最新刊期
卷 4 ， 期 4 ， 2018
- 摘要：Fast network devices with RDMA support have been price-compatible with traditional network primitives such as Ethernet,and it’s now widely deployed in modern data centers.RDMA can be used in two ways.Firstly,it can optimize the messaging primitive in distributed applications.The second way is to redesign the applications with RDMA’s onesided features.One-sided features provide high CPU utilizations and high network performance,but the system should be redesigned.The research progress of RDMA was introduced.An overview on the research efforts on using RDMA for distributed systems was presented.The works on how to use RDMA to redesign systems and the works on how to better leverage RDMA were included.The future research directions were also put forward.关键词：distributed system;key-value stores system;graph processing system;OLTP system;remote procedure call1695|2311|0更新时间：2018-07-15
- 摘要：Big data applications put more pressure on memory system in the aspect of capacity and power consumption.However,limited by the shortcomings of DRAM and non-volatile memory(NVM),memory consists of single medium like DRAM or NVM is not competent for the requirements of big data applications.Thus,how to effectively design,efficiently manage and accurately evaluate the hybrid memories consist of DRAM and NVM are the major challenges that the academia and industry face today.The challenges of hybrid memory systems for big data processing from the perspective of computer architecture,system software,programming model and application were analyzed,and several solutions and optimizations were correspondingly provided,such as on-chip cache management,parallel processing,memory access scheduling,energy management,virtual-to-physical address translation,object-level memory allocation and migration mechanisms.Meanwhile,a number of prototypes to validate the effectiveness and efficiency of these proposals were developed.关键词：in-memory processing;hybrid memory;big data;non-volatile memory1130|1640|0更新时间：2018-07-15
- 摘要：Traditional relational data model cannot meet the demand of big data applications for expressing and processing wide varieties of data.As a result,a number of non-relational data types have become popular in practice,among which JSONlike tree-structured data types have been widely adopted.Tree-structured data types have important theoretical and practical values.A systematic description of tree-structured data types was provided,and the way to efficiently support data analysis operations on tree-structured data was investigated.关键词：tree-structured data;JSON;Steed653|1263|0更新时间：2018-07-15
- 摘要：In the scenario where data of real-world applications is in high-speed growth,existing methods for static graph computation are hard to approach the challenges from the rapidly updated data,and graph stream model arise at the historic moment.The inherent defects of static graph model and exiting data stream algorithms/systems over high-speed graph-structured data were discussed,and then the formal definition of graph stream combining with previous similar models was presented.Some promising research problems and applications over graph stream were probed,and then the possible requirements and technique issues on graph stream management system (GSMS) were looked into the future.关键词：graph model;data stream system;graph stream;data management system821|840|0更新时间：2018-07-15
- 摘要：In recent years,deep learning algorithms became increasingly pervasive.It has drew extensive attentions from both researchers and industries,as it achieves very promising results on many applications of various fields.More and more researchers began to use deep learning algorithms to solve practical problems (e.g.,image classification,image recognition,speech recognition,and natural language processing).Many deep learning frameworks and libraries were proposed so that researchers can develop new deep learning algorithms in a more convenient fashion.These frameworks and libraries were different in many aspects (e.g.,design principles and abstraction).Firstly,several pervasive deep learning frameworks were introduced,and then the critical issue of designing such frameworks was analyzed.At last,the future challenges of designing deep learning frameworks were discussed.The study provides ideas and directions for future design.关键词：machine learning;programming framework;big data704|1009|0更新时间：2018-07-15
TOPIC：SYSTEM ARCHITECTURE FOR BIG DATA-DRIVEN INTELLIGENT
- 摘要：The data cleaning and recognition technology,business model and algorithm analysis technology,data visualization display technology were used to build the big data analysis platform,based on the working data and business data of concrete machinery.The goal to analysis the construction rate and market analysis of all the equipment in China were achieved,also the developing trend and market forecast were made,and dynamic maintenance,fault statistics and real-time warning were also achieved.The purpose of data driven production,market and service were realized,and the transformation and development of intelligent of construction machinery can be realized through big data drive in the near future.关键词：concrete machinery;industrial big data;big data analysis;big data application408|779|0更新时间：2018-07-15
- 摘要：Based on the big data concept and techniques in the financial regulation,smoke index was taken as the core technology to the Internet financial risk monitoring system,and the real-time monitoring and integration of multi-heterogeneous risk information were carried out and a set of “people”,“capital” and “business” risk assessment indexes by using technologies such as big data,cloud computing and artificial intelligence were built.The means and efficiency of routine supervision of Internet financial risks were enhanced and optimized,and factual basis and data reference for the regulatory agencies’ decision-making was provided.关键词：big data technology;multivariate heterogeneous information;smoke index;Internet finance;risk monitoring1645|1567|0更新时间：2018-07-15
APPLICATION
- 摘要：In view of bottlenecks faced by big data analysis and application in China,such as weak big data mining and analysis ability,low big data algorithm application and comprehensive ability,the overall technical framework of big data analysis and application technology innovation platform was systematically introduced.The shortcomings and solutions of the five major common technologies in China's big data analysis and application were analyzed in detail.The design ideas and application directions of the four supporting platforms in the innovation platform were introduced.Finally,the future development direction and key work of the National Engineering Laboratory for Big Data Analysis and Application were introduced.关键词：big data;data processing;quality control;data mining;visual analytics;intelligent data management;National Engineering Laboratory1196|1432|0更新时间：2018-07-15
COLUMN：NATIONAL ENGINEERING LABORATORY FOR BIG DATA
- 摘要：The conventional transformation of production technology and equipment has been unable to further improve the energy efficiency of enterprises.The challenges in energy saving were analyzed.Under the economic and social background,energy saving solutions for enterprises were provided by energy saving big data platform,the data of industrial were capitalized,and the big data industry benchmarks and core algorithms were excavated to provide energy saving solutions for industrial enterprises.At present,the platform has been widely used in many industries.关键词：energy efficiency;energy saving big data platform;energy saving and reduce consume413|723|0更新时间：2018-07-15
COLUMN：2017 TOP 10 PRACTICES OF BIG DATA APPLICATION
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