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

My Beliefs

[MBCook]

OK, here is my impression from years of reading hardware sites.

The P4 has amazing floating point performance, but you have to use packed SSE2/3 to get it. For general (non-packed SSE or x86) floating point performance, the Athlon lines are strong.

If you can get a low end Athlon 64 (like one of the single channel versions) that might be great for you. They are the "budget" versions but have great FPUs, more registers if your software can use it, and are true 64-bit.

As for the Athlon (non-64), I wouldn't personally. I would think you could get a low end Athlon 64 (like I said above) for a reasonable price that would smoke it.

Last of all, the Intel compiler is designed for Intel chips (duh), but the code can be run by Athlons and Opterons and even on the AMD chips it's code is often better performing than GCC code. That said, if you get a P4, using that compiler is probably a must because it is sooooo good at seting up floating point stuff and gets much better performance (but then again, what do you expect?). So give it a try no matter what you buy, it will probably help your performance.

So those are my theories/impressions. You can get SFF PC that will hold just about any processor. Too bad money is an object because that dual-cpu Iwill Opteron SFF that will come out later this year would kill anything else in a SFF (assuming you can take advantage of the 2nd CPU with whatever you're doing, which I assume you can).

Re:My Beliefs (Continued)

[MBCook]

I have something to add that another post reminded me of. If memory latency is important to you (I know know much about numerical simulations so I don't know), then you want an x86-64 chip by AMD. Becuase of the on-die memory controller, the memory latency is substantially lower than on P4s (especially the high end P4s with the huge clock speeds).

The last thing I have to say is that as another poster pointed out, are you stuck in the Wintel world? Because the G4 and G5s (the later especially) are supposed to be VERY good at this kind of thing. So you could use a XServe G5 (pretty small) or just a normal G5 (not as small). They aren't that cheap (probably couldn't get one in your budget, but maybe used) but they should preform great. They are also true 64-bit. Also, IBM sells G5 computers, so you're not stuck buying an Apple (you might be able to get a cheaper one that way too). Not sure about the sizes of those though.

Just more stuff to think about.

IWILL Dual Opteron SFF

[DeadBugs]

You may want to look into the IWILL Dual Opteron SFF PC It's in a small form factor design like a Shuttle XPC, but with support for Dual AMD Opterons.

Even if you don't have the money for both CPU's right now...it's a good start and you could add the 2nd CPU later. This would be the most powerful small form factor number cruncher.

Re:there is a difference

[Piquan]

AMD and Intel both subscribe to the IEEE 754 standard for FPU units,

This is true for "normal" floating-point operations and SSE, but 3DNow! is not IEEE-compliant. There are also some ways to introduce non-compliance in SSE, such as the LDMXCSR, RCP, and RSQRT instructions. (The former can change over/underflow behavior, and the other two are approximation functions.)

Re:Use the GPU and a suitable language

[rgbe]

Kayvon Fatahalian et al. have a good comparison for matrix-matrix multiplication between CPU's and GPU's.
One major disadvantage of the GPU at the moment is that, as far as I know, no standard software (such as LINPACK, FFTW, etc) supports it.

Portland Compilers

[XenonOfArcticus]

Compiler support is critical. Forget GCC. It's not a high-performance compiler. Look into the CodePlay C++ compiler under Windows, or the Portland Compiler Group products under Windows and Linux.