Design Of Parallel Applications Research Articles

Photo-electrochemical oxidation flow system for stormwater herbicides removal: Operational conditions and energy consumption analysis

Photoelectrochemical oxidation (PECO) is a promising advanced technology for treating micropollutants in stormwater. However, it is important to understand its operation prior to practical validation. In this study, we introduced a flow PECO system designed to evaluate its potential for full-scale applications in herbicides degradation, providing valuable insights for future large-scale implementations. The PECO flow reactor demonstrated the ability to treat a larger volume of stormwater (675 mL, approximately 10 times more than previous batch experiments) with effective removal rates of 92 % for diuron and 22 % for atrazine over 6 h of operation at 2 V. To address the large volume issue in stormwater treatment, a multiple module parallel application design is being considered to increase the treatment capacity of the PECO flow reactor. During the flow reactor operations, flow rate was found to have a notable impact on removal performance, particularly for diuron. At a flow rate of 610 mL min−1, approximately 90 % removal of diuron was achieved, while at 29 mL min−1, the removal efficiency decreased to 60 %. While light intensity had minimal effect on diuron degradation (all settings achieved over 90 % removal), it enhanced atrazine degradation from 9 % to 31 % with an increase in intensity from 63 mW cm−2 to 144 mW cm−2. Remarkably, the PECO flow system exhibited excellent removal performance (>90 % removal) for diuron even at extremely high initial pollutant concentrations (240 μg L−1), demonstrating its capacity to handle varying contaminant loads in stormwater. Energy consumption analysis revealed that flow rate as the primary factor influenced the specific energy consumption rate. Higher flow rate (e.g., 610 mL min−1) were preferable in flow reactor due to its well-balanced performance between removal and energy consumption. These findings confirm that the PECO flow system offers an efficient and promising approach for stormwater treatment applications.

Effective Runtime Management of Tasks and Priorities in GNU OpenMP Applications

OpenMP has become a reference standard for the design of parallel applications. This standard is evolving quickly, thus offering new opportunities to the application programmers. However, OpenMP runtime environments are often not fully aligned with the actual requirements imposed by the evolution of such a standard. Among the main lacks, we find: (a) a limited capability to effectively cope with task priorities, and (b) the inadequacy in guaranteeing core properties while processing tasks such as the so-called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">work-conservativeness</i> —the ability of the OpenMP runtime environment to fully exploit the underlying multi-processor/multi-core machine through the avoidance of thread-blocking phases. In this article, we present the design of extensions to the GNU OpenMP ( <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">GOMP</monospace> ) implementation, integrated into <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">gcc</monospace> , which allow the effective management of tasks and their priorities. Our proposal is based on a user-space library—modularly combined with the one already offered by <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">GOMP</monospace> —and an external kernel-level Linux module—offering the opportunity to exploit raising hardware facilities for task/priority management. We also provide experimental results showing the effectiveness of our proposal, achieved by running either OpenMP common benchmarks or a new benchmark application ( <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Hashtag-Text</small> ) that we explicitly devised to stress the runtime environment in relation to the above-mentioned task/priority management aspects.

Migrating parallel applications to the cloud: assessing cloud readiness based on parallel design decisions

Parallel applications are the computational backbone of major industry trends and grand challenges in science. Whereas these applications are typically constructed for dedicated High Performance Computing clusters and supercomputers, the cloud emerges as attractive execution environment, which provides on-demand resource provisioning and a pay-per-use model. However, cloud environments require specific application properties that may restrict parallel application design. As a result, design trade-offs are required to simultaneously maximize parallel performance and benefit from cloud-specific characteristics. In this paper, we present a novel approach to assess the cloud readiness of parallel applications based on the design decisions made. By discovering and understanding the implications of these parallel design decisions on an application’s cloud readiness, our approach supports the migration of parallel applications to the cloud. We introduce an assessment procedure, its underlying meta model, and a corresponding instantiation to structure this multi-dimensional design space. For evaluation purposes, we present an extensive case study comprising three parallel applications and discuss their cloud readiness based on our approach.

Combined load balancing algorithm in distributed computing environment

Load balancing algorithms and task scheduling are one of the most important tasks in parallel application design and implementation. Proper task assignment to processor cores can minimize execution time and increase the performance of a parallel application. In this paper, we analyzed the domain decomposition and master-slave load balancing algorithms and proposed a combined version. The combined algorithm is based on a combination of standard, existing and well known, domain decomposition and master-slave algorithms. They minimize communication between independent tasks and improve performance of a parallel application. Simulation results confirmed that proposed algorithm decrease the execution time and reduce the load imbalance. DOI: http://dx.doi.org/10.5755/j01.itc.45.3.13084

A DSL Based Toolchain for Design Space Exploration in Structured Parallel Programming

We introduce a DSL based toolchain supporting the design of parallel applications where parallelism is structured after parallel design pattern compositions. A DSL provides the possibility to write high level parallel design pattern expressions representing the structure of parallel applications, to refactor the pattern expressions, to evaluate their non-functional properties (e.g. ideal performance, total parallelism degree, etc.) and finally to generate parallel code ready to be compiled and run on different target architectures. We discuss a proof-of-concept prototype implementation of the proposed toolchain generating FastFlow code and show some preliminary results achieved using the prototype implementation.

SANComSim: A Scalable, Adaptive and Non-intrusive Framework to Optimize Performance in Computational Science Applications

Parallel processing has become the most common solution for developing and executing scientific computing applications. Actually, the best way to obtain good performance ratios is to exploit parallelism in both processing and communications. Although the study of computational performance has historically involved CPU power, currently the CPU is not the only concern in the overall performance. Due to the underlying design of parallel applications, communication networks play a very important role in the field of computational science. Despite the fact that networks used in multicore clusters are fast and have low latency, the amount of transferred data may cause a bottleneck in the communication system, as communication- intensive, parallel applications spend a significant amount of their total execution time exchanging data between processes. Moreover, in most cases, several users are executing different parallel applications at the same time in the cluster. In this paper we present SANComSim, a Scalable, Adaptive and Non-intrusive framework, based on simulation techniques, for optimizing the performance of the network system to execute complex applications. The main objective of this framework is to apply run-time compression, to reduce the data sent through the network, in order to increase the overall system performance. The main features of SANComSim are: adaptability, to dynamically adapt to the current state of the system; portability, the framework is neither focused on a specific programming language nor a platform; non-intrusive, since this framework is based on simulation techniques, which does not require exclusive access of the entire cluster system; scalability, any parallel application, independently of the number of processed and computing nodes, can use this framework to improve performance in cluster systems.

Parallel application benchmarks and performance evaluation of the Intel Xeon 7500 family processors

Abstract With the recent advent of novel multi- and many-core hardware architectures, application programmers have to deal with many hardware-specific implementation details and have to be familiar with software optimization techniques to benefit from new high-performance computing machines. Highly effcient parallel application design is in fact an interdisciplinary process involving domain specific and IT experts. Therefore, this paper aims to present early experiences with computationally demanding applications, development efforts and evaluation of their performance on the new family of Intel Xeon 7500 processors. We selected two application benchmarks applicable to real quantum chemistry and Computational Fluid Dynamics (CFD) problems as they can potentially take advantage of parallel processing on novel hardware architectures and built-in new features. Additionally, we discuss various parallel software improvements to mentioned applications, including appropriate changes to data structures as well as to communication and synchronization routines to deal with multi-level parallelism and hybrid hardware architectures. The obtained results confirmed that new hardware solutions can improve the overall application performance. However, in order to obtain a high level of parallel scalability various application modifications and tuning procedures are required as hardware configurations, including processors characteristics, interconnects and topologies, and they have a great influence on large-scale simulations.

SYMBOLIC EXPRESSION ANALYSIS FOR COMPILED COMMUNICATION

Compiled communication can benefit the parallel application design and performance in several ways such as analyzing the communication pattern to optimize a configurable network for performance improvement or to visualize the communication requirements to study and improve the application design. In this article we present symbolic expression analysis techniques in a MPI parallel compiler. Symbolic expression analysis allows the identification and representation of the communication pattern and also assists in the determination of communication phases in MPI parallel applications at compile-time. We demonstrate that using compiler analysis based on symbolic expression analysis to determine the communication pattern can provide an accurate visualization of the communication requirements. Using information from the compiler to program a circuit switching interconnect in multiprocessor systems has the potential to achieve more efficient communication with lower cost compared to packet/wormhole switching. For example, we demonstrate that our compiler approach provides an average of 2.6 times improvement in message delay over a threshold-based runtime system for our benchmarks with a maximum improvement of 9.7 times.

Para++: A High Level C++ Interface for Message Passing

This paper describes a high level C++ interface for message passing applications. Our interface is built on top of PVM and MPI. The two main contributions are to allow a quicker design of parallel applications without any important drop of performances. We introduce two levels of tasks and use C++ streams for communications. We also present a performance study over both PVM and MPI to show the overhead of our implementation. Finally, we detail two applications based on the heat equation to explain howPara++ can be used for SPMD and MPMD applications.

A toolkit for parallel functional programming

AbstractOur toolkit for the design and implementation of parallel functional programs supports the stepwise development of parallel programs from a high level sequential specification to an optimised parallel implementation. The toolkit is used as follows: The algorithm to be implemented is specified in a functional language. The program is debugged and tested using an interpreter. The program is compiled for a sequential machine. Its performance is analysed and improved. Annotation‐driven transformations are applied to the program to indicate parallel tasks. Simulations at task level, basic block level and bus transaction level make it possible to analyse the parallel performance of the program at three levels of detail. When the performance is optimised using the simulators, the program is executed on a genuine parallel machine. Several programs have been developed with the toolkit. A program that simulates tidal flow in an estuary of the North sea is presented as a case study to demonstrate the merits of the toolkit when developing complex parallel programs.The toolkit not only supports the design of parallel applications, it also allows the study of important concepts in parallel computer architecture. These include the behaviour of cached memory systems, bus protocols, scheduling algorithms and memory management algorithms.

Parallel application design: The simulation approach with HASTE

It is important for the development of an industrial parallel application to have estimates of the execution time and cycle time of the application from early stages of its conception. This paper presents HASTE, a tool built to simulate the behavior of an application in its design form, in terms of real time predictions for a particular target machine (transputers in the current version). HASTE (HAmlet Simulator Tool (E)) is a discrete event simulator implemented by a linkable library for programs written in parallel C. The modelling of the application design is based on functions for synchronization, communication and process creation. An event trace is generated for the analysis of the simulated execution. A version of HASTE has been provided to the parallel application developers of the HAMLET project. They have been using it for a few months and have provided some feedback which is used to develop the next version of the simulator.