I noticed an interesting problem. If I run the following code in R 2.12.0 (32-Bit) on a windows 3.00 gHz Core 2 Duo CPU with 2GB of RAM, it runs in less than one second. If I run it on a unix-box with sparc-sun-solaris2.10 (Also 32-Bit, though the unix box could run 64-bit) it takes 84 seconds. The processing speed of the unix box is 2.5 gHz. If I run top while the code is running, I noticed that my R process is only taking up to ~3.2% of available cpu states, even if more are available. Could this be part of the problem? I read the install manual, but nothing jumped out at me as the obvious solution to my problem. Is the unix operating system somehow limiting available resources while windows is not? Or, is there some preferable way to compile R from source that was not done? I apologize if I have not given enough information to answer the problem, this is not really my area of expertise.
t0 <- proc.time()[[3]]
x <- rnorm(10000)
for(i in 1:10000){
sd(x)
}
print(proc.time()[[3]]-t0)
Processors such as the T1 or T2 have a number of cores, and each core has a number of strands (hardware-level context switching). If you can run a multithreaded application, you’ll get a large throughput. A typical intended use case would be a Java based web server, processing e.g. 20-40 connections at the same time.
The downside of this type of processors is that single threaded performance of these SPARC chips is quite low. It looks like Oracle is aware of the issue; the current development on T4 focuses on improving the single threaded speed.
The T1 processor exposes 32 logical CPUs to the operating system. If this was your case, and the displayed value was the percent of total computing power, 1/32 ~= 3.125%, which is close to what you saw.
To squeeze all the performance from a T1 processor, you need to make R use multiple CPUs, for example via the multicore package.