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检索条件"任意字段=Proceedings of the ACM Symposium on Principles of Distributed Computing"

共 4473 条记录，以下是171-180 订阅

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distributed-Memory Randomized Algorithms for Sparse Tensor CP Decomposition 24

Distributed-Memory Randomized Algorithms for Sparse Tensor C...

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36th acm symposium on Parallelism in Algorithms and Architectures (SPAA)

作者： Bharadwaj, Vivek Malik, Osman Asif Murray, Riley Buluc, Aydin Demmel, James Univ Calif Berkeley Berkeley CA 94720 USA Encube Technol Stockholm Sweden Sandia Natl Labs POB 5800 Albuquerque NM 87185 USA Lawrence Berkeley Natl Lab Berkeley CA 94720 USA

ISBN: (纸本)9798400704161

Candecomp / PARAFAC (CP) decomposition, a generalization of the matrix singular value decomposition to higher-dimensional tensors, is a popular tool for analyzing multidimensional sparse data. On tensors with billions of nonzero entries, computing a CP decomposition is a computationally intensive task. We propose the first distributed-memory implementations of two randomized CP decomposition algorithms, CP-ARLS-LEV and STS-CP, that offer nearly an order-of-magnitude speedup at high decomposition ranks over well-tuned non-randomized decomposition packages. Both algorithms rely on leverage score sampling and enjoy strong theoretical guarantees, each with varying time and accuracy tradeoffs. We tailor the communication schedule for our random sampling algorithms, eliminating expensive reduction collectives and forcing communication costs to scale with the random sample count. Finally, we optimize the local storage format for our methods, switching between analogues of compressed sparse column and compressed sparse row formats. Experiments show that our methods are fast and scalable, producing 11x speedup over SPLATT by decomposing the billion-scale Reddit tensor on 512 CPU cores in under two minutes.

关键词： Sparse Tensors CP Decomposition Randomized Linear Algebra Leverage Score Sampling

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Brief Announcement: distributed MST Computation in the Sleeping Model: Awake-Optimal Algorithms and Lower Bounds 22

Brief Announcement: Distributed MST Computation in the Sleep...

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acm symposium on principles of distributed computing (PODC)

作者： Augustine, John Moses, William K., Jr. Pandurangan, Gopal Indian Inst Technol Madras Chennai India Univ Houston Houston TX USA

ISBN: (纸本)9781450392624

We study the distributed minimum spanning tree (MST) problem, a fundamental problem in distributed computing. It is well-known that distributed MST can be solved in (O) over tilde (D + root n) rounds in the standard CONGEST model (where n is the network size and D is the network diameter) and this is essentially the best possible round complexity (up to logarithmic factors). However, in resource-constrained networks such as wireless ad hoc and sensor networks, nodes spending so much time can lead to significant spending of resources such as energy. Motivated by the above consideration, we study distributed algorithms for MST under the sleeping model [Chatterjee et al., PODC 2020], a model for design and analysis of resource-efficient distributed algorithms. In the sleeping model, a node can be in one of two modes in any round - sleeping or awake (unlike the traditional model where nodes are always awake). Only the rounds in which a node is awake are counted, while sleeping rounds are ignored. A node spends resources only in the awake rounds and hence the main goal is to minimize the awake complexity of a distributed algorithm, the worst-case number of rounds any node is awake. We present distributed MST algorithms that have optimal awake complexity with a matching lower bound. We also show that our awake-optimal algorithms have essentially the best possible round complexity by presenting a lower bound on the product of the awake and round complexity of any distributed algorithm (including randomized).

关键词： Minimum Spanning Tree Sleeping model energy-efficient awake complexity round complexity trade-offs

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MYRTUS: Multi-layer 360° dYnamic orchestration and interopeRable design environmenT for compute-continUum Systems Invited Paper 21

MYRTUS: Multi-layer 360° dYnamic orchestration and interope...

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21st acm International Conference on computing Frontiers (CF)

作者： Palumbo, Francesca Zedda, Maria Katiuscia Fanni, Tiziana Bagnato, Alessandra Castello, Luca Castrillon, Jeronimo Del Ponte, Roberto Deng, Yansha Driessen, Bart Fadda, Mauro du Fretay, Tristan Halna de Oliveira Filho, Julio Rao, Veena Regazzoni, Francesco Rodriguez, Alfonso Schranz, Melanie Sedda, Giulia Abinsula Srl Turin Italy Univ Cagliari Cagliari Italy Univ Sassari Sassari Italy Softeam Guyancourt France Tech Univ Dresden Dresden Germany TNO The Hague Netherlands Lakeside Labs Reidsville NC USA Univ Politecn Madrid Madrid Spain Hiro Microdatactr Heerlen Netherlands Kings Coll London London England Forge Reply Srl Turin Italy ArubaKube Srl Turin Italy Canon Res Ctr France Cesson Sevigne France Univ Amsterdam Amsterdam Netherlands Univ Svizzera Italiana Lugano Switzerland

The MYRTUS Horizon Europe Project embraces the principles of the EUCloudEdgeIOT Initiative and integrates edge, fog and cloud computing platforms, leveraging a cognitive engine based on swarm intelligence and federate... 详细信息

ISBN: (纸本)9798400704925

关键词： Computer hardware and architecture Design environment Dynamic orchestration computing continuum Interoperability AI

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NSF/IEEE-TCPP Curriculum on Parallel and distributed computing for Undergraduates - Version II - Big Data, Energy, and distributed computing 2023

NSF/IEEE-TCPP Curriculum on Parallel and Distributed Computi...

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54th Annual acm SIGCSE Technical symposium on Computer Science Education (SIGCSE TS)

作者： Prasad, Sushil Weems, Charles Sussman, Alan Gupta, Anshul Estrada, Trilce Vaidyanathan, Ramachandran Ghafoor, Sheikh Kant, Krishna Stunkel, Craig Univ Texas San Antonio San Antonio TX 78249 USA Univ Massachusetts Amherst MA 01003 USA Univ Maryland College Pk MD 20742 USA IBM Res Yorktown Hts NY USA Univ New Mexico Albuquerque NM 87131 USA Louisiana State Univ Baton Rouge LA 70803 USA Tennessee Technol Univ Cookeville TN USA Temple Univ Philadelphia PA 19122 USA NVIDIA St Louis MO USA

ISBN: (纸本)9781450394338

This special session will report on the updated NSF/IEEE-TCPP Curriculum on Parallel and distributed computing released in Nov 2020 by the Center for Parallel and distributed computing Curriculum Development and Educational Resources (CDER). The purpose of the special session is to obtain SIGCSE community feedback on this curriculum in a highly interactive manner employing the hybrid modality and supported by a full-time CDER booth for the duration of SIGCSE. In this era of big data, cloud, and multi- and many-core systems, it is essential that the computer science (CS) and computer engineering (CE) graduates have basic skills in parallel and distributed computing (PDC). The topics are primarily organized into the areas of architecture, programming, and algorithms topics. A set of pervasive concepts that percolate across area boundaries are also identified. Version 1 of this curriculum was released in December 2012. That curriculum guideline has over 140 early adopter institutions worldwide and has been incorporated into the 2013 acm/IEEE Computer Science curricula. This Version-II represents a major revision. The updates have focused on enhancing coverage related to the topical aspects of Big Data, Energy, and distributed computing. The session will also report on related CDER activities including a workshop series on a PDC institute conceptualization, developing a CE-oriented version of the curriculum, and identifying a minimal set of PDC topics aligned with ABET's exposure-level PDC requirements. The interested SIGCSE audience includes educators, authors, publishers, curriculum committee members, department chairs and administrators, professional societies, and the computing industry.

关键词： Education Undergraduate Curriculum Parallel and distributed computing Bloom's Classification Learning Outcomes

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SoCC 2023 - proceedings of the 2023 acm symposium on Cloud computing

SoCC 2023 - Proceedings of the 2023 ACM Symposium on Cloud C...

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14th acm symposium on Cloud computing, SoCC 2023

ISBN: (纸本)9798400703874

The proceedings contain 40 papers. The topics discussed include: Plexus: optimizing join approximation for geo-distributed data analytics;carbon containers: a system-level facility for managing application-level carbon emissions;Golgi: performance-aware, resource-efficient function scheduling for serverless computing;oblivious Paxos: privacy-preserving consensus over secret-shares;not all resources are visible: exploiting fragmented shadow resources in shared-state scheduler architecture;dissecting overheads of service mesh sidecars;OneAdapt: fast adaptation for deep learning applications via backpropagation;multivariate anomaly detection with domain clustering;a comparison of end-to-end decision forest inference pipelines;and maximizing the utilization of GPUs used by cloud gaming through adaptive co-location with combo.

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Extreme-scale Direct Numerical Simulation of Incompressible Turbulence on the Heterogeneous Many-core System 24

Extreme-scale Direct Numerical Simulation of Incompressible ...

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29th acm SIGPLAN Annual symposium on principles and Practice of Parallel Programming (PPoPP)

作者： Xie, Jiabin Feng, Guangnan Huang, Han Feng, Junxuan Chen, Zhiguang Lu, Yutong Sun Yat Sen Univ Guangzhou Peoples R China

ISBN: (纸本)9798400704352

Direct numerical simulation (DNS) is a technique that directly solves the fluid Navier-Stokes equations with high spatial and temporal resolutions, which has driven much research regarding the nature of turbulence. For high-Reynolds number (Re) incompressible turbulence of particular interest, where the nondimensional Re characterizes the flow regime, the application of DNS is hindered by the fact that the numerical grid size (i.e., the memory requirement) scales with Re-3, while the overall computational cost scales with Re-4. Recent studies have shown that developing efficient parallel methods for heterogeneous many-core systems is promising to solve this computational challenge. We develop PowerLLEL++, a high-performance and scalable implicit finite difference solver for heterogeneous manycore systems, to accelerate the extreme-scale DNS of incompressible turbulence. To achieve this goal, an adaptive multi-level parallelization strategy is first proposed to fully exploit the multi-level parallelism and computing power of heterogeneous many-core systems. Second, hierarchicalmemory-adapted data reuse/tiling strategy and kernel fusion are adopted to improve the performance of memory-bound stencil-like operations. Third, a parallel tridiagonal solver based on the parallel diagonal dominant (PDD) algorithm is developed to minimize the number of global data transposes. Fourth, three effective communication optimizations are implemented by Remote Direct Memory Access (RDMA) to maximize the performance of the remaining global transposes and halo exchange. Results show that the solver exploits the heterogeneous computing power of the new Tianhe supercomputer and achieves a speedup of up to 10.6x (against the CPU-only performance). Linear strong scaling is obtained with a grid size of up to 25.8 billion.

关键词： incompressible turbulence direct numerical simulation heterogeneous many-core high performance computing

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Devastator: A Scalable Parallel Discrete Event Simulation Framework for Modern C plus 38

Devastator: A Scalable Parallel Discrete Event Simulation Fr...

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38th acm SIGSIM International Conference on principles of Advanced Discrete Simulation (acm SIGSIM PADS)

作者： Bachan, John Nguyen, Tan Natarajan, Mahesh Bremer, Maximilian Chan, Cy Jiang, Xuan Ye, Jianlan Lawrence Berkeley Natl Lab Berkeley CA USA Univ Calif Berkeley Berkeley CA USA Arizona State Univ Tempe AZ USA

ISBN: (纸本)9798400703638

Parallel discrete event simulation is a fundamental simulation technology that is essential to the parallelization of event-based models including hardware and transportation systems. Parallelization is often difficult due to dynamic data-dependencies and limited computational work for hiding runtime overheads. We present Devastator, a scalable parallel discrete event simulation framework for modern C++. Devastator provides a productive API that leverages C++'s type system to eliminate boilerplate code. Devastator has been designed to specifically optimize performance on distributed many-core architectures with deepening memory hierarchies. Devastator relies on the GASNet-Ex communication runtime as well as lock-free message queues to achieve highly competitive performance. We perform strong and weak scaling studies on NERSC's Perlmutter up to 32,698 cores and demonstrate an up to 5x speed-up over the ROSS simulator for workloads with substantial locality.

关键词： High-performance computing parallel discrete event simulation Time Warp active messages GASNet

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A Next Generation Architecture for Internet of Things in the Automotive Supply Chain for Electric Vehicles 24

A Next Generation Architecture for Internet of Things in the...

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2024 International symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile computing, MobiHoc 2024

作者： Kapsalis, Panagiotis Rimassa, Giovanni Zeydan, Engin Via, Selva Risso, Fulvio Giovanni Chiasserini, Carla Fabiana Vivo, Giulio Martel Innovate Zürich Switzerland Castelldefels Spain Politechnico di Torino Turin Italy Centro Ricerche FIAT SCpA Turin Italy

ISBN: (纸本)9798400705212

This paper presents a next-generation architecture that focuses on the advancement of edge computing and Internet of Things (IoT) technologies in the context of the automotive supply value chain for electric vehicles (EVs). First, we outline the general architecture design, the specific layers and their goals. Based on the principles of the proposed architecture, we also give a use case for improving the traceability, monitoring and efficiency of EV battery transportation using innovative approaches in federated data spaces, AI-powered inference and orchestration of a multi-objective computational continuum. The automotive supply chain use case is presented with potential Key Performance Indicators (KPIs) while emphasizing the potential impact on operational efficiency, cost reduction and sustainability. By addressing the current limitations in distributed intelligence, data governance, and cross-domain interoperability, we emphasize the importance of real-time data processing, dynamic field governance, and energy-efficient machine learning in the context of the electric vehicle supply chain. At the end of the paper, a discussion and comparative analysis highlights the advances over existing technologies and frameworks and identifies future directions to further improve innovations and applications in this area. © 2024 Copyright held by the owner/author(s).

关键词： Edge computing

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PODS 2023 - proceedings of the 42nd acm SIGMOD-SIGACT-SIGAI symposium on principles of Database Systems

PODS 2023 - Proceedings of the 42nd ACM SIGMOD-SIGACT-SIGAI ...

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42nd acm SIGMOD-SIGACT-SIGAI symposium on principles of Database Systems, PODS 2023

ISBN: (纸本)9798400701276

The proceedings contain 33 papers. The topics discussed include: applications of sketching and pathways to impact;generative datalog with stable negation;synthesizing nested relational queries from implicit specifications;distributed consistency beyond queries;space-time tradeoffs for conjunctive queries with access patterns;allocating isolation levels to transactions in a multiversion setting;better differentially private approximate histograms and heavy hitters using the Misra-Gries sketch;extremal fitting problems for conjunctive queries;on join sampling and the hardness of combinatorial output-sensitive join algorithms;set cover in the one-pass edge-arrival streaming model;coloring in graph streams via deterministic and adversarially robust algorithms;towards better bounds for finding quasi-identifiers;weighted Minwise hashing beats linear sketching for inner product estimation;and node-differentially private estimation of the number of connected components.

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Fast, Accurate and distributed Simulation of novel HPC systems incorporating ARM and RISC-V CPUs 24

Fast, Accurate and Distributed Simulation of novel HPC syste...

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33rd International symposium on High-Performance Parallel and distributed computing (HPDC)

作者： Tampouratzis, Nikolaos Papaefstathiou, Ioannis EXAPSYS Plc Exascale Performance Syst Iraklion Greece

ISBN: (纸本)9798400704130

The growing developments of HPC systems used in a plethora of domains (healthcare, financial services, government and defense, energy) triggers an urgent demand for simulation frameworks that can simulate, in an integrated manner, both processing and network components of an HPC system-under-design (SuD). The main problem, however, is that, currently, there is a shortage of simulation frameworks that can handle the simulation of actual HPC systems, including the hardware, complete software stack and network dynamics in an integrated manner. In this work we start from the first known, open-source, fully-distributed Cloud simulation framework, COSSIM, and, as part of the RED-SEA1 and Vitamin-V2 European projects, we extend it so as to be able to accurately simulate HPC systems. The extended simulator has been evaluated when executing the very-widely used HPCG & LAMMPS benchmarks on both ARM & RISC-V architectures;the results demonstrate that the presented approach has up to 95% accuracy in the reported SuD aspects.

关键词： HPC Simulator distributed Systems Simulator ARM RISC-V

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