Technology advances at an astounding rate. Every few months new, more powerful machines appear on the market. The market situation is therefore in continuous evolution, and one should always try to decide what to buy as closely as possible to the day at which the purchase is actually made.
Trying to select the ``best computer for MD'' is never easy. The choice is always conditioned by various factor, such as
Nevertheless, performance remains perhaps the most important point! To evaluate performance, it is common to use benchmarks: programs which accomplish a certain task (sometimes very simple), are never (or seldom) modified, and are run in controlled conditions. When running a benchmark on a machine for evaluation, the execution time is measured, and the output is compared with a reference output to make sure that the machine produced the correct result.
There are many scientific benchmarks around. The most well known are the Linpack benchmark, and the SPEC program suite. A problem is that different machines behave differently on different programs. In other words, the ratio between the execution time of two different benchmarks can vary widely between one machine architecture and another. Linpack, for instance, is a linear algebra benchmark. Machines which are able to perform matrix multiplications very efficiently--perhaps due to a special organization of their floating point unit or to compilers highly optimized for this problem--will obtain a very good Linpack score. While extremely representative of an important class of physical problems (for instance those in which diagonalizations are involved), this is of limited usefulness to assess MD performance, since there is no linear algebra in classical MD!
The other extreme, and by far the best choice, is to run yourself a copy of the program you are going to use on the machines you are interested in. This will not only give you an idea of a machine's performance, but also of how easy is using it. However, this is often impractical to do, due to the need to find access to these computers, and the time to run the program on each of them and verify the results.
To partially relieve this problem, the author developed in 1988 a molecular dynamics benchmark called MDBNCH . A database of execution times on several machines has been collected over the years, and it keeps growing thanks to the contribution of many people. Keeping in mind that this benchmark may not exactly represent the applications which you are interested to run, it is probably an indicator of molecular dynamics performance more accurate than the more general benchmarks available around.