CPUs/Compilers for Numerical Simulations?

X43B asks: "I'm building a 'luggable' computer for numerical simulation work (very niche, I know). My goal is to have the best single precision floating point performance for under $1000. I have decided on a Shuttle XPC layout. I can build a AMD 3500+ for ~$80 less than a Prescott 3.4Ghz. I know the AMD is supposed to be a better 'general purpose' CPU however I found this comparison which says the Intels are better for floating point. Additionally, even though the AMD is somewhat cheaper, I have found the free Intel Linux FORTRAN compiler quicker than gfortran. So even if the AMD had similar performance for cross compiling, the Intel would be ~10% faster with the free compiler. Does anyone have any recommendations on AMD vs Intel for single precision floating point operations? If you recommend the AMD, what (cheap or free) compiler can be used that is comparable to the Intel?"

Comments

Re:there is a difference

[CaptainCheese]

AMD and Intel both subscribe to the IEEE 754 standard for FPU units, which defines the functions of single and double precision FPU operations and various other things, like how to handle the inevitable rounding errors.

No FPU meeting this standard will produce different results than any other FPU. They're just faster or slower at doing it.

You'll only start getting differences when you hack non-standard speed optimisations into your code. It's unfair to blame Intel and AMD for people writing incompetently coded software - they just provide the stick, it's the coder who's beating you with it.

Intel also has great libraries & VTune

[Salis]

Intel has a set of optimized mathematical libraries for all sorts of applications (linear algebra, image processing, random number generation, FFT's, etc). Not only are they optimized for Intel systems, but they save you the time of coding it yourself.

Intel also provides the VTune Performance Analyzer, which allows you to trace the path through your programs and determine where the bottlenecks are.

I've used the Intel Linux Fortran compiler and I am very happy with it. Code that runs fine on my Sun workstation (950 Mhz, 6 gig RAM) at school works 4-5x faster on my home PC (2.8 Ghz, 1 gig RAM). It's got all the fancy optimization options, but a simple -O3 -ipo will get you 90% there.

My two bits.

CPU? Use the GPU!

[Bazman]

Maybe you just want a better graphics card? Nowadays you can run numerical calculations on the graphics card's processor - and no, you don't get random noise all over your screen, its not simple memory-mapped graphics! Plus it gives you the excuse to buy a machine that can play Doom 3.

More info here: http://www.gpgpu.org/

Whatever you do, make sure you have a properly tuned ATLAS library:

http://math-atlas.sourceforge.net/

I don't know if anyone has got ATLAS or BLAS to work on GPUs yet.

Baz