Data Parallelism

Discussion on the Parallelism and classification of Cloud Computing Tasks ZHENG Ying The aspires studies the correlation betwee n Computational data and data partitioning method when e ...

Spark is a cluster computing platform that originated at the University of California, Berkeley Amplab. It is based on memory calculation, from many iterations of batch processing, eclectic data warehouse, flow processing and graph calculation and other computational paradigm, is a rare all-round player. Spark has formally applied to join the Apache incubator, from the "Spark" of the laboratory "" EDM into a large data technology platform for the emergence of the new sharp. This article mainly narrates the design thought of Spark. Spark, as its name shows, is an uncommon "flash" of large data. The specific characteristics are summarized as "light, fast ...

Beijing time this morning, Intel (Intel) officially released the Xeon Phi (Xeon) coprocessor based on an integrated Salt Lake City (MIC) architecture at the supercomputer (SC12) Conference held in the city. One of the Xeon Phi coprocessor 5110P with the date of shipment, January 28, 2013 GA, recommended customer price of 2649 dollars; Xeon Phi Coprocessor 3,110 families will be available in the first half of 2013, advising customers price less than 2000 U.S. dollars. Intel Xeon Phi Coprocessor Home ...

"Editor's note" Deep convolution neural network has a wide range of application scenarios, in this paper, the deep convolution neural network deep CNNs multi-GPU model parallel and data parallel framework for the detailed sharing, through a number of worker group to achieve data parallelism, the same worker Multiple worker implementation models in a group are parallel. In the framework, the three-stage parallel pipelined I/O and CPU processing time are implemented, and the model parallel engine is designed and implemented, which improves the execution efficiency of the model parallel computation, and solves the data by transmits layer ...

During the 2017 YunQi Computing Conference held in Shenzhen, Alibaba Cloud’s Chief Science Officer Dr Jingren Zhou officially launched the updated version of its machine learning platform “PAI 2.0”.

The large data in the wall are registered as dead data. Large data requires open innovation, from data openness, sharing and trading, to the opening of the value extraction ability, then to the foundation processing and analysis of the open platform, so that the data as the blood in the body of the data society long flow, moisture data economy, so that more long tail enterprises and data thinking innovators have a colorful chemical role, 　　To create a golden age of big data. My large data research trajectory I have been 4-5 years of mobile architecture and Java Virtual Machine, 4-5 years of nuclear architecture and parallel programming system, the last 4-5 years also in pursuit ...

After repeated bombing by countless authoritative media, we have generally believed that data scientists are the most mysterious and sexiest of the 21st century careers, they are the bomb-breaking experts in the big Data age, digital business engines, they are worth as much as the NFL four, and they are less than the number of snow leopards on the Kunlun mountains. It is clear that the data scientists are all 18 of the most proficient in the data analysis martial arts master, but they have also been a worry recently. Not long ago, open source database Scidb developer PARADIGM4 for 111 North American ...

This article will explain why thread based programming is not the best way to implement application parallelism in a multi-core era. Moore's Law (Moore 1965 predicts that the number of components per integrated circuit doubles every 18-24 months) is still applicable, and its applicability is expected to continue into 2015-2020 years. Before 2005, the CPU clock rate also increased synchronously, which was enough to improve the performance of all applications executing on those CPUs. Http://www.aliyun.co ...

The rapid development of large data and its application has aroused extensive attention from various circles of society, and people have been thinking and talking about this great change from different perspectives. In order to carry out the work deployment of the State Council on promoting information consumption and expanding domestic demand, taking into account the actual needs of developing large data industry and the great effect of promoting information consumption and stimulating domestic demand, Through the research on the characteristics of large data-related industry and its development trend and how to accelerate the development of large data-related industries in China, we think that China is a big data country, but it is not a big data country.

There is no doubt that all the people in the world concerned about the development of technology are aware of the potential value of "big data" for business business, and the goal is to address the pain caused by the growth of business data in the process of enterprise development. The reality is that many problems hinder the development and practical application of large data technologies. Because a successful technology requires some measure of standard. Now we can measure large data technologies with a few basic elements--streaming, parallelism, summary indexing, and visualization. Who uses the big data? A year ago, some of the major users of data technology ...