After testing Parallels with memory allocations of 512 RAM, 1 GB RAM, and 2 GB RAM, along with testing with multiple CPU/Core configurations, we came to some definite conclusions.
For the purposes of benchmark testing, the amount of RAM had little influence on overall performance. Yes, allocating more RAM did generally improve benchmark scores, but not at a substantial enough rate to warrant depriving the host OS (OS X) of RAM that it could put to better use.
Remember, though, that while we didn't see big improvements, we only tested the guest OS using benchmark tools. The actual Windows applications that you use may indeed be able to perform better with more RAM available to them. However, it's also clear that if you use your guest OS to run Outlook, Internet Explorer, or other general applications, you probably won't see any improvement by throwing more RAM at them.
The biggest performance increase came from making additional CPUs/Cores available to the Parallels guest OS. Doubling the number of CPUs/Cores didn't produce a doubling in performance. The best performance increase came in the Integer test, with a 50% to 60% increase when we doubled the number of available CPU/Cores. We saw a 47% to 58% improvement in the Floating Point test when we doubled the CPUs/Cores.
However, because the Overall score includes memory performance, which saw little change, or in the case of Stream test, a decline as CPUs/Cores were increased, the Overall percentage improvement only ranged from 26% to 40%.
We were looking for two RAM/CPU configurations to use for the rest of our tests, the worst performing and best performing. Remember that when we say 'worst,' we're only referring to performance in the Geekbench benchmark test. The worst performance in this test is actually decent real-world performance, usable for most basic Windows applications, such as email and web browsing.
- Worst: 512 MB RAM and 1 CPU
- Best: 1 GB RAM and 4 CPUs