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INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS 2009年第4期23卷 337-339页

作者： Lusk, Ewing Argonne Natl Lab Div Math & Comp Sci Argonne IL 60439 USA

One question before the high-performance computing community is "How will application developers write code for exascale machines?" At this point it looks like they might be riding a rough beast indeed. This paper is a brief assessment of where we stand now with respect to writing programs for our largest supercomputers and what we should do next. MPI is likely to remain a critical part of the programming infrastructure as we move towards exascale, but more is needed, in particular a robust, portable, and effective standard for parallel programming within a single address space, perhaps for heterogeneous processors. Formal methods provide the only truly scalable approach to developing correct code in this complex programming environment.

关键词： programming models exascale computing OpenMP MPI hybrid programming

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Parallel spherical harmonic transforms on heterogeneous architectures ( graphics processing units/multi-core CPUs)

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2014年第3期26卷 683-711页

作者： Szydlarski, Mikolaj Esterie, Pierre Falcou, Joel Grigori, Laura Stompor, Radek INRIA Saclay Ile de France F-91893 Orsay France Univ Paris 11 F-91405 Orsay France INRIA Rocquencourt F-78153 Le Chesnay France Univ Paris 06 CNRS UMR 7598 Lab Jacques Louis Lions F-75005 Paris France Univ Paris Diderot Obs Paris CNRS IN2P3 CEA IrfuAPCSorbonne Paris Cite Paris France

Spherical harmonic transforms (SHT) are at the heart of many scientific and practical applications ranging from climate modelling to cosmological observations. In many of these areas, new cutting-edge science goals have been recently proposed requiring simulations and analyses of experimental or observational data at very high resolutions and of unprecedented volumes. Both these aspects pose formidable challenge for the currently existing implementations of the transforms. This paper describes parallel algorithms for computing SHT with two variants of intra-node parallelism appropriate for novel supercomputer architectures, multi-core processors and Graphic Processing Units (GPU). It also discusses their performance, alone and embedded within a top-level, Message Passing Interface-based parallelisation layer ported from the S(2)HAT library, in terms of their accuracy, overall efficiency and scalability. We show that our inverse SHT run on GeForce 400 Series GPUs equipped with latest Compute Unified Device Architecture architecture (Fermi) outperforms the state of the art implementation for a multi-core processor executed on a current Intel Core i7-2600K. Furthermore, we show that an Message Passing Interface/Compute Unified Device Architecture version of the inverse transform run on a cluster of 128 Nvidia Tesla S1070 is as much as 3times faster than the hybrid Message Passing Interface/OpenMP version executed on the same number of quad-core processors Intel Nehalem for problem sizes motivated by our target applications. Performance of the direct transforms is however found to be at the best comparable in these cases. We discuss in detail the algorithmic solutions devised for the major steps involved in the transforms calculation, emphasising those with a major impact on their overall performance and elucidates the sources of the dichotomy between the direct and the inverse *** (c) 2013 John Wiley & Sons, Ltd.

关键词： spherical harmonic transforms hybrid architectures hybrid programming CUDA multi-GPU CMB

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A hybrid parallel Delaunay image-to-mesh conversion algorithm scalable on distributed-memory clusters

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COMPUTER-AIDED DESIGN 2018年 103卷 34-46页

作者： Feng, Daming Chernikov, Andrey N. Chrisochoides, Nikos P. Old Dominion Univ Dept Comp Sci Norfolk VA 23529 USA

In this paper, we present a scalable three dimensional parallel Delaunay image-to-mesh conversion algorithm. A nested master worker model is used to simultaneously explore process- and thread-level parallelization. The mesh generation includes two stages: coarse and fine meshing. First, a coarse mesh is constructed in parallel by the threads of the master process. Then the coarse mesh is partitioned. Finally, the fine mesh refinement procedure is executed until all the elements in the mesh satisfy the quality and fidelity criteria. The communication and computation are separated during the fine mesh refinement procedure. The master thread of each process that initializes the MPI environment is in charge of the inter-node MPI communication for data (submesh) movement while the worker threads of each process are responsible for the local mesh refinement within the node. We conducted a set of experiments to test the performance of the algorithm on distributed memory clusters and observed that the granularity of coarse level data decomposition, which affects the coarse level concurrency, has a significant influence on the performance of the algorithm. With the proper value of granularity, the algorithm is scalable to 45 distributed memory compute nodes (900 cores). (C) 2017 Elsevier Ltd. All rights reserved.

关键词： hybrid programming Parallel mesh generation Image-to-mesh conversion Two-level parallelization

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Performance metrics in a hybrid MPI-OpenMP based molecular dynamics simulation with short-range interactions

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JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING 2014年第3期74卷 2203-2214页

作者： Pal, Anirban Agarwala, Abhishek Raha, Spumyendu Bhattacharya, Baidurya Rensselaer Polytech Inst Dept Mech Aerosp & Nucl Engn Troy NY 12180 USA Archayne Labs Gurgaon 122001 Haryana India Indian Inst Sci Supercomp Educ & Res Ctr Bangalore 560012 Karnataka India Indian Inst Technol Dept Civil Engn Kharagpur 721302 WB India

We discuss the computational bottlenecks in molecular dynamics (MD) and describe the challenges in parallelizing the computation-intensive tasks. We present a hybrid algorithm using MPI (Message Passing Interface) with OpenMP threads for parallelizing a generalized MD computation scheme for systems with short range interatomic interactions. The algorithm is discussed in the context of nano-indentation of Chromium films with carbon indenters using the Embedded Atom Method potential for Cr-Cr interaction and the Morse potential for Cr-C interactions. We study the performance of our algorithm for a range of MPI-thread combinations and find the performance to depend strongly on the computational task and load sharing in the multi-core processor. The algorithm scaled poorly with MPI and our hybrid schemes were observed to outperform the pure message passing scheme, despite utilizing the same number of processors or cores in the cluster. Speed-up achieved by our algorithm compared favorably with that achieved by standard MD packages. (C) 2013 Elsevier Inc. All rights reserved.

关键词： hybrid programming Molecular dynamics Message passing OpenMP threading Parallel computing

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Integrating software and hardware hierarchies in an autotuning method for parallel routines in heterogeneous clusters

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JOURNAL OF SUPERCOMPUTING 2020年第12期76卷 9922-9941页

作者： Camara, Jesus Cuenca, Javier Gimenez, Domingo Univ Murcia Dept Engn & Technol Comp Murcia Spain Univ Murcia Dept Comp & Syst Murcia Spain

A hierarchical approach for autotuning linear algebra routines on heterogeneous platforms is presented. Hierarchy helps to alleviate the difficulties of tuning parallel routines for high-performance computing systems. This paper analyzes the application of the hierarchical approach at both the hardware and software levels, using the basic matrix multiplication and the Strassen multiplication as proof of concept on multicore+coprocessor nodes. In this way, the hierarchical approach allows partial delegation of the efficient exploitation of the computing units in the node to the underlying direct autotuned matrix multiplication used in the base case.

关键词： Autotuning hybrid programming Heterogeneous computing Multicore Manycore

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Efficient parallelization of a regional ocean model for the western Mediterranean Sea

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INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS 2014年第3期28卷 368-383页

作者： Luisa Cordoba, M. Garcia Dopico, Antonio Isabel Garcia, M. Rosales, Francisco Arnaiz, Jesus Bermejo, Rodolfo Galan del Sastre, Pedro Univ Politecn Madrid Dept Comp Syst Architecture & Technol E-28040 Madrid Spain Univ Politecn Madrid E-28040 Madrid Spain Univ Politecn Madrid Appl Math ETSII E-28040 Madrid Spain

This paper focuses on the parallelization of an ocean model applying current multicore processor-based cluster architectures to an irregular computational mesh. The aim is to maximize the efficiency of the computational resources used. To make the best use of the resources offered by these architectures, this parallelization has been addressed at all the hardware levels of modern supercomputers: firstly, exploiting the internal parallelism of the CPU through vectorization;secondly, taking advantage of the multiple cores of each node using OpenMP;and finally, using the cluster nodes to distribute the computational mesh, using MPI for communication within the nodes. The speedup obtained with each parallelization technique as well as the combined overall speedup have been measured for the western Mediterranean Sea for different cluster configurations, achieving a speedup factor of 73.3 using 256 processors. The results also show the efficiency achieved in the different cluster nodes and the advantages obtained by combining OpenMP and MPI versus using only OpenMP or MPI. Finally, the scalability of the model has been analysed by examining computation and communication times as well as the communication and synchronization overhead due to parallelization.

关键词： Message passing shared memory hybrid programming multicore clusters ocean model finite element method

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Performance characteristics of the multi-zone NAS parallel benchmarks

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JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING 2006年第5期66卷 674-685页

作者： Jin, HQ Van der Wijngaart, RF NASA Ames Res Ctr NASA Adv Supercomp Div Moffett Field CA 94035 USA

We describe a new suite of computational benchmarks that models applications featuring multiple levels of parallelism. Such parallelism is often available in realistic flow computations on systems of meshes, but had not previously been captured in benchmarks. The new suite, named NPB (NAS parallel benchmarks) multi-zone, is derived from the NPB suite, and involves solving the application benchmarks LU, BT and SP on collections of loosely coupled discretization meshes. The solutions on the meshes are updated independently. but after each time step they exchange boundary value information. This strategy provides relatively easily exploitable coarse-grain parallelism between meshes. Three reference implementations are available: one serial, one hybrid using the message passing interface (MPI) and OpenMP, and another hybrid using a shared memory multi-level programming model (SMP+OpenMP). We examine the effectiveness of hybrid parallelization paradigms in these implementations on four different parallel computers. We also use an empirical formula to investigate the performance characteristics of the hybrid parallel codes. (c) 2005 Elsevier Inc. All rights reserved.

关键词： multi-zone parallel benchmarks parallel computers hybrid programming performance model

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High resolution aerospace applications using the NASA Columbia supercomputer

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INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS 2007年第1期21卷 106-126页

作者： Mavriplis, Dimitri J. Aftosmis, Michael J. Berger, Marsha Univ Wyoming Dept Mech Engn Laramie WY 82071 USA NASA Adv Supercomp Div Ames Res Ctr Moffett Field CA 94035 USA NYU Courant Inst Dept Comp Sci New York NY 10012 USA

This paper focuses on the parallel performance of two high-performance aerodynamic simulation packages on the newly installed NASA Columbia supercomputer. These packages include both a high-fidelity, unstructured, Reynolds-averaged Navier-Stokes solver, and a fully-automated inviscid flow package for cut-cell Cartesian grids. The complementary combination of these two simulation codes enables high-fidelity characterization of aerospace vehicle design performance over the entire flight envelope through extensive parametric analysis and detailed simulation of critical regions of the flight envelope. Both packages are industrial-level codes designed for complex geometry and incorporate customized multigrid solution algorithms. The performance of these codes on Columbia is examined using both MPI and OpenMP and using both the NUMAlink and InfiniBand interconnect fabrics. Numerical results demonstrate good scalability on up to 2016 CPUs using the NUMAlink4 interconnect, with measured computational rates in the vicinity of 3 TFLOP/s, while InfiniBand showed some performance degradation at high CPU counts, particularly with multigrid. Nonetheless, the results are encouraging enough to indicate that larger test cases using combined MPI/OpenMP communication should scale well on even more processors.

关键词： NASA Columbia SGI Altix scalability hybrid programming unstructured computational fluid dynamics OpenMP

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Analysis and optimization of gyrokinetic toroidal simulations on homogenous and heterogenous platforms

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INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS 2013年第4期27卷 454-473页

作者： Ibrahim, Khaled Z. Madduri, Kamesh Williams, Samuel Wang, Bei Ethier, Stephane Oliker, Leonid Univ Calif Berkeley Lawrence Berkeley Natl Lab High Performance Computat Res Div Berkeley CA 94720 USA Univ Calif Berkeley Lawrence Berkeley Natl Lab Future Technol Grp Berkeley CA 94720 USA Penn State Univ Comp Sci & Engn Dept University Pk PA 16802 USA Princeton Univ Princeton Inst Computat Sci & Engn Princeton NJ 08544 USA

The Gyrokinetic Toroidal Code (GTC) uses the particle-in-cell method to efficiently simulate plasma microturbulence. This work presents novel analysis and optimization techniques to enhance the performance of GTC on large-scale machines. We introduce cell access analysis to better manage locality vs. synchronization tradeoffs on CPU and GPU-based architectures. Our optimized hybrid parallel implementation of GTC uses MPI, OpenMP, and NVIDIA CUDA, achieves up to a 2x speedup over the reference Fortran version on multiple parallel systems, and scales efficiently to tens of thousands of cores.

关键词： Particle-in-cell hybrid programming memory-centric multi-core tuning multi-core optimization GPU programming

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A Low Power Consuming Model of Parallel programming for HPC System

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2019年第5期10卷 172-177页

作者： Aftouri, Mohammed Nawaf Algarni, Abdullah M. KAU Dept Comp Sci POB 80221 Jeddah 21589 Saudi Arabia

For most of the past five decades, the growing computational power of supercomputers has come primarily from a doubling of clock frequency every 18 months. Over this time period, the clock rate increased by six orders of magnitude, while the number of processors increased by three orders of magnitude. The major challenge caused by the increasing scale and complexity of HPC systems is the massive power consumption. Due to constraints on heat and the power requirements of today's microprocessors, vendors have shifted to putting multiple processors (cores) on a chip. The number of cores per chip is expected to continue increasing exponentially over the next decade. One expected strategy is the correct usage of parallel programming models that decrease power consumption and increase system performance through massive parallelism (concurrency). In the current study, we have proposed a hybrid MVAPICH-2 + CUDA (HMC) parallel programming model that outperformed other state-of-the-art dual and tri hierarchy level approaches with respect to power consumption and execution time. Moreover, the HMC model was evaluated by implementing the matrix multiplication benchmarking application. Consequently, it can be considered a leading model for the emerging Exascale computing system.

关键词： HPC parallel computation power consumption hybrid programming MVAPIC2 CUDA

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