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检索条件"任意字段=2024 International Symposium on Computer Architecture and High Performance Computing Workshops"

共 5225 条记录，以下是201-210 订阅

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FLIPBIT: Approximate Flash Memory for IoT Devices 30

FLIPBIT: Approximate Flash Memory for IoT Devices

引用

30th IEEE international symposium on high-performance computer architecture (HPCA)

作者： Buck, Alexander Ganesan, Karthik Jerger, Natalie Enright Univ Toronto Toronto ON Canada

ISBN: (纸本)9798350393132;9798350393149

IoT devices commonly use flash memory for both data and code storage. Flash memory consumes a significant portion of the overall energy of such devices. This is problematic because IoT devices are energy constrained due to their reliance on batteries or energy harvesting. To save energy, we leverage a unique property of flash memory;write operations take unequal amounts of energy depending on if we are flipping a 1. 0 versus a 0. 1. We exploit this asymmetry to reduce energy consumption with FLIPBIT, a hardware-software approximation approach that limits costly 0. 1 transitions in flash. Instead of performing an exact write, we write an approximated value that avoids any costly 0. 1 bit flips. Using FLIPBIT, we reduce the mean energy used by flash by 68% on video streaming applications while maintaining 42 dB PSNR. On machine learning models, we reduce energy by an average of 39% and up to 71% with only a 1% accuracy loss. Additionally, by reducing the number of program-erase cycles, we increase the flash lifetime by 68%.

关键词： Approximate computing Internet-of-Things Non-volatile memory

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AI Gauge: Runtime Estimation for Deep Learning in the Cloud 31

AI Gauge: Runtime Estimation for Deep Learning in the Cloud

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31st international symposium on computer architecture and high performance computing (SBAC-PAD)

作者： Dube, Parijat Suk, Tonghoon Wang, Chen IBM Res Yorktown Hts NY 10598 USA

ISBN: (纸本)9781728141947

Major cloud providers, including IBM Cloud, Amazon Web Services, Microsoft Azure, and Google Cloud, offer services to train, debug, store, and deploy machine learning models at scale. For enhanced user experience in SLA-driven control, cost effective budgeting, elastic scaling, and efficient operations, estimating the runtime of training a machine learning model is important. We present AI Gauge, a cloud service to estimate runtime and cost for training deep learning models under different configuration options on the cloud. AI Gauge is designed using micro-service architecture and performs estimations based on machine learning models calibrated by an extensive and continuously populated job trace data-set. We show that AI Gauge can accurately predict the remaining time of running jobs based on its runtime progress (< 10% relative error) and can accurately predict the total runtime for a job before it starts with 7-8% relative error on average.

关键词： cloud computing deep learning model training GPUs runtime estimation micro-service architecture

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A Fault-Tolerant Agent-based architecture for Transient Servers in Fog computing 30

A Fault-Tolerant Agent-based Architecture for Transient Serv...

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30th international symposium on computer architecture and high performance computing (SBAC-PAD)

作者： de Araujo Neto, Jose Pergentino Pianto, Donald M. Ralha, Celia G. Univ Brasilia UnB Dept Comp Sci CIC Brasilia DF Brazil Univ Brasilia UnB Dept Stat EST Brasilia DF Brazil

ISBN: (纸本)9781538677698

Cloud datacenters are exploring their idle resources and offering virtual machine as transient servers without availability guarantees. Spot instances are transient servers offered by Amazon AWS, with rules that define prices according to supply and demand. These instances will run for as long as the current price is lower than the maximum bid price given by users. Spot instances have been increasingly used for executing computation and memory intensive applications. By using dynamic fault tolerant mechanisms and appropriate strategies, users can effectively use spot instances to run applications at a cheaper price. This paper presents a resilient multi-strategy agent-based cloud computing architecture. The architecture combines machine learning and a statistical model to predict instance survival times, refine fault tolerance parameters and reduce total execution time. We evaluate our strategies and the experiments demonstrate high levels of accuracy, reaching a 94% survival prediction success rate, which indicates that the model can be effectively used to define execution strategies to prevent failures at revocation events under realistic working conditions.

关键词： Agent-based architecture Resilient Cloud computing Spot Instance Fault Tolerance Checkpoint

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Finite Element Nodal Approach for Parallel Processing of Non Linear Shell Analysis

Finite Element Nodal Approach for Parallel Processing of Non...

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21st international symposium on computer architecture and high performance computing

作者： Ogawa Kawabata, Celia Leiko Kawabata Neto, Masaki Coda, Humberto Breves Venturini, Wilson Sergio Univ Sao Paulo Sch Engn Sao Carlos Dept Struct Engn Sao Carlos SP Brazil

ISBN: (纸本)9780769538570

This study presents a new parallel Finite Element Method (FEM) strategy designed for coarse grain distributed memory systems. The adopted communication protocol is Message Passing Interface (MPI) and tests are carried out in a cluster of PCs. Compressed data structure is used to store the Hessian matrix in order to optimize memory usage and to use the parallel direct solver MUMPS. The new partitioning paradigm is based on structural finite element nodes, not elements (as usually done in references), resulting in an overlapping algorithm, where a reduced amount of information should be allocated and manipulated to integrate finite elements. The main advantage of the nodal partitioning is the performance improvement of the Hessian matrix assembly and the natural ordering to improve the system solution. Numerical examples are shown in order to demonstrate the efficiency and scalability of the proposed algorithm.

关键词： parallel computing message passing interface finite element method coarse grain simulation

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XPySom: high-performance Self-Organizing Maps 32

XPySom: High-Performance Self-Organizing Maps

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32nd IEEE international symposium on computer architecture and high-performance computing (SBAC-PAD) / 11th Workshop on Applications for Multi-Core architectures (WAMCA)

作者： Mancini, Riccardo Ritacco, Antonio Lanciano, Giacomo Cucinotta, Tommaso Scuola Super Sant Anna Pisa Italy Scuola Normale Super Pisa Pisa Italy

ISBN: (纸本)9781728199245

In this paper, we introduce XPySom, a new opensource Python implementation of the well-known Self-Organizing Maps (SOM) technique. It is designed to achieve high performance on a single node, exploiting widely available Python libraries for vector processing on multi-core CPUs and GP-GPUs. We present results from an extensive experimental evaluation of XPySom in comparison to widely used open-source SOM implementations, showing that it outperforms the other available alternatives. Indeed, our experimentation carried out using the Extended MNIST open data set shows a speed-up of about 7x and 100x when compared to the best open-source multi-core implementations we could find with multi-core and GP-GPU acceleration, respectively, achieving the same accuracy levels in terms of quantization error.

关键词： self-organizing maps (SOMs) performance comparison experimental evaluation GP-GPU acceleration

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CLITE: Efficient and QoS-Aware Co-location of Multiple Latency-Critical Jobs for Warehouse Scale computers 26

CLITE: Efficient and QoS-Aware Co-location of Multiple Laten...

引用

26th IEEE international symposium on high performance computer architecture (HPCA)

作者： Patel, Tirthak Tiwari, Devesh Northeastern Univ Boston MA 02115 USA

ISBN: (纸本)9781728161495

Large-scale data centers run latency-critical jobs with quality-of-service (QoS) requirements, and throughput-oriented background :jobs, which need to achieve high performance. Previous works have proposed methods which cannot co-locate multiple latency-critical jobs with multiple backgrounds jobs while: (I) meeting the QoS requirements of all latency-critical jobs, and (2) maximizing the performance of the background jobs. This paper proposes CLITE, a Bayesian Optimization-based, multi-resource partitioning technique which achieves these goals.

关键词： Latency Critical Jobs Multi Tenancy QoS Delivery Warehouse Scale computing

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Non-stationary simulation of computer systems and dynamic performance evaluation: a concern-based approach and case study on cloud computing 27

Non-stationary simulation of computer systems and dynamic pe...

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IEEE 27th international symposium on computer architecture and high performance computing

作者： Pereira, Lourenco A., Jr. Mamani, Edwin L. C. Santana, Marcos J. Santana, Regina H. C. Nobile, Pedro Northon Monaco, Francisco Jose Univ Sao Paulo Dept Sistemas Comp Sao Carlos SP Brazil Inst Fed Sao Paulo Dept Informat Sao Carlos SP Brazil Univ Sao Paulo Dept Sist Comp Sao Carlos SP Brazil

ISBN: (纸本)9781467380119

This paper introduces an approach to the design of discrete event simulation experiments aimed at transient performance analysis. Specially in complex, multi-tier applications, the net effects of small delays introduced by buffers, IO operations, communication latency and averaged measurements, may result in significant inertia along the input-output path. In order to bring out these dynamic properties, the simulation experiment should excite the system with non-stationary workload under controlled conditions. The work discusses on the dynamic properties of large-scale distributed computer systems and how these may impact delivered performance. These rationales are explored to motivate a concern-based architecture which captures the elicited requirements. The design approach is systematic formulated and illustrated by a case study on extending a well-known cloud computing simulation framework to meet the aimed features. Experimental results of ongoing work are also addressed.

关键词： Cloud computing performance Evaluation Quality of Service

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Evaluation Model and performance Analysis of NIC Aggregations in Containerized Private Clouds 35

Evaluation Model and Performance Analysis of NIC Aggregation...

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35th IEEE international symposium on computer architecture and high performance computing (SBAC-PAD)

作者： Maliszewski, Anderson M. Griebler, Dalvan Roloff, Eduardo Righi, Rodrigo da Rosa Navaux, Philippe O. A. Fed Univ Rio Grande Sul UFRGS Informat Inst Porto Alegre RS Brazil Tres de Maio Fac SETREM Lab Adv Res Cloud Comp LARCC Tres De Maio Brazil Pontifical Catholica Univ Rio Grande Sul PUCRS Sch Technol Porto Alegre RS Brazil Univ Vale Rio Sinos UNISINOS Software Innovat Lab SoftwareLab Sao Leopoldo Brazil

ISBN: (纸本)9798350381603

The availability of computational resources changed significantly due to cloud computing. In addition, we have witnessed efforts to execute high-performance computing (HPC) applications in the cloud attracted by the advantages of cost savings and scalable/elastic resource allocation. Allocating more powerful hardware and exclusivity allocating resources such as memory, storage, and CPU can improve performance in the cloud. For network interconnection, significant noise, and other inferences are generated by several simultaneous instances (multitenants) communicating using the same network. As increasing the network bandwidth may be an alternative, we designed an evaluation model, and performance analysis of NIC aggregation approaches in containerized private clouds. The experiments using NAS Parallel Benchmarks revealed that NIC aggregation approach outperforms the baseline up to similar to 98% of the executions with applications characterized by intensive network use. Also, the Balance Round-Robin aggregation mode performed better than the 802.3ad aggregation mode in most assessments.

关键词： Cloud computing Private Cloud high performance computing Network performance NIC Aggregation performance Analysis

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A User-level Scheduling Framework for BoT Applications on Private Clouds 29

A User-level Scheduling Framework for BoT Applications on Pr...

引用

29th international symposium on computer architecture and high performance computing SBAC-PAD

作者： dos Santos, Maicon Anca Du Bois, Andre R. Cavalheiro, Gerson Geraldo H. Univ Fed Pelotas Grad Program Comp Sci POB 354 BR-96010900 Pelotas RS Brazil

ISBN: (纸本)9781509012336

This paper presents a high level model to describe bag of tasks (BoT) applications and a framework to evaluate user level approaches to scheduler BoTs on coarser works units. The scheduler consolidates the load of the tasks in a given number of virtual machines (VMs) providing the estimated makespan. The framework allows to change the policy of tasks selection in order to compare the length of the scheduling produced giving a limited number of VMs. The framework has as input a BoT description and produces for each VM its trace of processing load. This paper validates the BoT model and the proposed framework with a performance assessment. In our case studies, the output of the framework is submitted to a real OpenStack based IaaS infrastructure. The results show that the makespan can be reduced by grouping tasks in coarse units of loads.

关键词： Processor scheduling Cloud computing Computational modeling Computational efficiency Weibull distribution

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16 Years of SPEC Power: An Analysis of x86 Energy Efficiency Trends

16 Years of SPEC Power: An Analysis of x86 Energy Efficiency...

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2024 international Conference on Cluster computing

作者： Troepgen, Hannes Schoene, Robert Ilsche, Thomas Hackenberg, Daniel Tech Univ Dresden CIDS ZIH D-01062 Dresden Germany

ISBN: (纸本)9798350383461;9798350383454

The SPEC Power benchmark offers valuable insights into the energy efficiency of server systems, allowing comparisons across various hardware and software configurations. Benchmark results are publicly available for hundreds of systems from different vendors, published since 2007. We leverage this data to perform an analysis of trends in x86 server systems, focusing on power consumption, energy efficiency, energy proportionality and idle power consumption. Through this analysis, we aim to provide a clearer understanding of how server energy efficiency has evolved and the factors influencing these changes.

关键词： computer architecture performance analysis high performance computing Processor energy efficiency

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