Note: If your existing version is MLwiN 2.10 Beta and you wish to install the latest MLwiN, we recommend uninstalling this version before installing a new one.
MLwiN 2.10 (and subsequent versions) can be installed on the following operating systems:
If you would like to install MLwiN 2.10 on an earlier operating system than shown on the list above, you will need to download our pre-XP installer (msi, 5.4 mb). and install this on your system before you download MLwiN.
32 Mb RAM; 100Mb hard disk.
The actual amount of memory and disk space required will depend on the data being analysed.
MLwiN is Windows-only software and therefore will not run natively on these machines. There are three options for running on these systems detailed below:
The following commands are required to install MLwiN in Wine (this assumes that Wine is installed and that the MLwiN installer is in the current directory):
msiexec -i MLwiN.msi
You should then be able to run MLwiN with the command:
wine <full path to mlwin.exe>
If you want to avoid the wine prefix and are running Linux you can use the command as root:
echo ':DOSWin:M::MZ::/usr/bin/wine:' > /proc/sys/fs/binfmt_misc/register
If you are going to run more than one Windows application in a session you can improve startup times with the following command at the beginning of the session:
This method requires that you have a valid Windows license.
If you are using Mac OS X the installation can be automated with Boot Camp (http://www.apple.com/support/bootcamp/).
If you are running Linux then you have to either partition your hard drive, or install a second one and then set up Windows on this drive.
There are a variety of software packages that will allow you to set up a virtual Windows PC. These are both commercial (for example www.vmware.com/products/fusion/ or www.parallels.com) or free (for example Oracle's VirtualBox) All of these require a legal copy of Windows to use. Instructions for VirtualBox are given below.
Although MLwiN should work on these systems it is not possible for us to test every combination.
If you do experience problems then it is possible to use virtualisation software such as Virtual PC 2007 or VMware to enable you to run Windows XP along side your normal operating system, for the purposes of running MLwiN. If you have Windows 7 Professional or higher then you can make use of Windows XP Mode.
Although MLwiN is a 32-bit application running it on a 64-bit machine will allow it to access 4Gb of address space, rather than the usual 2Gb. This should allow smoother processing and manipulation of larger datasets.
MLwiN has been designed for a single CPU and is single-threaded. In multi-processor environments the most benefit MLwiN would gain would be that it could have one of the CPUs to itself without having to fight with other applications and the operating system.
Redesigning MLwiN to take advantage of multiple processors would be a major undertaking, for which we have no immediate plans.
We are currently re-designing our network, which means that our MLwiN users will have to access the data MLwiN uses through a Citrix-"window" and they will not be allowed to put the data onto their local hard disk. This means that MLwiN cannot run on their computers but must reside in the secure network, and either be processed on the Citrix-server/Citrix-desktop, or running on a dedicated application-server
We do not have a Citrix system here to test MLwiN on, so cannot give a definitive answer, however we have had reports of people using MLwiN successfully on this and similar systems. MLwiN 2.10 should have more success that previous versions as it no longer attempts to write files temporarily to its program directory.
One thing to note is that MLwiN loads the whole data set being analysed into memory, so if your users are running models on large data sets on the same machine you may run into memory issues.
Running more complex models can also be quite CPU intensive. Whether this is an issue for you will depend on the number of processors in your server machine and the number of simultaneous MLwiN users. Each instance of MLwiN can only make use of a single processor, so as long as the number of copies running a model is less than or equal to the number of processors in the machine there should be no slowdown compared with running it on the user's machine.