Read this interview with Dr Dobbs [ddj.com]:

A floating-point matrix multiply using the new SSE5 extensions is 30 percent faster than a similar algorithm

I believe this helps gaming and other simulations.

Discrete Cosine Transformations (DCT), which are a basic building block for encoders, get a 20 percent performance improvement

And then we have the "holy shit" moment:

For example, the Advanced Encryption Standard (AES) algorithm gets a factor of 5 performance improvement by using the new SSE5 extension

If I get one of these CPUs, I'll almost certainly be encrypting my hard drives. It was already fast enough, but now...

As for existing OS support, it looks promising:

We're also working closely with the tool community to enable developer adoption -- PGI is on board, updates to the GCC compiler will be available this week, and AMD Code Analyst Performance Analyzer, AMD Performance Library, AMD Core Math Library and AMD SimNow (system emulator) are all updated with SSE5 support.

So, if you're really curious, you can download SimNow and emulate an SSE5 CPU, try to boot your favorite OS... even though they say they're not planning to ship the silicon for another two years. Given that they say the GCC patches will be out in a week, I imagine two years is plenty of time to get everything rock solid on the software end.

The 64-bit designation refers to the width of the address bus*. For example, IA-32 processors have been able to handle 64 bit integers for ages.. so a 64-bit address-capable processor handling 128 bit numbers is nothing new.

* Yes, PAE was a slight deviation from a 32 bit address space, but in userspace, it's 32 bit flat memory.

I believe the 64-bit designation refers to the width of the general purpose registers. This usually correlates to the address space used, but has nothing to do with the address bus. The 8086, for example, while being a 16-bit processor had a 20-bit address bus. The 8088 was a 16-bit processor, but only had an 8-bit data bus to save costs. Both were 16-bit processors, because the general purpose registers (AX, BX, CX, DX) were 16-bit.

In the x64 world, the general purpose registers are 64-bit wide. This also used to influence the width of the 'int' datatype in the C compiler, although I'm not sure that 'int' is a 64-bit integer when compiling x64 code.

The 64-bit designation refers to the width of the address bus*. For example, IA-32 processors have been able to handle 64 bit integers for ages.. so a 64-bit address-capable processor handling 128 bit numbers is nothing new.

Technically, the "bit designation" of a platform is defined as the largest number on the spec sheet which marketing is convinced customers will accept as truthful. Seriously, over the years different processors and systems have been "16 bit" or "32 bit" for any number of odd and wacky reasons. for example, the Atari Jaguar was widely touted as a 64 bit platform, and the control processor was a Motorola 68000. The Sega Genesis also had a 68k in it, and was a 16 bit platform. The thing is, Atari's marketing folks decided that since the graphics processor worked in 64 bit chunks, they could sell the system as a 64 bt platform. C'est la vie. It's an issue that doesn't just crop up in video game consoles -- I just find the Jaguar a particularly amusing example.

But, yeah, having a CPU sold as one "bitness" and being able to work with a larger data size than the bitness is not unusual. The physical address bus width is indeed one common designator of bitness, just as you say. Another is the internal single address width, or the total segmented address width. Also, the size of a GPR is popular. On many platforms, some or all of those are the same number, which simplifies things.

An Athlon64, for example, has 64 bit GPR's, and in theory a 64 bit address space, but it actually only cares about 48 bits of address space, and only 40 of those bits can actual be addressed by current implimentations.

A 32 it Intel Xeon has 32 bit GPR's, but an 80 bit floating point unit, the ability to do 128 bit SSE computations, 32 bit individual addresses, and IIRC a 36 bit segmented physical address space. but, Intel's marketing knew that customers wouldn't believe it if they called it anything but 32 bit since it could only address 32 bits in a single chunk. (And, they didn't want it to compete with IA64!)

The Jaguar had a 64-bit data bus, a 32-bit CPU "Tom" connected to the GPU, a 32-bit CPU "Jerry" connected to the sound chip, and a 32-bit MC68000 with a 16-bit connection to the data bus, used as an I/O processor (in much the same way that the PS2 uses the PS1 CPU). Some games ran their game logic on "Tom"; others (presumably those developed by programmers hired away from Genesis or Neo-Geo shops) ran it on the IOP. Pretty much only graphics operations ever used the full width of the data bus.

Being thick (and out of coffee) how the hell can any thing be infinitely precise?

The result will still eventually be stored back into a floating-point number. What it means for an intermediate computation to be infinitely precise is just that it doesn't discard any information that wouldn't inherently be discarded by rounding the end result.
When you multiply two finite numbers, the result has only as many bits as the combined inputs. So it's quite possible for a computer to keep all of those bits, then perform the addition with that full precision, and then chop it back to 32bits. As opposed to implementing the same operation with current instructions, which would be: multiply, (round), add, (round).

>> And then we have the "holy shit" moment:

For example, the Advanced Encryption Standard (AES) algorithm gets a factor of 5 performance improvement by using the new SSE5 extension
If I get one of these CPUs, I'll almost certainly be encrypting my hard drives. It was already fast enough, but now...

They copied two important features from the PowerPC instruction set: Fused multiply-add (calculate +/- x*y +/- z in one instruction), and the Altivec vector permute instruction, which can among other things rearrange 16 bytes in an arbitrary way. The latter should be really nice for AES, because it does a lot of rearranging 4x4 byte matrices (if I remember correctly).

Motorola 6800x, 68010 are 16-bit designs, that is, 16-bit processors with 32-bit register file. Whenever you used 32-bit operands on those CPUs, they were slower, because it was really executing them in 16-bit parts. Bus was also 16-bits wide, but with 24 address lines. It was just a forward-thinking design hiding 16-bitness.

>> Being thick (and out of coffee) how the hell can any thing be infinitely precise? Or atleast while it can be infinitely precise how do you go about checking it... might take a while to prove it for all possible numbers (of which there is an infinite amount of, and for each one you would have to check it to an infinite number of decimal places).

I'll give you an example. Lets say we are working with four decimal digits instead of 53 binary digits, which is what standard double precision uses. Any operation will behave as if it calculated the infinitely precise result and then rounded it. For example, any result x that is in the range 1233.5 = x = 1234.5 with infinite precision will be rounded 1234.

Now lets say we calculate x * y + z with infinite precision and round. We have x = 2469, y = 0.5, and z happens to be 0.00000000001. So x * y = 1234.5, x *y + z is just a tiny bit larger, so the result has to be rounded up to 1235. To do this right, you need x * y with infinite precision. Knowing twelve decimals wouldn't be enough. If I told you "x * y equals 1234.50000000 with twelve digit precision", you wouldn't know how to round x * y + z. x * y could be 1234.499999996, and adding z would still be less than 1234.5, so it needs to be rounded down. Or x * y could be 1234.500000004, and x * y + z needs to be rounded up.

That is meant by "infinite precision": The processor guarantees to give the same result _as if_ it would use infinite precision for the calculation. In practice, it doesn't use infinite precision. About 110 binary digits precision is enough to get the same result.

The important word there is intermediate. You don't get a result of infinite precision, you get a 32-bit result (since the parent mentioned single-precision floating point). But it carries the right number of bits internally, and uses the right algorithms, so that the result is as if the processor did the multiply and add at infinite precision, and then rounded the result to the nearest 32-bit float. Which is better than the result you would get by multiplying two 32-bit floats into a 32-bit float, then adding that to another 32-bit float into a 32-bit float. You're limited to 32 bits at all times and therefore you have intermediate precision loss.

Making sense now?