Minnesota Supercomputing Institute
With regards to the safety measures put in place by the university to mitigate the risks of the COVID-19 virus, at this time all MSI systems will remain operational and can be accessed remotely as usual. The only planned outages concern our in-person Helpdesk and tutorials. More information, as well as alternative remote support options, can be found at MSI COVID-19 Continuity Plan
R2017b, R2010b, R2011a, R2011b, R2019a, R2012a, R2016b, R2012b, R2015b, R2013a, R2015a, R2013b, R2014b, R2014a
Thursday, October 3, 2019
D4M attempts to combine the advantages of five distinct processing technologies (sparse linear algebra, associative arrays, fuzzy algebra, distributed arrays, and triple-store/NoSQL databases such as Hadoop HBase and Apache Accumulo) to provide a database and computation system that addresses the problems associated with Big Data.
D4M is a library accessed through Matlab. You must be familiar with Matlab before using D4M. To use D4M on the MSI lab machines, load the matlab module and add the following lines to the top of your Matlab input, or in your startup.m file.
D4M_HOME = '/nfs/soft-el6/d4m/2.0.3' % SET TO LOCATION OF D4M.
addpath([D4M_HOME '/matlab_src']) % Add the D4M library.
Assoc('','','') % Initialize library.
If you have an accumulo database, you can access it from Matlab by defining a connection, e.g.
DB = DBserver('accumulo1:2181','Accumulo','msitest', '','')