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Evaluating Performance Portability of SYCL and Kokkos: A Case Study on LBM Simulations 21

Evaluating Performance Portability of SYCL and Kokkos: A Cas...

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21st IEEE international symposium on parallel and distributed Processing with Applications, 13th IEEE international Conference on Big Data and Cloud computing, 16th IEEE international Conference on Social computing and Networking and 13th international Conference on Sustainable computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Ding, Yue Xu, Chuanfu Qiu, Haozhong Wang, Qingsong Dai, Weixi Lin, Yongzhen Che, Yonggang National University of Defense Technology Institute for Quantum Information State Key Laboratory of High Performance Computing Changsha China

ISBN: (纸本)9798350329223

Since modern high performance computing systems are evolving towards diverse and heterogeneous architectures, the emergence of high-level portable programming models leads to a particular focus on performance portability. In this paper, we evaluate the performance portability and explore performance optimization methods for two portable programming models SYCL and Kokkos. We take an open-source multi-phase Lattice Boltzmann Method (LBM) flow simulation code as a case study and implement portable versions with different optimizations. Then we compare our portable implementations with engineer-tuned OpenMP and CUDA versions on Intel CPUs and NVIDIA GPUs. Experimental results show that both SYCL and Kokkos can deliver superior performance than traditional programming models, but the best performance of the portable versions depends heavily on platform-specific optimizations. There is no single implementation that can achieve the best performance on both CPUs and GPUs. Consequently, we conclude that the performance portability still needs to be further improved for both SYCL and Kokkos. In addition, we present a comparative analysis of different optimization methods that qualify the performance enhancement when using SYCL and Kokkos on CPUs and GPUs. Our work offers valuable references for the development of both portable programming models and applications. © 2023 IEEE.

关键词： Program processors

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Large-scale k Edge Server Placement Based on User Clustering and Intelligent Search 21

Large-scale k Edge Server Placement Based on User Clustering...

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作者： Mao, Chengying Hu, Haiquan Jiangxi University of Finance and Economics School of Software and IoT Engineering Nanchang330013 China

ISBN: (纸本)9798350329223

In the field of mobile edge computing, the k Edge Server Placement (kESP) problem has attracted extensive attention. However, existing studies have mainly focused on solving small-scale problems, and the large-scale scenarios need to be explored. Based on this observation, this paper attempts to develop a cost-effective solution for the large-scale kESP problem. The proposed algorithm named UCIS-kESP realizes the selection of a small subset from a large collection of base stations by clustering mobile users, thereby significantly reducing the search cost of the kESP problem. Subsequently, an intelligent search based on genetic algorithm is applied to find the 'optimal' deployment of k edge servers from the candidate subset. The experimental analysis conducted on a public dataset demonstrates that our proposed UCIS-kESP algorithm obtains better deployment solutions than the state-of-the-art algorithms, while also exhibiting fast and stable solving efficiency. On average, our algorithm can save about 40% of the computational time. Even as the size of the kESP problem increases, the computational overhead of the UCIS-kESP algorithm grows relatively slowly. © 2023 IEEE.

关键词： Mobile edge computing

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Coverage Probability of distributed CoMP UAV-Assisted Cellular Networks 22

Coverage Probability of Distributed CoMP UAV-Assisted Cellul...

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22nd IEEE international symposium on parallel and distributed Processing with Applications, ISPA 2024

作者： Li, Yan Long, Qingmin Tang, Qiang He, Shiming Xiong, Bing Changsha University of Science and Technology School of Computer and Communication Engineering Changsha410004 China National University of Defense Technology Science and Technology on Information System Engineering Laboratory Changsha410073 China

ISBN: (纸本)9798331509712

It is well-established that terrestrial communication systems may fail during emergencies such as earthquakes, tsunamis, and floods. Fortunately, with the rapid advancement of unmanned aerial vehicle (UAV) network technology, deploying UAV nodes as aerial base stations (BSs) is assuming an increasingly crucial role in facilitating downlink transmissions and restoring ground communication capabilities. However, a single UAV node is not sufficient to meet the requirements. Inspired by distributed communication, we introduce a performance analysis framework based on stochastic geometry to analyze the distributed coordinated multi-point (CoMP) UAV-assisted communication network. Specifically, we assume that all UAV nodes follow a homogeneous Poisson point process (PPP) and maintain a constant altitude. The entire space is tessellated by multiple hexagons, with multiple UAV nodes within each hexagonal region working together to serve terrestrial user equipments (UEs). For this region-centric cooperative model, we derive an exact expression for the coverage probability to quantify the performance improvement enabled by UAVs, analyze the upper bound of the coverage probability, and provide a simplified approximation. We then compare this model to a user-centric model. Our numerical findings demonstrate that the cooperation of UAV nodes can significantly enhance the coverage probability and save spectrum resources. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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distributed Energy Management for Carbon Neutral Data Centers 22

Distributed Energy Management for Carbon Neutral Data Center...

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22nd IEEE international symposium on parallel and distributed Processing with Applications, ISPA 2024

作者： Liu, Chuyi Wan, Jianxiong Li, Leixiao Ren, Guanyu Wang, Xiaolei Inner Mongolia University of Technology Huhhot China Inner Mongolia Autonomous Region Engineering Technology Research Center of Big Data Based Software Service Huhhot China Research Center of Large-Scale Energy Storage Technologies Huhhot China

ISBN: (纸本)9798331509712

With the continuous expansion of data centers, their carbon emission becomes a serious issue. A number of studies are committing to reduce the carbon emission of data centers. Carbon trading is a promising emission reduction technique which is, however, seldom applied to data centers. To bridge this gap, we propose a carbon-neutral architecture DC2 for distributed data centers, where each data center consists of three subsystems, i.e., energy subsystem for energy supply, thermal subsystem for data center cooling and the carbon subsystem for carbon trading. Then, we formulate the energy management problem as a Decentralized Partially Observable Markov Decision Processe (Dec-POMDP) and develop a distributed solution framework using Multi-Agent Deep Deterministic Policy Gradient (MAD-DPG). Finally, simulations on real-world data shows that the DC2 provides a cost saving of 8.16%, and applying MADDPG saves 10.04% of the overall cost compared to Independent MADDPG. © 2024 IEEE.

关键词： Carbon sequestration

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A scalable adaptive-matrix SPMV for heterogeneous architectures 36

A scalable adaptive-matrix SPMV for heterogeneous architectu...

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36th IEEE international parallel and distributed Processing symposium (IEEE IPDPS)

作者： Tran, Han D. Fernando, Milinda Saurabh, Kumar Ganapathysubramanian, Baskar Kirby, Robert M. Sundar, Hari Univ Utah Salt Lake City UT 84112 USA Univ Texas Austin Austin TX 78712 USA Iowa State Univ Ames IA 50011 USA

ISBN: (纸本)9781665481069

In most computational codes, the core computational kernel is the Sparse Matrix-Vector product (SPMV) that enables specialized linear algebra libraries like PETSc to be used, especially in the distributed memory setting. However, optimizing SPMV performance and scalability at all levels of a modern heterogeneous architecture can be challenging as it is characterized by irregular memory access. This work presents a hybrid approach (HYMV) for evaluating SPMV for matrices arising from PDE discretization schemes such as the finite element method (FEM). The approach enables localized structured memory access that provides improved performance and scalability. Additionally, it simplifies the programmability and portability on different architectures. The developed HYMV approach enables efficient parallelization using MPI, SIMD, OpenMP, and CUDA with minimum programming effort. We present a detailed comparison of HYMV with the two traditional approaches in computational code, matrix-assembled and matrix-free approaches, for structured and unstructured meshes. Our results demonstrate that the HYMV approach achieves excellent scalability and outperforms both approaches, e.g., achieving average speedups of 11x for matrix setup, 1.7x for SPMV with structured meshes, 3.6x for SPMV with unstructured meshes, and 7.5x for GPU SPMV.

关键词： adaptive-matrix matrix-assembled matrix-free element-by-element FEM parallel computing heterogeneous architectures

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Mixed Precision s-step Conjugate Gradient with Residual Replacement on GPUs 36

Mixed Precision s-step Conjugate Gradient with Residual Repl...

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36th IEEE international parallel and distributed Processing symposium (IEEE IPDPS)

作者： Yamazaki, Ichitaro Carson, Erin Kelley, Brian Sandia Natl Labs POB 5800 Albuquerque NM 87185 USA Charles Univ Prague Fac Math & Phys Prague Czech Republic

ISBN: (纸本)9781665481069

The s-step Conjugate Gradient (CG) algorithm has the potential to reduce the communication cost of standard CG by a factor of s. However, though mathematically equivalent, s-step CG may be numerically less stable compared to standard CG in finite precision, exhibiting slower convergence and decreased attainable accuracy. This limits the use of s-step CG in practice. To improve the numerical behavior of s-step CG and overcome this potential limitation, we incorporate two techniques. First, we improve convergence behavior through the use of higher precision at critical parts of the s-step iteration and second, we integrate a residual replacement strategy into the resulting mixed precision s-step CG to improve attainable accuracy. Our experimental results on the Summit Supercomputer demonstrate that when the higher precision is implemented in hardware, these techniques have virtually no overhead on the iteration time while improving both the convergence rate and the attainable accuracy of s-step CG. Even when the higher precision is implemented in software, these techniques may still reduce the time-to-solution (speedups of up to 1.8x in our experiments), especially when s-step CG suffers from numerical instability with a small step size and the latency cost becomes a significant part of its iteration time.

关键词： distributed processing Costs Supercomputers Software Hardware Behavioral sciences Numerical stability

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HiPS2022: The 2nd Workshop on High Performance Serverless computing 22

HiPS2022: The 2nd Workshop on High Performance Serverless Co...

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31st international symposium on High-Performance parallel and distributed computing (HPDC)

作者： Babuji, Yadu Chard, Kyle Foster, Ian Li, Zhuozhao Argonne Natl Lab Argonne IL 60439 USA Southern Univ Sci & Technol Shenzhen Peoples R China

ISBN: (纸本)9781450391993

Serverless computing presents an attractive model for general distributed computing as it focuses on abstracting the infrastructure required to execute an application. This workshop investigates the intersection between high performance computing and serverless computing, looking both at the high performance and distributed systems used to deliver serverless platforms and also at the use of serverless models for high performance and distributed systems.

关键词： Cloud computing Serverless distributed Systems

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Graph-based Multi-view Clustering for Web services 21

Graph-based Multi-view Clustering for Web services

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作者： Yang, Wang Zhenzhen, Yuan Guosheng, Kang Buqing, Cao Jianxun, Liu Yong, Xiao Hnust Xiangtan China Hunan University of Science and Technology Hunan Provincial Key Lab. for Services Computing and Novel Software Technology Xiangtan China School of Computer Science and Engineering China

ISBN: (纸本)9798350329223

The number of Web services on the Internet has been steadily increasing in recent years due to their growing popularity. Under the big data environment, how to effectively manage Web services is of significance for service discovery, service recommendation, etc. It is widely studied that Web services clustering is an effective way for service management. However, most of the current Web service clustering only extracts the information of Web services for clustering from one view, such as Web service content descriptions, networks in which Web services participate, and so on. Extracting information from Web services only unilaterally will not be able to provide a three-dimensional and comprehensive description of Web services, which may diminish the effect of Web service clustering. In addition, some Web service resources will be wasted if other information of Web services is not used at the same time. We find that multi-view clustering can simultaneously consider multiple information of a data at the same time, and multiple information can complement and enhance each other according to the characteristics of multiview clustering. Therefore, in this paper, we apply Web services to graph-based multi-view clustering in multi-view clustering to improve the performance of Web service clustering by simultaneously considering multiple feature information about Web services and distributing different weights to different information in the clustering process. © 2023 IEEE.

关键词： Web services

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FlashWalker: An In-Storage Accelerator for Graph Random Walks 36

FlashWalker: An In-Storage Accelerator for Graph Random Walk...

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36th IEEE international parallel and distributed Processing symposium (IEEE IPDPS)

作者： Niu, Fuping Yue, Jianhui Shen, Jiangqiu Liao, Xiaofei Liu, Haikun Jin, Hai Huazhong Univ Sci & Technol Natl Engn Res Ctr Big Data Technol & Syst Sch Comp Sci & Technol Serv Comp Technol & Syst LabCluster & Grid Comp Wuhan 430074 Peoples R China Michigan Technol Univ Dept Comp Sci Houghton MI 49931 USA

ISBN: (纸本)9781665481069

Graph random walk is widely used in the graph processing as it is a fundamental component in graph analysis, ranging from vertices ranking to the graph embedding. Different from traditional graph processing workload, random walk features massive processing parallelisms and poor graph data reuse, being limited by low I/O efficiency. Prior designs for random walk mitigate slow I/O operations. However, the state-of-the-art random walk processing systems are bounded by slow disk I/O bandwidth, which is confirmed by our experiments with real-world graphs. To address this issue, we propose FlashWalker, an in-storage accelerator for random walk that moves walk updating close to graph data stored in flash memory, by exploiting significant parallelisms inside SSD. Featuring a heterogeneous and parallel processing system, FlashWalker includes a board-level accelerator, channel-level accelerators, and chip-level accelerators. To address challenges posed by the tight resource constraints for processing large-scale graphs, we propose novel designs: storing a few popular subgraphs in accelerators, the pre-walking for dense walks, two optimizations to search the subgraph mapping table, and a subgraph scheduling algorithm. We implement FlashWalker in RTL, showing small circuit area overhead. Our evaluation shows FlashWalker reduces the execution time of random walk algorithms by up to 660.50x, compared with GraphWalker, which is the state-of-the-art system for random walk algorithms.

关键词： random walk graph computing in-storage processing accelerator

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HPPython: Extending Python with HPspmd for Data parallel Programming 2

HPPython: Extending Python with HPspmd for Data Parallel Pro...

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2nd international symposium on computing and Artificial Intelligence, ISCAI 2023

作者： Nava, Judah Josiah Lee, Jaden Jinu Lee, Hanku Computer Science and Information Systems Department University Moorhead MN United States

ISBN: (纸本)9798400708954

In light of previous endeavors and trends in the realm of parallel programming, HPPython emerges as an essential superset that enhances the accessibility of parallel programming for developers, facilitating scalability across multiple nodes. Despite Python's popularity as a programming language in scientific and engineering applications and its native support for executing various processes, HPPython brings substantial simplification to the development of parallel programs and empowers program distribution across heterogeneous clusters consisting of multiple physical computers. HPPython leverages the MPI standard for its underlying communication, thereby harnessing the benefits of the SPMD model. Additionally, HPPython introduces novel syntax and constructs, such as parallel loops and distributed lists, while endeavoring to retain the natural essence of the original language. This paper delves into the distinct components of HPPython and elucidates their integration, establishing HPPython as a viable solution for parallel programming in today's data-driven world. © 2023 ACM.

关键词： parallel programming

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