Affix-oriented metadata search is one of the essential fuzzy search capabilities that allow users to find data of interest in their voluminous data set with incomplete query conditions. With the recent transition towa...
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ISBN:
(数字)9798350395662
ISBN:
(纸本)9798350395679
Affix-oriented metadata search is one of the essential fuzzy search capabilities that allow users to find data of interest in their voluminous data set with incomplete query conditions. With the recent transition towards object-centric data management systems in the science community, there is a paramount need for the support of such features in distributed settings. However, existing metadata search solutions either do not support efficient affix-oriented metadata search or do not suit well in a distributed setting of object-centric data management systems. To bridge this gap, we introduce IDIOMS, a metadata search solution underpinned by a distributed metadata index, meticulously designed to enable high-performance affix-oriented metadata search for parallel object-centric storage. One of the standout features of IDIOMS is its efficiency in supporting four distinct types of highly demanded metadata queries. Furthermore, IDIOMS is flexibly catering to both independent and collective metadata search operations. Our experimental comparisons with SoMeta, a state-of-the-art metadata query method, demonstrate more than 400× performance boost for independent queries and up to 300× performance improvements for collective queries, while keeping a small index management overhead.
When applied to large-scale industrial plants, the traditional linear quadratic gaussian (LQG) benchmark performance assessment method usually brings about unreachable economics, and its LQG curve dimension increases ...
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ISBN:
(数字)9781665471749
ISBN:
(纸本)9781665471749
When applied to large-scale industrial plants, the traditional linear quadratic gaussian (LQG) benchmark performance assessment method usually brings about unreachable economics, and its LQG curve dimension increases with the expansion of the system scale, which significantly aggravates the computation burden. To address various problems in the LQG benchmark method, an ILC-based two-layer economic performance assessment and improvement strategy are proposed and applied in large-scale distributed model predictive control (DMPC) systems. The presented strategy separates the whole operation time into multiple intervals during which the economic performance will be gradually improved and finally achieves its optimal. In each interval, the economic performance acquires its first promotion by the fixed variance obtained from the lower DMPC layer. The distributed ILC (DILC) method then provides the tuning parameters of each DMPC controller in the next period with the updating principle based on sensitivity analysis. The effectiveness of the presented strategy is verified via an improved Alumina continuous carbonation decomposition process compared to the former one.
Processing large datasets requires significant hardware resources and energy. Researchers have observed that most database management systems could not utilize available resources efficiently, increasing data to resul...
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ISBN:
(纸本)9798350302080
Processing large datasets requires significant hardware resources and energy. Researchers have observed that most database management systems could not utilize available resources efficiently, increasing data to result time and application running costs. This research explores techniques that can maximize the utilization of available resources to efficiently process large datasets on limited resource systems. The work implemented single and multiple resource maximization techniques and observed improvements in total workload execution time (WET). Results showed that combining CPU and RAM resource maximization techniques can reduce WET by 61-81% compared to the original WET observed with default resource allocation configuration. This work proposes a lightweight real-time resource allocation and task scheduling algorithm MUAR (Maximizing Utilization of Available Resources). It maximizes the utilization of available resources considering the real-time availability of resources and workload task complexity. The algorithm identifies complex multi-join queries and allocates maximum available resources for faster execution. MUAR is capable of estimating work memory value with 15-20% error required to achieve the best query performance with only single query run data. A comparison of MUAR with machine learning-based techniques like PCC and AutoToken is also presented.
Graph data is becoming dynamic and large-scale, demanding high-performance and large-capacity graph storage. Therefore, due to the performance approaching DRAM and the larger capacity than DRAM, persistent memory (PM)...
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ISBN:
(数字)9798331509712
ISBN:
(纸本)9798331509729
Graph data is becoming dynamic and large-scale, demanding high-performance and large-capacity graph storage. Therefore, due to the performance approaching DRAM and the larger capacity than DRAM, persistent memory (PM) has been adopted in large-scale dynamic graph storage systems. However, existing PM-based dynamic graph storage systems have issues, especially PM write amplification caused by the unsorted data structure used to store edges. To improve this issue, we propose a PM-based dynamic graph storage system, HDGraph, using sorted data structure to store edges on DRAM-PM hybrid memory architecture. To better adapt the sorted data structure on PM, HDGraph employs edge buffering on DRAM, merging small writes to reduce write amplification in PM. Moreover, HDGraph also triggers buffer flushing based on a heat evaluating strategy to alleviate DRAM space pressure. Finally, HDGraph maintains a buffering log in PM for edge-level data consistency, enabling quick recovery after a crash. Experimental results show that HDGraph achieves 1.09× to 1.52× higher edge ingestion performance, compared with the only PM-based dynamic graph storage system XPGraph, which use unsorted data structure to store edges.
Multi-parallel grid-connected inverter system is increasingly applied in distributed power generation systems. Due to the existence of grid impedance, the output current of the grid-connected inverter cannot be fed to...
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As semiconductor design approaches physical limits, computer processing speeds are stagnating. This poses significant challenges for traffic simulations, which are becoming more and more computationally demanding. To ...
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ISBN:
(数字)9798350369199
ISBN:
(纸本)9798350369205
As semiconductor design approaches physical limits, computer processing speeds are stagnating. This poses significant challenges for traffic simulations, which are becoming more and more computationally demanding. To maintain fast execution times while accommodating more complex simulations, it is essential to utilize the parallel computing capabilities of modern hardware. This paper discusses the need for an updated architectural design in the MATSim traffic simulation framework to take advantage of parallel computing infrastructures. We introduce a prototype that adapts the existing traffic simulation logic to a distributedparallel algorithm. Extensive benchmarks have been conducted to evaluate the prototype’s performance and identify its limitations. The results demonstrate that the prototype performs up to 100 times faster than the current implementation. Based on these findings, we advocate for the integration of a distributed traffic simulation within the MATSim framework and outline necessary steps to enhance the prototype.
The proceedings contain 42 papers. The special focus in this conference is on Joint international Conference of the internationalsymposium on Science of Mechanisms and Machines and international Conference on Robotic...
ISBN:
(纸本)9783031256547
The proceedings contain 42 papers. The special focus in this conference is on Joint international Conference of the internationalsymposium on Science of Mechanisms and Machines and international Conference on Robotics. The topics include: Study of Vibrations of a Cantilever Beam with Uniformly distributed Mass;considerations on the Proper Selection of Sensors for Vibroacoustic Study of the Vehicles;experimental Identification of Singularities in parallel Manipulators;requirements and Problems for Space Berthing System;A Kinematic Analysis of the TORVEastro Astronaut Robot Arm;Evaluation by Numerical Simulation of Friction Forces in Spherical Joints of a 6-DOF parallel Topology Robot;comparative Analysis of Four Solutions for Command and Control Applied to Anthropomorphic Grippers for Robots;Model-Free Reaching of a 2-DOF Robotic Arm Using Neural Networks;inverse Dynamic Modeling of a parallel Robot for Lower Limb Rehabilitation;a Study of Feasibility of a Mechanism for Rib-Vertebra-Sternum Prosthesis;kinematic and Dynamic Analysis of an Exoskeleton Robotic System;design and Operation of a Cable-Driven Robot for Lower-Limb Rehabilitation;a State of Art Overwiew on Wrist Rehabilitation Exoskeletons;design of an Exoskeleton for Rehabilitation Ankle Joint;requirements and Characteristics of Finger Motion Assistance;development of a Force Feedback Control for Robotic Assisted Liver Cancer Treatment;Perspectives on Originally Designed Eco-Friendly Robotic Cell for PCB Dismantling;cloud-Based Digital Twin for Robot Health Monitoring and Integration in Cyber-Physical Production systems;a Novel Design of a Robotic System for Biological Fluid Aliquoting;multimodal Perceptual Cues for Context-Aware Human-Robot Interaction;a Review on Mechanisms Used for the Reconfigurable Wheelchairs.
The proceedings contain 148 papers. The topics discussed include: heterogeneous architecture for sparse data processing;combined application of approximate computing techniques in DNN hardware accelerators;highly effi...
ISBN:
(纸本)9781665497473
The proceedings contain 148 papers. The topics discussed include: heterogeneous architecture for sparse data processing;combined application of approximate computing techniques in DNN hardware accelerators;highly efficient ALLTOALL and ALLTOALLV communication algorithms for GPU systems;implementing spatio-temporal graph convolutional networks on graphcore IPUs;the best of many worlds: scheduling machine learning inference on CPU-GPU integrated architectures;online learning RTL synthesis for automated design space exploration;machine learning aided hardware resource estimation for FPGA DNN implementations;optimal schedules for high-level programming environments on FPGAs with constraint programming;on how to push efficient medical semantic segmentation to the edge: the SENECA approach;and exploiting high-bandwidth memory for FPGA-acceleration of inference on sum-product networks.
distributed storage systems must store large amounts of data over long periods of time. To avoid data loss due to device failures, an [n, k] erasure code is used to encode k data symbols into a codeword of n symbols t...
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ISBN:
(纸本)9781665421607;9781665421591
distributed storage systems must store large amounts of data over long periods of time. To avoid data loss due to device failures, an [n, k] erasure code is used to encode k data symbols into a codeword of n symbols that are stored across different devices. However, device failure rates change throughout the life of the data, and tuning n and k according to these changes has been shown to save significant storage space. Code conversion is the process of converting multiple codewords of an initial [n(I), k(I)] code into codewords of a final [n(F), k(F)] code that decode to the same set of data symbols. In this paper, we study conversion bandwidth, defined as the total amount of data transferred between nodes during conversion. In particular, we consider the case where the initial and final codes are MDS and a single initial codeword is split into several final codewords (k(I) = lambda(F) k(F) for integer lambda(F) >= 2), called the split regime. We derive lower bounds on the conversion bandwidth in the split regime and propose constructions that significantly reduce conversion bandwidth and are optimal for certain parameters. An extended version of this paper is available at [1].
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