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International Conference on Enterprise Distributed Object computing (EDOC)

作者： Amir Hossein Borhani Philipp Leitner Bu-Sung Lee Xiaorong Li Terence Hung Institute of High-Performance Computing (IHPC) Singapore s.e.a.l. software evolution & architecture lab University of Zurich Switzerland Parallel and Distributed Computing Center (PDCC) Nanyang Technological University Singapore

ISBN: (纸本)9781479954711

Approaching a comprehensive performance benchmark for on-line transaction processing (OLTP) applications in a cloud environment is a challenging task. Fundamental features of clouds, such as the pay-as-you-go pricing model and unknown underlying configuration of the system, are contrary to the basic assumptions of available benchmarks such as TPC-W or RUBiS. In this paper, we introduce a systematic performance benchmark approach for OLTP applications on public clouds that use virtual machines(VMs). We propose WPress benchmark, which is based on the widespread blogging software, WordPress, as a representative OLTP application and implement an open source workload generator. Furthermore, we utilize a CPU micro-benchmark to investigate CPU performance of cloud-based VMs in greater detail. Average response time and total VM cost are the performance metrics measured by WPress. We evaluate small and large instance types of three real-life cloud providers, Amazon EC2, Microsoft Azure and Rackspace cloud. Results imply that Rackspace cloud has better average response times and total VM cost on small instances. However, Microsoft Azure is preferable for large instance type.

关键词： Benchmark testing Cloud computing Time factors Servers Databases Blogs Publishing

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Fuzzy correlational analysis for dynamic consolidation of virtual machines in cloud computing environment

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2023年第PartD期126卷

作者： Bertei, Alex Foss, Luciana Bedregal, Benjamin Reiser, Renata Univ Fed Pelotas Lab Ubiquitous & Parallel Syst Pelotas RS Brazil Fed Univ Rio Grande de Norte Dept Informat & Appl Math Postgrad Program Syst & Computing Natal RN Brazil

This theoretical research in fuzzy correlation analysis integrates data uncertainty analysis by measuring the strength of the linear relationship restricted to two fuzzy sets. As the relevant contribution to this research area, this paper presents the axiomatic definition of the n-dimensional generalized fuzzy correlation coefficient (nGCC), assigning to n input fuzzy sets an output value in the interval [-1,1]. Thus, the properties of general overlap functions and fuzzy negations are studied, discussing binary non-normed restricted dissimilarity functions, and the n-dimensional non-normed conjunctive functions. This study provides new methods for the n-dimensional generalized fuzzy correlation coefficient analysis, regarding their applications in solving multi-criteria and decision-making problems founded on fuzzy logic extensions. The n-dimensional non-normed conjunctive aggregation functions are also introduced, as range domain extensions from [0,1] to [-1.1], covering the interpretation of negative to positive variable associations. The proposal correlation analysis promotes a better evaluation and data selection even when more than one algorithm is applied to evaluate the reduction methods in the defuzzification process based on Interval-valued Fuzzy Logic. We also investigate the relevance to determine a reliable result from the fuzzy inference system based on the nGCC methodology. This correlation methodology applied to the Interval Fuzzy Load Balancing for Cloud computing (Int-FLBCC) model contributes as a flexible approach for virtual machines dynamic consolidation enabling improvements in resource usage and power efficiency, improving the computational system's energy efficiency. So, the nGCC methodology extends the Int-FLBCC model by adding other degrees of reliability to the results obtained with diverse evaluations through n-dimensional generalized fuzzy correlation coefficient expressions, exploring average aggregations as arithmetic and exponential me

关键词： Pearsen's correlation coefficient Cloud computing Fuzzy set n-dimensional fuzzy correlation analysis Multi-criteria Decision-making Interval-valued fuzzy logic

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C++ and Interoperability between Libraries: The GraphBLAS C++ Specification

C++ and Interoperability between Libraries: The GraphBLAS C+...

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2023 IEEE International parallel and Distributed Processing Symposium Workshops, IPDPSW 2023

作者： Brock, Benjamin McMillan, Scott Buluc, Aydin Mattson, Timothy G. Moreira, Jose E. Parallel Computing Lab Intel United States Software Engineering Institute Carnegie Mellon University United States Lawrence Berkeley National Laboratory Computational Research Department United States University of California EECS Department Berkeley United States IBM Thomas J. Watson Research Center United States

ISBN: (纸本)9798350311990

Interoperability between libraries is often hindered by incompatible data formats, which can necessitate creating new copies of data when transferring data back and forth between different libraries. This additional data movement incurs additional runtime costs, particularly for sparse applications, where the costs of data movement often dwarf compute costs. In this paper, we investigate interoperability in the context of the C++ GraphBLAS Specification, where C++ concepts allow GraphBLAS algorithms to accept any matrix type as long as it follows the matrix interface defined in the GraphBLAS matrix concept. We first develop non-owning, lazily evaluated adapted views for a number of external data structures, including two categories of graphs defined in the Northwest Graph Library (NWGraph) and traditional pointer-based CSR data structures. These adapted views fulfill the C++ GraphBLAS matrix concept, allowing them to be used inside GraphBLAS algorithms. We then evaluate the performance of these adapted views across two kernels, matrix reduction and sparse times dense matrix multiplication (SpMM), where the performance achieved using a single generic implementation with these views largely matches the performance achieved operating directly on the original data structures, with a slight performance loss in one case. We then propose a mechanism for automatically discovering the availability of these views, allowing algorithms to directly accept external data structures. We also discuss potential extensions to the C++ GraphBLAS specification that might eliminate the small performance dip observed for one of the views. © 2023 IEEE.

关键词： Data structures

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Using behavior to decode allocation of attention in context dependent decision making 14

Using behavior to decode allocation of attention in context ...

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14th International Conference on Cognitive Modeling, ICCM 2016

作者： Shvartsman, Michael Srivastava, Vaibhav Sundaram, Narayanan Cohen, Jonathan D. Princeton Neuroscience Institute Washington Rd. PrincetonNJ08544 United States Department of Mechanical and Aerospace Engineering 41 Olden St. PrincetonNJ08544 United States Intel Parallel Computing Lab 2200 Mission College Blvd. Santa ClaraCA95054 United States

ISBN: (纸本)9780998508207

We present a model of the dynamics of adaptive attention allocation in the AX Continuous Performance Test (AX-CPT), a simple context dependent decision making task of interest to the research communities concerned with cognitive control, schizophrenia, anxiety and aging (Braver et al., 2001;Cohen et al., 1999;Eysenck et al., 2007). We ground it in our recent theory of decision making under dynamic context, that assumes humans use sequential Bayesian inference to combine information from multiple sources in perception and (optionally) memory over time. The theory generalizes the well-known diffusion decision model of single-stimulus decision making (DDM;Ratcliff, 1978). Our first result is a new analysis that shows how memory encoding and retention can yield a variable initial condition for either a single- or multiple-stimulus decision, providing a theoretical grounding to the assumption of variability in initial condition previously shown to improve data fits for the DDM. Our second result is using this model to decode attention allocation from behavioral data in a novel quantitative payoff manipulation in the AX-CPT, showing that our model can capture the differences in how subjects encode and retrieve contextual information when the relative emphasis on task speed and accuracy is changed. Copyright © TRECVID *** rights reserved.

关键词： Decision making

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A Redundancy-Based Protocol for Safety Message Dissemination in Vehicular Ad Hoc Networks

A Redundancy-Based Protocol for Safety Message Dissemination...

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IEEE Conference on Vehicular Technology (VTC)

作者： Imen Achour Tarek Bejaoui Anthony Busson Sami Tabbane Mediatron Lab. SupCom University of Carthage Tunisia Telnet Holding Telnet Innovation Labs. Tunisia Laboratory of Parallel Computing University of Lyon France

ISBN: (纸本)9781479980925

The diversity of applications' types in vehicular ad hoc networks (VANETs) has spawned a large variety of messages that need to be disseminated in a vehicle to vehicle (V2V) communication mode. The most critical messages are those dedicated for safety applications such as accident warning, road hazardous warning, signal violation warning, etc. The dissemination of this kind of messages is a challenging task in VANETs since they should be efficiently transmitted i.e. by achieving high packet delivery within a limited transmission delay and an acceptable overhead. In this work, we propose a robust and an original data dissemination protocol called ``Redundancy-based Protocol (RBP)''. Unlike most of density-based protocols, RBP is beaconless. It takes into account the surrounding vehicles' density during the broadcasting process through a specific metric, named ``Packet Redundancy Ratio'', calculated locally at each vehicular node. On the basis of this metric, each vehicle is able to dynamically define the probability of rebroadcast in order to mitigate the broadcast storm problem. The simulation results show that the proposed protocol outperforms the slotted 1-persistence scheme in terms of packet drop ratio, and network load while still maintaining a low End-to-End delay and high packet reachability. This scheme is suitable either for safety applications or for further kinds of applications by saving the network capacity consumption.

关键词： Vehicles Protocols Redundancy Delays Safety Vehicular ad hoc networks

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Miss-Correlation Folding: Encoding Per-Block Miss Correlations in Compressed DRAM for Data Prefetching

Miss-Correlation Folding: Encoding Per-Block Miss Correlatio...

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IEEE International parallel & Distributed Processing Symposium

作者： Gang Liu Jih-Kwon Peir Victor Lee Department of Computer & Information Science & Eng University of Florida Gainesville FL USA Parallel Computing Lab Intel Labs Intel Corporation Santa Clara CA USA

ISBN: (纸本)9781467309752

Cache misses frequently exhibit repeated streaming behavior, i.e. a sequence of cache misses has a high tendency of being repeated. Correlation-based prefetchers record the missing streams in a history table for accurate prefetching. Saving a large miss history in off-chip DRAM is a practical implementation, but incurs access latency and consumes memory bandwidth which leads to performance degradation. In this paper, we investigate a new data prefetching mechanism based on per-block miss correlation where a miss is correlated with an earlier miss when the two misses are closely encountered both in time and space. The miss correlations are captured dynamically and saved along with the content of the data block using a simple data compression technique. As a result of this novel combination, our scheme provides unbounded correlation history and its prefetch metadata can be fetched together with demand data without incurring additional latency nor consuming any memory bandwidth. Performance evaluations using data-parallel applications demonstrate that prefetchers based on per-block miss correlations can improve IPC by 42-139% with an average of 88% compared to the IPC without prefetching. In comparison with regular stream prefetcher, sampled temporal streaming prefetcher and spatial-temporal memory streaming prefetcher, up to 115%, 99% and 98% IPC improvement can be obtained with an average about 36%, 26% and 27% respectively.

关键词： prefetch data parallel miss correlation compress cache temporal spatial

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Inverse scattering pre-stack depth imaging and it's comparison to some depth migration methods for imaging rich fault complex structure

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AIP Conference Proceedings 2011年第1期1454卷 83-86页

作者： Nurhandoko, Bagus Endar B. Sukmana, Indriani Mubarok, Syahrul Deny, Agus Widowati, Sri Kurniadi, Rizal Wave Inversion and Subsurface Fluid Imaging Research Laboratory WISFIR Basic Science Center A 4th floor Physics Department FMIPA Institut Teknologi Bandung Indonesia Rock Fluid Imaging Lab. Parallel Cluster Computing Center Bandung Jl. Sukasenang Raya no.2 Indonesia Department of Physics Institut Teknologi Bandung Indonesia

Migration is important issue for seismic imaging in complex structure. In this decade, depth imaging becomes important tools for producing accurate image in depth imaging instead of time domain imaging. The challenge of depth migration method, however, is in revealing the complex structure of subsurface. There are many methods of depth migration with their advantages and weaknesses. In this paper, we show our propose method of pre-stack depth migration based on time domain inverse scattering wave equation. Hopefully this method can be as solution for imaging complex structure in Indonesia, especially in rich thrusting fault zones. In this research, we develop a recent advance wave equation migration based on time domain inverse scattering wave which use more natural wave propagation using scattering wave. This wave equation pre-stack depth migration use time domain inverse scattering wave equation based on Helmholtz equation. To provide true amplitude recovery, an inverse of divergence procedure and recovering transmission loss are considered of pre-stack migration. Benchmarking the propose inverse scattering pre-stack depth migration with the other migration methods are also presented, i.e.: wave equation pre-stack depth migration, waveequation depth migration, and pre-stack time migration method. This inverse scattering pre-stack depth migration could image successfully the rich fault zone which consist extremely dip and resulting superior quality of seismic image. The image quality of inverse scattering migration is much better than the others migration methods. © 2012 American Institute of Physics.

关键词： Inverse scattering Migration Seismic

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NebulaFL: Effective Asynchronous Federated Learning for JointCloud computing

arXiv

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arXiv 2024年

作者： Gao, Fei Hu, Ming Xie, Zhiyu Shi, Peichang Xie, Xiaofei Yi, Guodong Wang, Huaimin National Key Lab. of Parallel and Distributed Processing National University of Defense Technology Changsha China School of Computing and Information Systems Singapore Management University Singapore Xiangjiang Lab Changsha China

With advancements in AI infrastructure and Trusted Execution Environment (TEE) technology, Federated Learning as a Service (FLaaS) through JointCloud computing (JCC) is promising to break through the resource constraints caused by heterogeneous edge devices in the traditional Federated Learning (FL) paradigm. Specifically, with the protection from TEE, data owners can achieve efficient model training with high-performance AI services in the cloud. By providing additional FL services, cloud service providers can achieve collaborative learning among data owners. However, FLaaS still faces three challenges, i.e., i) low training performance caused by heterogeneous data among data owners, ii) high communication overhead among different clouds (i.e., data centers), and iii) lack of efficient resource scheduling strategies to balance training time and cost. To address these challenges, this paper presents a novel asynchronous FL approach named NebulaFL for collaborative model training among multiple clouds. To address data heterogeneity issues, NebulaFL adopts a version control-based asynchronous FL training scheme in each data center to balance training time among data owners. To reduce communication overhead, NebulaFL adopts a decentralized model rotation mechanism to achieve effective knowledge sharing among data centers. To balance training time and cost, NebulaFL integrates a reward-guided strategy for data owners selection and resource scheduling. The experimental results demonstrate that, compared to the state-of-the-art FL methods, NebulaFL can achieve up to 5.71% accuracy improvement. In addition, NebulaFL can reduce up to 50% communication overhead and 61.94% costs under a target accuracy. Copyright © 2024, The Authors. All rights reserved.

关键词： Costs

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The stability performances improvement through kinematic and dynamic modeling of the hopping robots 10

The stability performances improvement through kinematic and...

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10th UKACC International Conference on Control, CONTROL 2014

作者： Bruja, Adrian Vladareanu, Luige Yu, Hongnian Wang, Hongbo Liu, Jingjing Bucharest Romania School of Design Engineering and Computing Bournemouth University Poole DorsetBH12 5BB United Kingdom Parallel Robot and Mechatronic System Laboratory of Hebei Province Key Lab. of Adv. Forging and Stamping Technol. and Sci. of Ministry of Education Yanshan University Qinhuangdao China

ISBN: (纸本)9781479950119

The paper presents an innovative design for a wheeled hopping robot. Our main objective was to obtain a stable and efficient robot, which can jump over obstacles and has the ability to reach a certain ledge. The innovative design of our robot has the capability to jump to a certain distance even with a zero initial velocity provided by the wheels movement. Also, we took into consideration the wind speed which can prevent our robot to reach the desired destination, and compensated with an initial velocity on the direction of movement. For testing we designed a simulation which had as inputs different initial conditions to test and present the jumping capability of our robot in different jumping conditions. In the end we provide a jump area which the robot can reach for certain initial conditions, so we can later chose the optimal one for reaching the target position. © 2014 IEEE.

关键词： Machine design

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Randomized reinforcement based scheduling in parallel processor systems

Randomized reinforcement based scheduling in parallel proces...

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Annual Hawaii International Conference on System Sciences (HICSS)

作者： A.Y. Zomaya M. Clements S. Olariu Parallel Computing Research Lab Department of Electrical & Electronic Engineering University of Western Australia Perth Australia Department of Computer Science Old Dominion University Norfolk VA USA

Task scheduling is important for the proper functioning of parallel processor systems. The static scheduling of tasks onto networks of parallel processors is well defined and documented in the literature. However, in many practical situations, a priori information about the tasks that need to be scheduled is not available. In such situations tasks usually arrive dynamically and the scheduling should be performed online or "on the fly". We present a framework based on stochastic reinforcement learning which is usually used to solve optimization problems in a simple and efficient way. The use of reinforcement learning reduces the dynamic scheduling problem to that of learning a stochastic approximation of an unknown average error surface. The learning system develops an association between the best action (schedule) and the current state of the environment (parallel system).

关键词： Processor scheduling Job shop scheduling Optimal scheduling Dynamic scheduling parallel processing Adaptive scheduling Learning systems Stochastic processes Unsupervised learning Signal processing

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