Agents are the new defacto standard for inclusion in modules of today’s software systems such as ERP systems, mobile applications and operating systems. Agents are an integral part of today’s software design. The qu...Agents are the new defacto standard for inclusion in modules of today’s software systems such as ERP systems, mobile applications and operating systems. Agents are an integral part of today’s software design. The question is how do intelligent agents work in the specific area of ERP credit card processing e-commerce models? To answer this question, a specific area of ERP systems will be analyzed: credit card processing for merchants. One specific merchant credit card processor will be specifically investigated: EVO Merchants. This paper will research how exactly does ERP systems interact using Application Programing Interface or “API” specified by a credit card clearing house. Secure Socket Layers or SSL, and XML are discussed and elaborated on specifically how intelligent agents play such a pivotal role in ERP e-commerce systems for credit card processing.展开更多
During the last years, we have developed the FLOPER platform for providing a practical support to the so-called Multi-Adjoint Logic Programming approach (MALP in brief), which represents an extremely flexible framewor...During the last years, we have developed the FLOPER platform for providing a practical support to the so-called Multi-Adjoint Logic Programming approach (MALP in brief), which represents an extremely flexible framework into the Fuzzy Logic Programming arena. Nowadays, FLOPER is useful for compiling (to standard Prolog code), executing and debugging (by drawing execution trees) MALP programs, and it is ready for being extended in the near future with powerful transformation and optimization techniques designed in our research group during the recent past. Our last update consists in the integration of a graphical interface for a comfortable interaction with the system which allows, among other capabilities, the use of projects for packing scripts and auxiliary definitions of fuzzy sets/connectives, together with fuzzy programs and their associated lattices modeling truth-degrees beyond the simpler crisp case ﹛true;false﹜.展开更多
Parallel programs consist of series of code sections with different thread-level parallelism （TLP）. As a result, it is rather common that a thread in a parallel program, such as a GPU kernel in CUDA programs, still ...Parallel programs consist of series of code sections with different thread-level parallelism （TLP）. As a result, it is rather common that a thread in a parallel program, such as a GPU kernel in CUDA programs, still contains both sequential code and parallel loops. In order to leverage such parallel loops, the latest NVIDIA Kepler architecture introduces dynamic parallelism, which allows a GPU thread to start another GPU kernel, thereby reducing the overhead of launching kernels from a CPU. However, with dynamic parallelism, a parent thread can only communicate with its child threads through global memory and the overhead of launching GPU kernels is non-trivial even within GPUs. In this paper, we first study a set of GPGPU benchmarks that contain parallel loops, and highlight that these benchmarks do not have a very high loop count or high degree of TLP. Consequently, the benefits of leveraging such parallel loops using dynamic parallelism are too limited to offset its overhead. We then present our proposed solution to exploit nested parallelism in CUDA, referred to as CUDA-NP. With CUDA-NP, we initially enable a high number of threads when a GPU program starts, and use control flow to activate different numbers of threads for different code sections. We implement our proposed CUDA-NP framework using a directive-based compiler approach. For a GPU kernel, an application developer only needs to add OpenMP-like pragmas for parallelizable code sections. Then, our CUDA-NP compiler automatically generates the optimized GPU kernels. It supports both the reduction and the scan primitives, explores different ways to distribute parallel loop iterations into threads, and efficiently manages on-chip resource. Our experiments show that for a set of GPGPU benchmarks, which have already been optimized and contain nested parallelism, our proposed CUDA-NP framework further improves the performance by up to 6.69 times and 2.01 times on average.展开更多
The paper presents a redesign of a database management system for a retail business company.Initially,based on a traditional data model,it is migrated to a hybrid model which combines both SQL and NoSQL databases.This...The paper presents a redesign of a database management system for a retail business company.Initially,based on a traditional data model,it is migrated to a hybrid model which combines both SQL and NoSQL databases.This approach adds flexibility,mobility,and efficiency to the data management system.The NoSQL database uses an ontology as a data schema,which we describe in this study.The NoSQL database is consulted using the SPARQL query language,and some examples of the queries are detailed in the paper.The architecture of the system and its functionality are discussed.展开更多
文摘Agents are the new defacto standard for inclusion in modules of today’s software systems such as ERP systems, mobile applications and operating systems. Agents are an integral part of today’s software design. The question is how do intelligent agents work in the specific area of ERP credit card processing e-commerce models? To answer this question, a specific area of ERP systems will be analyzed: credit card processing for merchants. One specific merchant credit card processor will be specifically investigated: EVO Merchants. This paper will research how exactly does ERP systems interact using Application Programing Interface or “API” specified by a credit card clearing house. Secure Socket Layers or SSL, and XML are discussed and elaborated on specifically how intelligent agents play such a pivotal role in ERP e-commerce systems for credit card processing.
文摘During the last years, we have developed the FLOPER platform for providing a practical support to the so-called Multi-Adjoint Logic Programming approach (MALP in brief), which represents an extremely flexible framework into the Fuzzy Logic Programming arena. Nowadays, FLOPER is useful for compiling (to standard Prolog code), executing and debugging (by drawing execution trees) MALP programs, and it is ready for being extended in the near future with powerful transformation and optimization techniques designed in our research group during the recent past. Our last update consists in the integration of a graphical interface for a comfortable interaction with the system which allows, among other capabilities, the use of projects for packing scripts and auxiliary definitions of fuzzy sets/connectives, together with fuzzy programs and their associated lattices modeling truth-degrees beyond the simpler crisp case ﹛true;false﹜.
基金This work was supported by the National Science Foundation of USA under Grant No. CCF-1216569 and a CAREER award of National Science Foundation of USA under Grant No. CCF-0968667.
文摘Parallel programs consist of series of code sections with different thread-level parallelism （TLP）. As a result, it is rather common that a thread in a parallel program, such as a GPU kernel in CUDA programs, still contains both sequential code and parallel loops. In order to leverage such parallel loops, the latest NVIDIA Kepler architecture introduces dynamic parallelism, which allows a GPU thread to start another GPU kernel, thereby reducing the overhead of launching kernels from a CPU. However, with dynamic parallelism, a parent thread can only communicate with its child threads through global memory and the overhead of launching GPU kernels is non-trivial even within GPUs. In this paper, we first study a set of GPGPU benchmarks that contain parallel loops, and highlight that these benchmarks do not have a very high loop count or high degree of TLP. Consequently, the benefits of leveraging such parallel loops using dynamic parallelism are too limited to offset its overhead. We then present our proposed solution to exploit nested parallelism in CUDA, referred to as CUDA-NP. With CUDA-NP, we initially enable a high number of threads when a GPU program starts, and use control flow to activate different numbers of threads for different code sections. We implement our proposed CUDA-NP framework using a directive-based compiler approach. For a GPU kernel, an application developer only needs to add OpenMP-like pragmas for parallelizable code sections. Then, our CUDA-NP compiler automatically generates the optimized GPU kernels. It supports both the reduction and the scan primitives, explores different ways to distribute parallel loop iterations into threads, and efficiently manages on-chip resource. Our experiments show that for a set of GPGPU benchmarks, which have already been optimized and contain nested parallelism, our proposed CUDA-NP framework further improves the performance by up to 6.69 times and 2.01 times on average.
基金This work was partially carried out within the strategic development program“Engineering Center of Digital Environment Technologies for Integrated Security:Telecommunications,Communications and Energy Efficiency”,dependent on the Ministry of Education and Science of the Russian Federation.
文摘The paper presents a redesign of a database management system for a retail business company.Initially,based on a traditional data model,it is migrated to a hybrid model which combines both SQL and NoSQL databases.This approach adds flexibility,mobility,and efficiency to the data management system.The NoSQL database uses an ontology as a data schema,which we describe in this study.The NoSQL database is consulted using the SPARQL query language,and some examples of the queries are detailed in the paper.The architecture of the system and its functionality are discussed.
