion. To improve the efficiency of solving the large-wave-number problem, we implemented a parallel algorithm based on the Message Passing Interface environment to solve the discrete system. The validity and accuracy of the proposed method are verified by numerical examples. The method is also applicable to solving problems with oscillatory solutions, which are characterized by numerical instability as the wave number increases. [ABSTRACT FROM AUTHOR]

High-performance computing (HPC) and its supercomputers are essential for solving the most difficult issues in many scientific computing domains. The proliferation of computational resources utilized by HPC systems has resulted in an increase in the associated error rates. As such, modern HPC systems promote a hybrid programming style that integrates the message-passing interface (MPI) and open multi-processing (OpenMP). However, this integration often leads to complex defects, such as deadlocks and race conditions, that are challenging to detect and resolve. This paper presents a novel approach: using machine learning algorithms to predict defects in C++-based systems by employing hybrid MPI and OpenMP models. We focus on employing a balanced dataset to enhance prediction accuracy and reliability. Our study highlights the effectiveness of the support vector machine (SVM) classifier, enhanced with term frequency (TF) and recursive feature elimination (RFE) techniques, which demonstrates superior accuracy and performance in defect prediction when compared to other classifiers. This research contributes significantly to the field by providing a robust method for early defect detection in hybrid programming environments, thereby reducing development time, costs and improving the overall reliability of HPC systems. [ABSTRACT FROM AUTHOR]

The Rural Bank (BPR) plays a crucial role in the Indonesian banking industry, particularly at the regional level, serving as an alternative financing source for the unbankable population. This research aims to analyse the productivity levels of BPRs in East Java using the Malmquist Productivity Index (MPI) during the period from 2016 to 2022. The study sample comprises 30 BPRs in East Java. The analysis results indicate that the productivity of BPRs in East Java fluctuates from year to year. Moreover, during the COVID-19 pandemic, BPR productivity experienced a significant decline. The study provides recommendations for BPR management and regulators to pay more attention to BPR productivity and decision-making foundations. [ABSTRACT FROM AUTHOR]

Urban poverty is a complex phenomenon and people experiencing poverty suffer from various deprivations. Multidimensional poverty measurement has been one of the best indicators of this deprivation. In general, slum dwellers are considered homogenous groups, but it is not valid in multidimensional deprivation. This paper aims to find out the correlates of multidimensional poverty in slums. Spatiality and correlates of poverty in Varanasi City have been tapped using statistical modelling. The paper is based on primary data collected from 384 households through an interview schedule from 12 slums across three geographical zones of the city. The MPI index for slums, based on global MPI, was used to compute MPI for each geographical zone. Further ANOVA and hierarchical regression analysis were performed to find spatiality and correlates of multidimensional deprivation. The paper reveals that socio-religious categories, occupation and geographical location are significant determinants or at least correlates of multidimensional poverty in slums. [ABSTRACT FROM AUTHOR]

Background: The aim of this research was to asses perfusion-defect detection-accuracy by human observers as a function of reduced-counts for 3D Gaussian post-reconstruction filtering vs deep learning (DL) denoising to determine if there was improved performance with DL. Methods: SPECT projection data of 156 normally interpreted patients were used for these studies. Half were altered to include hybrid perfusion defects with defect presence and location known. Ordered-subset expectation–maximization (OSEM) reconstruction was employed with the optional correction of attenuation (AC) and scatter (SC) in addition to distance-dependent resolution (RC). Count levels varied from full-counts (100%) to 6.25% of full-counts. The denoising strategies were previously optimized for defect detection using total perfusion deficit (TPD). Four medical physicist (PhD) and six physician (MD) observers rated the slices using a graphical user interface. Observer ratings were analyzed using the LABMRMC multi-reader, multi-case receiver-operating-characteristic (ROC) software to calculate and compare statistically the area-under-the-ROC-curves (AUCs). Results: For the same count-level no statistically significant increase in AUCs for DL over Gaussian denoising was determined when counts were reduced to either the 25% or 12.5% of full-counts. The average AUC for full-count OSEM with solely RC and Gaussian filtering was lower than for the strategies with AC and SC, except for a reduction to 6.25% of full-counts, thus verifying the utility of employing AC and SC with RC. Conclusion: We did not find any indication that at the dose levels investigated and with the DL network employed, that DL denoising was superior in AUC to optimized 3D post-reconstruction Gaussian filtering. [ABSTRACT FROM AUTHOR]

Advances in the prevention and treatment of cardiovascular disease (CVD) over the last decades have led to a marked reduction in mortality for CVD. Nevertheless, atherosclerosis leading to coronary artery disease and stroke remains one of the most common causes of death in the world. The usefulness of imaging tests in the early identification of disease led to identify subjects at major risk of poor outcomes, suggesting risk factor modification. The aim of this article is to analyze the state of art of combined imaging in patients at risk of CVD referred to MPI evaluation, to highlight the present and potential features able to provide incremental prognostic information to help clinicians in patient management and to reduce adverse events. [ABSTRACT FROM AUTHOR]

Driven by advances in computing power, the past decade has seen rapid developments in artificial intelligence (AI) which now offers potential enhancements to every aspect of nuclear cardiology workflow including acquisition, reconstruction, segmentation, direct image analysis, and interpretation; as well as facilitating clinical and imaging big-data integration for superior personalized risk stratification. To understand the relevance and potential of AI in their field, this review provides a primer for nuclear cardiologists in 2022. The aim is to explain terminology and provide a summary of key current implementations, challenges, and future aspirations of AI-based enhancements to nuclear cardiology. [ABSTRACT FROM AUTHOR]

This paper introduces PeriLab, a modern Peridynamics solver developed in the Julia programming language. Emphasizing easy installation, usability, and implementation of new features, the code’s structure is detailed, accompanied by illustrative examples illustrating some of the code’s core functionality. The fully Message Passing Interface (MPI) parallelized code undergoes a separate benchmark problem with two million degrees of freedom, revealing large scale capabilities and analyzing the communication cost occurring in such analysis. The paper highlights key considerations for the adoption of Peridynamics, including the need for a straightforward installation process, user-friendly interfaces, efficient research code development, and well-documented as well as tested functionalities. Overcoming these challenges is crucial for Peridynamics’ widespread acceptance in engineering applications, and PeriLab serves as a valuable contribution to addressing these issues.

Tim Sort is a sorting algorithm that combines Merge Sort and Binary Insertion Sort sorting algorithms. Parallel computing is a computational processing technique in parallel or is divided into several parts and carried out simultaneously. The application of parallel computing to algorithms is called parallelization. The purpose of parallelization is to reduce computational processing time, but not all parallelization can reduce computational processing time. Our research aims to analyse the effect of implementing parallel computing on the processing time of the Tim Sort algorithm. The Team Sort algorithm will be parallelized by dividing the flow or data into several parts, then each sorting and recombining them. The libraries we use are OpenMP and MPI, and tests are carried out using up to 16 core processors and data up to 4194304 numbers. The goal to be achieved by comparing the application of OpenMP and MPI to the Team Sort algorithm is to find out and choose which library is better for the case study, so that when there is a similar case, it can be used as a reference for using the library in solving the problem. The results of research for testing using 16 processor cores and the data used prove that the parallelization of the Sort Team algorithm using OpenMP is better with a speed increase of up to 8.48 times, compared to using MPI with a speed increase of 8.4 times. In addition, the increase in speed and efficiency increases as the amount of data increases. However, the increase in efficiency that is obtained by increasing the processor cores decreases.

While the conventional parallel-hole collimators are widely used in myocardial perfusion imaging (MPI) with SPECT, they are suboptimal in balancing the existing sensitivity-resolution compromise. Therefore, multi-pinhole collimation has been proposed to address the problem. In the present study, a channel multi-pinhole collimated SPECT scanner is modeled and then simulated using the GATE Monte Carlo simulation. The multi-pinhole collimator comprises eight apertures. The material, diameter, and height of the apertures were assumed to be varying. A comparison with conventional single-pinhole was also conducted. The results show that increasing the hole diameter leads to degraded spatial resolution for the multi-pinhole collimator. Compared to the single-pinhole, the multi-pinhole collimators suffer from projection overlapping and thus deteriorated spatial resolution. The findings confirm that the channel multi-pinhole collimators outperform the single-pinhole apertures by providing much higher sensitivity at the expense of slightly lower spatial resolution and therefore would be the collimator of choice for MPI with SPECT.

We present two magnetic particle imaging (MPI) systems with bore sizes of 75 mm and 100 mm, respectively, using three-dimensionally arranged permanent magnets for excitation and frequency mixing magnetic detection (FMMD) coils for detection. A rotational and a translational stage were combined to move the field free line (FFL) and acquire the MPI signal, thereby enabling simultaneous overall translation and rotational movement. With this concept, the complex coil system used in many MPI systems, with its high energy consumption to generate the drive field, can be replaced. The characteristic signal of superparamagnetic iron oxide (SPIO) nanoparticles was generated via movement of the FFL and acquired using the FMMD coil. The positions of the stages and the occurrence of the f1 + 2f2 harmonics were mapped to reconstruct the spatial location of the SPIO. Image reconstruction was performed using Radon and inverse Radon transformations. As a result, the presented method based on mechanical movement of permanent magnets can be used to measure the MPI, even for samples as large as 100 mm. Our research could pave the way for further technological developments to make the equipment human size, which is one of the ultimate goals of MPI.

We present a parallel algorithm for the fast Fourier transform (FFT) in higher dimensions. This algorithm generalizes the cyclic-to-cyclic one-dimensional parallel algorithm to a cyclic-to-cyclic multidimensional parallel algorithm while retaining the property of needing only a single all-to-all communication step. This is under the constraint that we use at most N processors for an FFT on an array with a total of N elements, irrespective of the dimension d or the shape of the array. The only assumption we make is that N is sufficiently composite. Our algorithm starts and ends in the same data distribution. We present our multidimensional implementation FFTU which utilizes the sequential FFTW program for its local FFTs, and which can handle any dimension d. We obtain experimental results for d ≤ 5 using MPI on up to 4096 cores of the supercomputer Snellius, comparing FFTU with the parallel FFTW program and with PFFT and heFFTe. These results show that FFTU is competitive with the state of the art and that it allows one to use a larger number of processors, while keeping communication limited to a single all-to-all operation. For arrays of size 1024³ and 645, FFTU achieves a speedup of a factor 149 and 176, respectively, on 4096 processors. [ABSTRACT FROM AUTHOR]

Bottlenecks and imbalance in parallel programs can significantly affect performance of parallel execution. Finding these bottlenecks is a key issue in performance analysis of MPI programs especially on a large scale. One of the ways to discover bottlenecks is to analyze the critical path of the parallel program: the longest execution path in the program activity graph. There are a number of methods of finding the critical path; however, most of them suffer a performance drop when scaled. In this paper, we analyze several methods of critical path finding based on classical Dijkstra and Delta-stepping algorithms along with the proposed algorithm based on topological sorting. Corresponding algorithms for each approach are presented including additional enhancements for increasing performance. The implementation of the algorithms and resulting performance for several benchmark applications (NAS Parallel Benchmarks, CP2K, OpenFOAM, LAMMPS, and MiniFE) are analyzed and discussed. [ABSTRACT FROM AUTHOR]

This paper is devoted to the use of the multigrid method to accelerate calculations of compressible flows in a stationary formulation on unstructured grids. The multigrid method is used with the construction of a full approximation for each grid level (FAS MG—Full Approximation Scheme Multigrid). In the case of an unstructured grid, such a method can cause difficulties associated both with the construction of grid levels and transition operators between them, and with software implementation in the existing simulation code. The program needs to deal with several different discretizations at once. If the entire data structure, including arrays with grid data, topology, and time integration data, was designed to work on a single grid, then the implementation of the FAS MG can turn into a disaster involving rewriting the entire code. The purpose of this work is to achieve multiple acceleration of calculations at the cost of minimal effort. The problem of implementing the multigrid method on the basis of an existing software package that was not designed to work with several grid levels is solved. The implementation of the multigrid method in an MPI parallel code is carried out in such a way that there is no need to rewrite the program to work with multiple grids at all. Also, difficulties with constructing grid levels for an unstructured grid are avoided; agglomeration of cells is not used, and the number of faces per cell at coarse levels is not increased. In fact, this paper describes how to deploy a FAS MG accelerator in literally a week, even in code that is outdated from the point of view of software architecture. [ABSTRACT FROM AUTHOR]