scholarly journals GPU-Based Dynamic Hyperspace Hash with Full Concurrency

2021 ◽  
Author(s):  
Zhuo Ren ◽  
Yu Gu ◽  
Chuanwen Li ◽  
FangFang Li ◽  
Ge Yu
Keyword(s):  
Control Strategy ◽  
Concurrency Control ◽  
High Performance ◽  
Hash Table ◽  
Multidimensional Space ◽  
Retrieval Performance ◽  
Data Bases ◽  
Sharing Strategy ◽  
The Rich ◽  
Parallel Acceleration

AbstractHyperspace hashing which is often applied to NoSQL data-bases builds indexes by mapping objects with multiple attributes to a multidimensional space. It can accelerate processing queries of some secondary attributes in addition to just primary keys. In recent years, the rich computing resources of GPU provide opportunities for implementing high-performance HyperSpace Hash. In this study, we construct a fully concurrent dynamic hyperspace hash table for GPU. By using atomic operations instead of locking, we make our approach highly parallel and lock-free. We propose a special concurrency control strategy that ensures wait-free read operations. Our data structure is designed considering GPU specific hardware characteristics. We also propose a warp-level pre-combinations data sharing strategy to obtain high parallel acceleration. Experiments on an Nvidia RTX2080Ti GPU suggest that GHSH performs about 20-100X faster than its counterpart on CPU. Specifically, GHSH performs updates with up to 396 M updates/s and processes search queries with up to 995 M queries/s. Compared to other GPU hashes that cannot conduct queries on non-key attributes, GHSH demonstrates comparable building and retrieval performance.

An Interpretation Process for Clustering Analysis Based on the Ontology of Language

2008 ◽  
pp. 297-320
Author(s):  
Wagner Francisco Castilho ◽  
Gentil José de Lucena Filho ◽  
Hércules Antonio do Prado ◽  
Edilson Ferneda
Keyword(s):  
Clustering Analysis ◽  
Multidimensional Space ◽  
Web Pages ◽  
Conceptual Basis ◽  
Data Bases ◽  
Interpretation Process

Clustering analysis (CA) techniques consist in, given a set of objects, estimating dense regions of points separated by sparse regions, according to the dimensions that describe these objects. Independently from the data nature – structured or non-structured -, we look for homogenous clouds of points, that define clusters, from which we want to extract some meaning. In other words, when doing CA, the analyst is searching for underlying structures in a multidimensional space for what one could assign some meaning. Grossly, to carry a CA application, two main activities are involved: generating clusters configurations by means of an algorithm and interpreting these configurations in order to approximate a solution that could contribute with the CA application objective. Generating a clusters configuration is typically a computational task, while the interpretation task brings a strong burden of subjectivity. Many approaches are presented in the literature for generating clusters configuration. Unfortunately, the interpretation task has not received so much attention, possibly due to the difficulty in modeling something that is subjective in nature. In this chapter a method to guide the interpretation of a clusters configuration is proposed. The inherent subjectivity is approached directly by describing the process with the apparatus of the Ontology of Language. The main contribution of this chapter is to provide a sound conceptual basis to guide the analyst in extracting meaning from the patterns found in a set of data, no matter we are talking about data bases, a set of free texts, or a set of web pages.

scholarly journals A Novel Vector Control Strategy for a Six-Phase Induction Motor with Low Torque Ripples and Harmonic Currents

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 1102 ◽  
Author(s):  
Hamidreza Heidari ◽  
Anton Rassõlkin ◽  
Toomas Vaimann ◽  
Ants Kallaste ◽  
Asghar Taheri ◽  
...  
Keyword(s):  
Vector Control ◽  
Induction Motor ◽  
Control Strategy ◽  
High Performance ◽  
Direct Torque Control ◽  
Low Frequency ◽  
Torque Control ◽  
Harmonic Currents ◽  
Torque Ripples ◽  
Vector Control Strategy

In this paper, a new vector control strategy is proposed to reduce torque ripples and harmonic currents represented in switching table-based direct torque control (ST-DTC) of a six-phase induction motor (6PIM). For this purpose, a new set of inputs is provided for the switching table (ST). These inputs are based on the decoupled current components in the synchronous reference frame. Indeed, using both field-oriented control (FOC) and direct torque control (DTC) concepts, precise inputs are applied to the ST in order to achieve better steady-state torque response. By applying the duty cycle control strategy, the loss subspace components are eliminated through a suitable selection of virtual voltage vectors. Each virtual voltage vector is based on a combination of a large and a medium vector to make the average volt-seconds in loss subspace near to zero. Therefore, the proposed strategy not only notably reduces the torque ripples, but also suppresses the low frequency current harmonics, simultaneously. Simulation and experimental results clarify the high performance of the proposed scheme.

EXPERIMENTAL REALIZATION OF DYNAMIC STAIR CLIMBING AND DESCENDING OF BIPED HUMANOID ROBOT, HUBO

2009 ◽  
Vol 06 (02) ◽  
pp. 205-240 ◽  
Author(s):  
JUNG-YUP KIM ◽  
ILL-WOO PARK ◽  
JUN-HO OH
Keyword(s):  
Control Strategy ◽  
High Performance ◽  
Humanoid Robot ◽  
Stair Climbing ◽  
Control Technique ◽  
Experimental Realization ◽  
Biped Walking ◽  
Switching Control Strategy ◽  
Stair Walking ◽  
And Performance

In this paper, dynamic stair climbing and descending are experimentally realized for a biped humanoid robot, HUBO. Currently, in addition to biped walking on the ground, other types of biped walking such as running, jogging, and stair walking (climbing and descending) have been also studied since the end of 1990. In spite of many years of research works on stair walking, it is still a challengeable topic that requires high performance of control technique. For dynamic stair walking, we designed stair climbing and descending patterns according to a known stair configuration. Next, we defined stair climbing and descending stages for a switching control strategy. In each stage, we designed and adopted several online controllers to maintain the balance. For the simplicity and easy application, the online controllers only use the force and torque signals of the force/torque sensors of the feet. Finally, the effectiveness and performance of the proposed strategy are verified through stair climbing and descending experiments of HUBO.

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