When loading the dataset in parallel, the structured extent of the dataset is distributed among all processes in a load-balanced way. vti file format stores regular structured image data, in most cases a 3D grid of point and/or cell values. Most details given below on how file formats are handled are based on descriptions taken from that page: See this ParaView page for up-to-date information on file formats and parallel data distribution. Below we list a few file format readers that do offer automatic data distribution. Not many of the file format readers that ParaView contains support automatic and efficient data distribution, so manually decomposing data into several files might be needed. In some cases data distribution happens automatically, but might still not happen very efficiently. This can lead to long filter and render times as only some of the processes will end up doing much of the work. Depending on the type of data and the file structure and decomposition used ParaView may not end up distributing the data very evenly over the server processes. In order to take advantage of parallel processing in client-server mode the loaded data needs to be distributed over the server processes, each process only operating on part of the dataset. without explicitly connecting to a ParaView server, you actually are using the so-called "built-in" server by default. This also reveals that when you run ParaView normally, i.e. ParaView even keeps a separate list of recent files per server you connected to : This is less relevant when running client and server on the same node (as we do here), but in principle the GUI/client can be run locally on your own system, connecting to a set of server processes running on Snellius. The Memory Inspector (use View → Memory Inspector if it isn't visible) shows the server connection, including memory statistics on the individual server processesĪ more subtle point is that any file I/O operations are done on the server side by the server processes.In the Pipeline Browser the connection is shown as cs://localhost:11111, instead of the regular builtin.When in client-server mode the GUI actually looks almost identical to when running ParaView in regular mode, but two things give indication to client-server mode being active: This will show a dialog for setting the type of startup, which is Manual in this case:Ĭlick Save, and you should now be back in the Choose Server Configuration dialog, with a new entry called "localhost":īy double-clicking on the "localhost" entry we make the GUI open a connection to the server processes:įrom this point on you can load data and build up your visualization as normal. This is a one-time action, as the configuration is saved and can be recalled in future sessions.Ĭlick Add Server and use " localhost" (for example) as Name. No configuration entries are listed by default, so we need to add one. This brings up the Choose Server Configuration dialog: We can connect to the running server processes through the File → Connect option, or using the icon: In a second terminal window we launch the ParaView GUI under VirtualGL, again loading the necessary modules first: The output indicates that the processes started up successfully and that the head process is listening on TCP port 11111 for a client connection. Next, we start 4 pvserver processes using mpirun : Walk-through of starting client-server modeĪssuming we have a running remote desktop on a Snellius GPU we open a terminal within the remote desktop and load the relevant ParaView module needed to start a set of server process: Or how to distribute a set of ParaView server processes over multiple nodes. It is also a natural extension of working with the remote desktop environment on Snellius.įurther below, we'll also show details on how to run the ParaView GUI locally, connecting to a set of ParaView server processes running on Snellius. This is the easiest form of usage, as all necessary software is available on Snellius and only a VNC client to be installed locally. We will first look at how to run ParaView in client-server mode on a single Snellius GPU node, within a remote desktop. This can provide a massive speed-up, which is especially useful when working with large datasets. In client-server mode the ParaView GUI works exactly like the standalone version, but it is transparently using multiple server processes to process and visualize the loaded data in parallel. In client-server mode one or more ParaView server processes are running on one or more Snellius GPU nodes, with the ParaView GUI acting as client of those server processes.
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