Performance characteristics of openMP constructs, and application benchmarks on a large symmetric multiprocessor

Fredrickson, Nathan R.; Afsahi, Ahmad; Qian, Ying

doi:10.1145/782832.782835

Cited by 3 publications

(2 citation statements)

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“…They observed almost linear speedup for 16 processors. Fredrickson et al [34] evaluated the performance of the parallel genetic algorithm (PGA) using OpenMP constructs, kernels, and application benchmarks on large-scale symmetric multiprocessing (SMP) systems using a 72 node Sun Fire 15k SMP node. They reported the basic timings, scalability, and run times for different parallel regions.…”

Section: Introductionmentioning

confidence: 99%

Using Parallel Genetic Algorithms for Estimating Model Parameters in Complex Reactive Transport Problems

Torlapati¹,

Clement²

2019

Processes

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In this study, we present the details of an optimization method for parameter estimation of one-dimensional groundwater reactive transport problems using a parallel genetic algorithm (PGA). The performance of the PGA was tested with two problems that had published analytical solutions and two problems with published numerical solutions. The optimization model was provided with the published experimental results and reasonable bounds for the unknown kinetic reaction parameters as inputs. Benchmarking results indicate that the PGA estimated parameters that are close to the published parameters and it also predicted the observed trends well for all four problems. Also, OpenMP FORTRAN parallel constructs were used to demonstrate the speedup of the code on an Intel quad-core desktop computer. The parallel code showed a linear speedup with an increasing number of processors. Furthermore, the performance of the underlying optimization algorithm was tested to evaluate its sensitivity to the various genetic algorithm (GA) parameters, including initial population size, number of generations, and parameter bounds. The PGA used in this study is generic and can be easily scaled to higher-order water quality modeling problems involving real-world applications.

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Section: Introductionmentioning

confidence: 99%

Using Parallel Genetic Algorithms for Estimating Model Parameters in Complex Reactive Transport Problems

Torlapati¹,

Clement²

2019

Processes

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“…OpenMP [16] has emerged as the standard for parallel programming on shared-memory systems. As small to large SMP clusters become more prominent, it is open to debate whether pure message-passing or mixed MPI-OpenMP is the programming of choice for higher performance.…”

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confidence: 99%

Performance evaluation of the Sun Fire Link SMP clusters

Qian

Afsahi

Fredrickson

et al. 2006

IJHPCN

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As symmetric multiprocessors become commonplace, the interconnection networks and the communication system software in clusters of multiprocessors become critical to achieving high performance. Recently, Sun Microsystems has introduced a new system area network, Sun Fire Link interconnect, for its Sun Fire cluster systems. Sun Fire Link is a memory-based interconnect, where Sun MPI uses the Remote Shared Memory (RSM) model for its user-level internode messaging protocol. In this paper, we present the overall architecture of the Sun Fire Link interconnect, explain how communication is done under the RSM, and describe the Sun MPI implementation. We provide an in-depth performance evaluation of the Sun Fire Link interconnect cluster of four Sun Fire 6800s at the RSM layer, MPI microbenchmark layer, and the application layer. Our results include the performance of the Remote Shared Memory API primitives, MPI overhead on top of the RSM, latency and bandwidth under different communication modes, parameters of the LogP model, collective communications, permutation communications, and two applications (Sphot and SMG2000) from the ASCI Purple suite under the MPI, OpenMP, and MPI-OpenMP programming paradigms. Our results indicate that put has a better performance than get on this interconnect. The Sun MPI implementation achieves an off-node latency of up to 5 microseconds. This is comparable to the Quadrics (QsNet II), and Myrinet (E-card), and better than the InfiniBand. The unidirectional and bidirectional bandwidths are 695 MB/s, and 660 MB/s, respectively. The QsNet II, and InfiniBand achieve higher bandwidths. The LogP parameters indicate the network interface is less capable of offloading the host CPU when the message size increases. The performance of our applications under MPI is better than the OpenMP version, and equal or slightly better than the mixedmode. In general, the Sun Fire Link cluster performs relatively well in most cases. I. INTRODUCTION Clusters of Symmetric Multiprocessors (SMP) have been regarded as viable scalable architectures to achieve supercomputing performance and to meet the ever-increasing demand for high-performance computing. There are two main components in such systems: the SMP node, and the communication subsystem including the interconnect, and the communication system software. Considerable work has gone into the design of SMP systems, and several vendors such as IBM, Sun, Compaq, SGI, and HP offer small to large scale shared memory systems. Sun Microsystems has introduced its Sun Fire systems in three categories of small, midsize, and large SMPs, supporting two to 106 processors, backed up with its Sun Fireplane interconnect [1] used inside the Sun UltraSPARC III Cu. The Sun Fireplane interconnect uses one to four levels of interconnect ASICs to provide better sharedmemory performance. All Sun Fire systems use point-to-point signals with a crossbar rather than a data bus. The interconnection network hardware and the communication system software are the keys to the performance of cl...

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Toward Dynamic Load Balancing across OpenMP Thread Teams for Irregular Workloads

Xiao

Hirasawa

Takizawa

et al. 2017

IJNC

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In the field of high performance computing, massively-parallel many-core processors such as Intel Xeon Phi coprocessors are becoming popular because they can significantly accelerate various applications. In order to efficiently parallelize applications for such many-core processors, several high-level programming models have been proposed. The de facto standard programming model mainly for shared-memory parallel processing is OpenMP. For hierarchical parallel processing, OpenMP version 4.0 or later allows programmers to create multiple thread teams. Each thread team contains a bunch of newly-created synchronizable threads. When multiple thread teams are used to execute an application, it is important to have dynamic load balancing across thread teams, since static load balancing easily encounters load imbalance across teams, and thus degrades performance. In this paper, we first motivate our work by clarifying the benefit of using multiple thread teams to execute an irregular workload on a many-core processor. Then, we demonstrate that dynamic load balancing across those thread teams has a potential of significantly improving the performance of irregular workloads on a many-core processor, with considering the scheduling overhead. Although such a dynamic load balancing mechanism has not been provided by the current OpenMP specification, the benefits of dynamic load balancing across thread teams are discussed through experiments using the Intel Xeon Phi coprocessor. We evaluate the performance gain of dynamic load balancing across thread teams using a ray tracing code. The results show that such a dynamic load balancing mechanism can improve the Toward Dynamic Load Balancing across OpenMP Thread Teams for Irregular Workloads performance by up to 14% compared to static load balancing across teams, with considering scheduling overhead.

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Performance characteristics of openMP constructs, and application benchmarks on a large symmetric multiprocessor

Cited by 3 publications

References 0 publications

Using Parallel Genetic Algorithms for Estimating Model Parameters in Complex Reactive Transport Problems

Using Parallel Genetic Algorithms for Estimating Model Parameters in Complex Reactive Transport Problems

Performance evaluation of the Sun Fire Link SMP clusters

Toward Dynamic Load Balancing across OpenMP Thread Teams for Irregular Workloads

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