HPC Toolbox

Standard Software

I can imagine that many people who need to handle a task that requires an HPC system will not relish the idea of parallel programming. It is always worthwhile to check whether a useful piece of software already exists for the problem. If a program needs the Message Passing Interface (MPI), or is at least capable of using MPI, this is a good indication that the software is capable of running on the cluster.

DistCC [14] is an example of a project that provides a distributed compiler. This kind of compiler saves money because developers don’t need to wait while the program builds. If you need to compute number-crunching-style statistics on a cluster, the free S-Plus clone, R [15], is a useful choice. 

Finite Element Method (FEM) programs are used throughout the field of physical and mechanical simulation. Elmer [16] is a free program that can use FE methods to simulate global and structure mechanics, and it is cluster capable. 

Another field in which simulation is used heavily benefits from the Weather Research and Forecasting Model [17]. Many items of free simulation code are also available for purely scientific purposes. Clustal [18] and Emboss [19] are suites for molecular genetic simulations. APBS [20] is a program that can compute the electrochemical properties and processes of biomolecules (see Figure 4). In the field of physics, Cernlib [21] is a collection of libraries and modules made available by the CERN physics lab.

Figure 4: A protein molecule shown in VMD. VMD can interact directly with the APBS simulation software.

A handful of projects specialize in helping you convert your cluster into a rendering farm. POV-Ray [22] has supported distributed execution for many years. Also, the free 3D modeler Blender can export to the POV-Ray format or handle parallel rendering itself thanks to DrQueue [23], an open source tool designed for managing a rendering farm. 

Parallel Programming

If you are working on a very specific problem, often the only solution is to write the software yourself or to parallelize an existing program. One important paradigm for creating distributed computer systems is the Message Passing Interface (MPI), a complete programming model that supports communications between parallel processors. MPI often provides the driver interface for the high-speed networks used by large-scale parallel computers. Free MPI implementations include Open MPI [24] or MPICH2 [25]. 

Another popular paradigm is OpenMP. The OpenMP programming model mainly relies on parallel programming of multiple core systems. Special pragma directives, which the programmer adds directly to the program code, tell the computer what it can automatically parallelize. Many compilers, including GCC, offer native support for OpenMP directives.

Open Computing Language (OpenCL) has recently gained traction as an important option for cross-platform parallel computing. You’ll get a close look at coding with OpenCL in the next article in this supplement. n