Deadline-Budget constrained Scheduling Algorithm for Scientific Workflows in a Cloud Environment

Recently cloud computing has gained popularity among e-Science environments as a high performance computing platform. From the viewpoint of the system, applications can be submitted by users at any moment in time and with distinct QoS requirements. To achieve higher rates of successful applications attending to their QoS demands, an effective resource allocation (scheduling) strategy between workflow\u27s tasks and available resources is required. Several algorithms have been proposed for QoS workflow scheduling, but most of them use search-based strategies that generally have a higher time complexity, making them less useful in realistic scenarios. In this paper, we present a heuristic scheduling algorithm with quadratic time complexity that considers two important constraints for QoS-based workflow scheduling, time and cost, named Deadline-Budget Workflow Scheduling (DBWS) for cloud environments. Performance evaluation of some well-known scientific workflows shows that the DBWS algorithm accomplishes both constraints with higher success rate in comparison to the current state-of-the-art heuristic-based approaches

An OpenMP based Parallelization Compiler for C Applications

Directive-drive programming models, such as OpenMP, are one solution for exploiting the potential of multi-core architectures, and enable developers to accelerate software applications by adding annotations on for-type loops and other code regions. However, manual parallelization of applications is known to be a non trivial and time consuming process, requiring parallel programming skills. Automatic parallelization approaches can reduce the burden on the application development side. This paper presents an OpenMP based automatic parallelization compiler, named AutoPar-Clava, for automatic identification and annotation of loops in C code. By using static analysis, parallelizable regions are detected, and a compilable OpenMP parallel code from the sequential version is produced. In order to reduce the accesses to shared memory by each thread, each variable is categorized into the proper OpenMP scoping. Also, AutoPar-Clava is able to support reduction on arrays, which is available since OpenMP 4.5. The effectiveness of AutoPar-Clava is evaluated by means of the Polyhedral Benchmark suite, and targeting a N-cores x86-based computing platform. The achieved results are very promising and compare favorably with closely related auto-parallelization compilers such as Intel C/C++ Compiler (i.e., icc), ROSE, TRACO, and Cetus

FabSim3: An automation toolkit for verified simulations using high performance computing

A common feature of computational modelling and simulation research is the need to perform many tasks in complex sequences to achieve a usable result. This will typically involve tasks such as preparing input data, pre-processing, running simulations on a local or remote machine, post-processing, and performing coupling communications, validations and/or optimisations. Tasks like these can involve manual steps which are time and effort intensive, especially when it involves the management of large ensemble runs. Additionally, human errors become more likely and numerous as the research work becomes more complex, increasing the risk of damaging the credibility of simulation results. Automation tools can help ensure the credibility of simulation results by reducing the manual time and effort required to perform these research tasks, by making more rigorous procedures tractable, and by reducing the probability of human error due to a reduced number of manual actions. In addition, efficiency gained through automation can help researchers to perform more research within the budget and effort constraints imposed by their projects. This paper presents the main software release of FabSim3, and explains how our automation toolkit can improve and simplify a range of tasks for researchers and application developers. FabSim3 helps to prepare, submit, execute, retrieve, and analyze simulation workflows. By providing a suitable level of abstraction, FabSim3 reduces the complexity of setting up and managing a large-scale simulation scenario, while still providing transparent access to the underlying layers for effective debugging. The tool also facilitates job submission and management (including staging and curation of files and environments) for a range of different supercomputing environments. Although FabSim3 itself is application-agnostic, it supports a provably extensible plugin system where users automate simulation and analysis workflows for their own application domains. To highlight this, we briefly describe a selection of these plugins and we demonstrate the efficiency of the toolkit in handling large ensemble workflows

Tutorial applications for Verification, Validation and Uncertainty Quantification using VECMA toolkit

The VECMA toolkit enables automated Verification, Validation and Uncertainty Quantification (VVUQ) for complex applications that can be deployed on emerging exascale platforms and provides support for software applications for any domain of interest. The toolkit has four main components including EasyVVUQ for VVUQ workflows, FabSim3 for automation and tool integration, MUSCLE3 for coupling multiscale models and QCG tools to execute application workflows on high performance computing (HPC). A more recent addition to the VECMAtk is EasySurrogate for various types of surrogate methods. In this paper, we present five tutorials from different application domains that apply these VECMAtk components to perform uncertainty quantification analysis, use surrogate models, couple multiscale models and execute sensitivity analysis on HPC. This paper aims to provide hands-on experience for practitioners aiming to test and contrast with their own applications

Assessing the strength of reinforced concrete structures through Ultrasonic Pulse Velocity and Schmidt Rebound Hammer tests

The experimental studies using Ultrasonic Pulse Velocity and Schmidt Rebound Hammer as Non-Destructive Tests (NDT) were presented in this paper to establish a correlation between the compressive strengths of compression tests and NDT values. These two tests have been used to determine the concrete quality by applying regression analysis models between compressive strength of in-situ concrete on existing building and tests values. The main members of an existing structure including column, beam and slab were included in the study. The relationship between compression strength of concrete collected from crashing test records and estimated results from NDT’s records using regression analysis was compared together to evaluate their prediction for concrete strength. The test results show that the rebound number method was more efficient in predicting the strength of concrete under certain conditions. A combined method for the above two tests, reveals an improvement in the concrete strength estimation and the latter shows better improvement. Applying combined methods produces more reliable results that are closer to the true values. The resulting strength calibration curves estimation was compared with other results from previous published literatures

Behavior of channel shear connectors in normal and light weight aggregate concrete (Experimental and analytical study)

This paper describes five push-out tests carried out at the University of Malaya using channel shear connector. The tests study experimentally and analytically, the behavior of channel shear connectors embedded in normal and light weight aggregate concrete (LWAC). Limited push-out tests are used to measure the accuracy of a proposed nonlinear finite element model for typical push-out test specimens. Using this model, an extensive parametric study performed to arrive at prediction for shear capacity of channel connectors in LWAC. An equation is suggested for the shear capacity of these connectors in LWAC

Behaviour of C-shaped angle shear connectors under monotonic and fully reversed cyclic loading: An experimental study

This paper presents an evaluation of the structural behaviour of C-shaped angle shear connectors in composite beams, suitable for transferring shear force in composite structures. The results of the experimental programme, including eight push-out tests, are presented and discussed. The results include resistance, strength degradation, ductility, and failure modes of C-shaped angle shear connectors, under monotonic and fully reversed cyclic loading. The results show that connector fracture type of failure was experienced in C-shaped angle connectors and after the failure, more cracking was observed in those slabs with longer angles. On top of that, by comparing the shear resistance of C-shaped angle shear connectors under monotonic and cyclic loading, these connectors showed 8.8-33.1% strength degradation, under fully reversed cyclic loading. Furthermore, it was concluded that the mentioned shear connector shows a proper behaviour, in terms of the ultimate shear capacity, but it does not satisfy the ductility criteria, imposed by the Eurocode 4, to perform a plastic distribution of the shear force between different connectors along the beam length.</p

Large-Scale Parallelization of Human Migration Simulation

Forced displacement of people worldwide, for example, due to violent conflicts, is common in the modern world, and today more than 82 million people are forcibly displaced. This puts the problem of migration at the forefront of the most important problems of humanity. The Flee simulation code is an agent-based modeling tool that can forecast population displacements in civil war settings, but performing accurate simulations requires nonnegligible computational capacity. In this article, we present our approach to Flee parallelization for fast execution on multicore platforms, as well as discuss the computational complexity of the algorithm and its implementation. We benchmark parallelized code using supercomputers equipped with AMD EPYC Rome 7742 and Intel Xeon Platinum 8268 processors and investigate its performance across a range of alternative rule sets, different refinements in the spatial representation, and various numbers of agents representing displaced persons. We find that Flee scales excellently to up to 8192 cores for large cases, although very detailed location graphs can impose a large initialization time overhead