Parallelism

mental ray has been designed to take full advantage of parallel hardware. On multiprocessor machines that provide the necessary facilities, it automatically exploits thread parallelism where multiple threads of execution access shared memory. No user intervention is required to take advantage of this type of parallelism. mental ray is also capable of exploiting thread and process level parallelism where multiple threads or processes cooperate in the rendering of a single image but do not share memory. This is done using a distributed shared database that provides demand-driven transparent sharing of database items on multiple systems. [1] This allows parallel execution across a network of computers for distributed rendering.

mental ray also supports hyperthreading on Intel Pentium 4 processors if enabled. Hyperthreading is a technique that runs a second thread, including a separate process counter, on a single CPU chip to exploit otherwise idle execution units on the chip. Since this increases memory access frequency and reduces locality of reference, hyperthreading achieves a performance increase of only about 15-25%. Early machines with hyperthreading support are not very reliable, so most vendors disable hyperthreading in their hardware, BIOS, or operating system even though the CPU supports it. mental ray will not pull a license for a hyperthreading companion thread.

Distributed Rendering

A mental ray renderer that is started on a host to read or translate the scene, or is executed in application software it is integrated in, may be used as a master to utilize remote machines as slave renderers to contribute to the rendering of the current image and reduce the overall rendering time. mental ray needs to be available as a service on the remote machines to support distributed rendering.

The master is responsible for connecting to all other machines, assigning the rendering of a specific tile of the image to a slave, transporting the requested scene data to the remote host, and collecting the final results back on the master to write the complete image.

The slave is always tied to a specific master, message communication and resource usage is typically managed by the master. The machine of a slave may be used by another user at the same time; systems do not become unavailable for other jobs if used as slaves. However, running a mental ray slave on a host may degrade the performance of independent interactive application programs such as modelers on that host significantly. If a slave aborts rendering, the entire network participating in the render (the master and all slaves) will be notified and abort as well. mental ray periodically checks the health of all hosts on the master/slave network.

The list of remote machines for distributed rendering can be provided to the master in several ways.

The host names or addresses can be stored in a file named either .ray3hosts or .rayhosts. mental ray will search for such a file in the local directory and in the directory pointed to by the environment variable $HOME (on Windows: %HOMEDRIVE%%HOMEPATH%), in that order. Each line contains a hostname, an optional colon-separated port number of the service to connect to, and an optional whitespace-separated command line parameter list that is passed to the slave upon start-up. The first line that literally matches the name of the master host is ignored; this allows all hosts on the network to share a single .rayhosts file, each ignoring the first reference to itself. Empty lines or lines starting with the comment character # will be skipped. Only masters ever access the host list.
If the command line option -hosts is used to start mental ray then the .rayhosts file is ignored, and the list of slave hosts is taken from the command line instead. In this case, no hosts are ignored.
The integrated version of mental ray may get its host list directly set from the application using API functions.

[1] The parallel rendering technology which is required for the support of distributed shared databases has been originally developed by mental images as part of the ESPRIT Project 6173 Design by Simulation and Rendering on Parallel Architectures (DESIRE). See Herken94.