Sparse Allreduce: Efficient Scalable Communication for Power-Law Data

Many large datasets exhibit power-law statistics: The web graph, social networks, text data, click through data etc. Their adjacency graphs are termed natural graphs, and are known to be difficult to partition. As a consequence most distributed algorithms on these graphs are communication intensive. Many algorithms on natural graphs involve an Allreduce: a sum or average of partitioned data which is then shared back to the cluster nodes. Examples include PageRank, spectral partitioning, and many machine learning algorithms including regression, factor (topic) models, and clustering. In this paper we describe an efficient and scalable Allreduce primitive for power-law data. We point out scaling problems with existing butterfly and round-robin networks for Sparse Allreduce, and show that a hybrid approach improves on both. Furthermore, we show that Sparse Allreduce stages should be nested instead of cascaded (as in the dense case). And that the optimum throughput Allreduce network should be a butterfly of heterogeneous degree where degree decreases with depth into the network. Finally, a simple replication scheme is introduced to deal with node failures. We present experiments showing significant improvements over existing systems such as PowerGraph and Hadoop

Application of e-Procurement in Fraud Prevention and it’s Implications in Circular Economy

This study aim to know and determine the application of e-procurement to fraud prevention for it’s implication of a circular economy. This research is using qualitative research. The data collected by using Web scraping, by mining the data from news articles on the internet and the research about of 2,237 news articles. This study is using Natural Language Processing (NLP) between humans and computers, Bigram as a text and language processing to identify topics in news articles by using topic modelling with LDA or Latent Dirichlet Allocation method to determine the trend topic. The result from the research shows that implementation of e-procurement is considered as a way to improve the wheels of economy

Upaya meningkatkan hasil belajar siswa dengan Model numbered heads together (nht) pada mata pelajaran pkn dengan materi Globalisasi di kelas iv Min sei agul Medan

Tujuan penelitian ini adalah untuk mneingkatkan hasil belajar siswa pada mata peljaraan PKN materi Globalisasi dengan Mpodel Numbered Heads Together pada mata Pelajrana PKN Materi Globalisasi di kelas IV Min Sei Agul Medan