POTENTIAL is a virtual database machine based on general computing platforms, especially parallel computing platforms. It provides a complete solution to high-performance database systems by a 'virtual processor ...POTENTIAL is a virtual database machine based on general computing platforms, especially parallel computing platforms. It provides a complete solution to high-performance database systems by a 'virtual processor + virtual data bus + virtual memory' architecture. Virtual processors manage all CPU resources in the system, on which various operations are running. Virtual data bus is responsible for the management of data transmission between associated operations, which forms the hinges of the entire system. Virtual memory provides efficient data storage and buffering mechanisms that conform to data reference behaviors in database systems. The architecture of POTENTIAL is very clear and has many good features, including high efficiency, high scalability, high extensibility, high portability, etc.展开更多
We developed a parallel object relational DBMS named PORLES. It uses BSP model as its parallel computing model, and monoid calculus as its basis of data model. In this paper, we introduce its data model, parallel que...We developed a parallel object relational DBMS named PORLES. It uses BSP model as its parallel computing model, and monoid calculus as its basis of data model. In this paper, we introduce its data model, parallel query optimization, transaction processing system and parallel access method in detail.展开更多
A novel Hilbert-curve is introduced for parallel spatial data partitioning, with consideration of the huge-amount property of spatial information and the variable-length characteristic of vector data items. Based on t...A novel Hilbert-curve is introduced for parallel spatial data partitioning, with consideration of the huge-amount property of spatial information and the variable-length characteristic of vector data items. Based on the improved Hilbert curve, the algorithm can be designed to achieve almost-uniform spatial data partitioning among multiple disks in parallel spatial databases. Thus, the phenomenon of data imbalance can be significantly avoided and search and query efficiency can be enhanced.展开更多
Pneumonia is an acute lung infection that has caused many fatalitiesglobally. Radiologists often employ chest X-rays to identify pneumoniasince they are presently the most effective imaging method for this purpose.Com...Pneumonia is an acute lung infection that has caused many fatalitiesglobally. Radiologists often employ chest X-rays to identify pneumoniasince they are presently the most effective imaging method for this purpose.Computer-aided diagnosis of pneumonia using deep learning techniques iswidely used due to its effectiveness and performance. In the proposed method,the Synthetic Minority Oversampling Technique (SMOTE) approach is usedto eliminate the class imbalance in the X-ray dataset. To compensate forthe paucity of accessible data, pre-trained transfer learning is used, and anensemble Convolutional Neural Network (CNN) model is developed. Theensemble model consists of all possible combinations of the MobileNetv2,Visual Geometry Group (VGG16), and DenseNet169 models. MobileNetV2and DenseNet169 performed well in the Single classifier model, with anaccuracy of 94%, while the ensemble model (MobileNetV2+DenseNet169)achieved an accuracy of 96.9%. Using the data synchronous parallel modelin Distributed Tensorflow, the training process accelerated performance by98.6% and outperformed other conventional approaches.展开更多
This paper focuses on the parallel aggregation processing of data streams based on the shared-nothing architecture. A novel granularity-aware parallel aggregating model is proposed. It employs parallel sampling and li...This paper focuses on the parallel aggregation processing of data streams based on the shared-nothing architecture. A novel granularity-aware parallel aggregating model is proposed. It employs parallel sampling and linear regression to describe the characteristics of the data quantity in the query window in order to determine the partition granularity of tuples, and utilizes equal depth histogram to implement partitio ning. This method can avoid data skew and reduce communi cation cost. The experiment results on both synthetic data and actual data prove that the proposed method is efficient, practical and suitable for time-varying data streams processing.展开更多
Since Multimode data is composed of many modes and their complex relationships,it cannot be retrieved or mined effectively by utilizing traditional analysis and processing techniques for single mode data.To address th...Since Multimode data is composed of many modes and their complex relationships,it cannot be retrieved or mined effectively by utilizing traditional analysis and processing techniques for single mode data.To address the challenges,we design and implement a graph-based storage and parallel loading system aimed at multimode medical image data.The system is a framework designed to flexibly store and rapidly load these multimode data.Specifically,the system utilizes the Mode Network to model the modes and their relationships in multimode medical image data and the graph database to store the data with a parallel loading technique.展开更多
Aim To develop a heterogeneous database united system(HDBUS)that combines the local database of Oracle, Sybase and SQL server distributed on different server into a global database,and supports the global transaction...Aim To develop a heterogeneous database united system(HDBUS)that combines the local database of Oracle, Sybase and SQL server distributed on different server into a global database,and supports the global transaction management and parallel query over the Intranet Methods In the designing and implementation of HDBUS two important concepts heterogeneous tables join. Results and Conclu- tion The first concept can be used to process the parallel query of multiple database server, the second one is the key technology of heterogeneous is the key technology of heterogeneous distribute database.展开更多
To efficiently exploit the performance of single instruction multiple data （SIMD） architectures for video coding, a parallel memory architecture with power-of-two memory modules is proposed. It employs two novel ske...To efficiently exploit the performance of single instruction multiple data （SIMD） architectures for video coding, a parallel memory architecture with power-of-two memory modules is proposed. It employs two novel skewing schemes to provide conflict-free access to adjacent elements （8-bit and 16-bit data types） or with power-of-two intervals in both horizontal and vertical directions, which were not possible in previous parallel memory architectures. Area consumptions and delay estimations are given respectively with 4, 8 and 16 memory modules. Under a 0.18-pm CMOS technology, the synthesis results show that the proposed system can achieve 230 MHz clock frequency with 16 memory modules at the cost of 19k gates when read and write latencies are 3 and 2 clock cycles, respectively. We implement the proposed parallel memory architecture on a video signal processor （VSP）. The results show that VSP enhanced with the proposed architecture achieves 1.28× speedups for H.264 real-time decoding.展开更多
Based on the analysis of the task sizes and the load, this paper discussps the granularity ofrelation spliting in the spliting phase taking acount of task load being less than average load,andprobes into the relations...Based on the analysis of the task sizes and the load, this paper discussps the granularity ofrelation spliting in the spliting phase taking acount of task load being less than average load,andprobes into the relationship between the granularity and load balancing. The minimum number ofbuckets is determined on the basis of relation spliting granularity,and the maximum number ofproduct tuples of each node is induced under the prerequisite for ensuring load balance in paralleljoin.展开更多
基金This work is supported by the National .'863' High-Tech Programme under grant! No.863-306-02-04-1the National Natural Scienc
文摘POTENTIAL is a virtual database machine based on general computing platforms, especially parallel computing platforms. It provides a complete solution to high-performance database systems by a 'virtual processor + virtual data bus + virtual memory' architecture. Virtual processors manage all CPU resources in the system, on which various operations are running. Virtual data bus is responsible for the management of data transmission between associated operations, which forms the hinges of the entire system. Virtual memory provides efficient data storage and buffering mechanisms that conform to data reference behaviors in database systems. The architecture of POTENTIAL is very clear and has many good features, including high efficiency, high scalability, high extensibility, high portability, etc.
文摘We developed a parallel object relational DBMS named PORLES. It uses BSP model as its parallel computing model, and monoid calculus as its basis of data model. In this paper, we introduce its data model, parallel query optimization, transaction processing system and parallel access method in detail.
基金Funded by the National 863 Program of China （No. 2005AA113150）, and the National Natural Science Foundation of China （No.40701158）.
文摘A novel Hilbert-curve is introduced for parallel spatial data partitioning, with consideration of the huge-amount property of spatial information and the variable-length characteristic of vector data items. Based on the improved Hilbert curve, the algorithm can be designed to achieve almost-uniform spatial data partitioning among multiple disks in parallel spatial databases. Thus, the phenomenon of data imbalance can be significantly avoided and search and query efficiency can be enhanced.
文摘Pneumonia is an acute lung infection that has caused many fatalitiesglobally. Radiologists often employ chest X-rays to identify pneumoniasince they are presently the most effective imaging method for this purpose.Computer-aided diagnosis of pneumonia using deep learning techniques iswidely used due to its effectiveness and performance. In the proposed method,the Synthetic Minority Oversampling Technique (SMOTE) approach is usedto eliminate the class imbalance in the X-ray dataset. To compensate forthe paucity of accessible data, pre-trained transfer learning is used, and anensemble Convolutional Neural Network (CNN) model is developed. Theensemble model consists of all possible combinations of the MobileNetv2,Visual Geometry Group (VGG16), and DenseNet169 models. MobileNetV2and DenseNet169 performed well in the Single classifier model, with anaccuracy of 94%, while the ensemble model (MobileNetV2+DenseNet169)achieved an accuracy of 96.9%. Using the data synchronous parallel modelin Distributed Tensorflow, the training process accelerated performance by98.6% and outperformed other conventional approaches.
基金Supported by Foundation of High Technology Pro-ject of Jiangsu (BG2004034) , Foundation of Graduate Creative Pro-gramof Jiangsu (xm04-36)
文摘This paper focuses on the parallel aggregation processing of data streams based on the shared-nothing architecture. A novel granularity-aware parallel aggregating model is proposed. It employs parallel sampling and linear regression to describe the characteristics of the data quantity in the query window in order to determine the partition granularity of tuples, and utilizes equal depth histogram to implement partitio ning. This method can avoid data skew and reduce communi cation cost. The experiment results on both synthetic data and actual data prove that the proposed method is efficient, practical and suitable for time-varying data streams processing.
文摘Since Multimode data is composed of many modes and their complex relationships,it cannot be retrieved or mined effectively by utilizing traditional analysis and processing techniques for single mode data.To address the challenges,we design and implement a graph-based storage and parallel loading system aimed at multimode medical image data.The system is a framework designed to flexibly store and rapidly load these multimode data.Specifically,the system utilizes the Mode Network to model the modes and their relationships in multimode medical image data and the graph database to store the data with a parallel loading technique.
文摘Aim To develop a heterogeneous database united system(HDBUS)that combines the local database of Oracle, Sybase and SQL server distributed on different server into a global database,and supports the global transaction management and parallel query over the Intranet Methods In the designing and implementation of HDBUS two important concepts heterogeneous tables join. Results and Conclu- tion The first concept can be used to process the parallel query of multiple database server, the second one is the key technology of heterogeneous is the key technology of heterogeneous distribute database.
基金Project (No. 2005AA1Z1271) supported by the Hi-Tech Research and Development Program (863) of China
文摘To efficiently exploit the performance of single instruction multiple data （SIMD） architectures for video coding, a parallel memory architecture with power-of-two memory modules is proposed. It employs two novel skewing schemes to provide conflict-free access to adjacent elements （8-bit and 16-bit data types） or with power-of-two intervals in both horizontal and vertical directions, which were not possible in previous parallel memory architectures. Area consumptions and delay estimations are given respectively with 4, 8 and 16 memory modules. Under a 0.18-pm CMOS technology, the synthesis results show that the proposed system can achieve 230 MHz clock frequency with 16 memory modules at the cost of 19k gates when read and write latencies are 3 and 2 clock cycles, respectively. We implement the proposed parallel memory architecture on a video signal processor （VSP）. The results show that VSP enhanced with the proposed architecture achieves 1.28× speedups for H.264 real-time decoding.
文摘Based on the analysis of the task sizes and the load, this paper discussps the granularity ofrelation spliting in the spliting phase taking acount of task load being less than average load,andprobes into the relationship between the granularity and load balancing. The minimum number ofbuckets is determined on the basis of relation spliting granularity,and the maximum number ofproduct tuples of each node is induced under the prerequisite for ensuring load balance in paralleljoin.
