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Kepler's implementation should be pretty much the same, but with doubled throughput per L2 partition.
Kepler's implementation should be pretty much the same, but with doubled throughput per L2 partition.
Jawed
Legend
I'd like to see some actual performance investigation before claiming that GK104 sucks on compute. And I think we should be mindful that NVidia appears to be saying that an evolution of this compute architecture is its long term plan.
Minimal dynamic scoreboarding is a key concept for the future. There's no option but to track long latencies (such as off-chip) but scoreboarding every instruction, last seen in Fermi, seems to be a dead concept for NVidia.
So, then you're left with a question of multi-issue. As far as I can tell, NVidia is quite explicit in stating that multi-issue is its future. Long instruction words are where it's headed. The compiler will be in the mix.
NVidia is aiming for the knee of the curve "ALU utilisation efficiency" not the highest point on it. The future is power efficiency, not ALU utilisation efficiency.
The stuff that gets instructions executing in Fermi is too costly to carry forward. It would be a case of tail wagging the dog if left that way for the future.
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That's not to say that NVidia can't tweak the current SMX layout. e.g. narrower SIMDs (but the same number) reducing the count of hardware threads required to avoid pure ALU stalls. But with essentially no data out there we've got no idea what the actual bottlenecks are.
Minimal dynamic scoreboarding is a key concept for the future. There's no option but to track long latencies (such as off-chip) but scoreboarding every instruction, last seen in Fermi, seems to be a dead concept for NVidia.
So, then you're left with a question of multi-issue. As far as I can tell, NVidia is quite explicit in stating that multi-issue is its future. Long instruction words are where it's headed. The compiler will be in the mix.
NVidia is aiming for the knee of the curve "ALU utilisation efficiency" not the highest point on it. The future is power efficiency, not ALU utilisation efficiency.
The stuff that gets instructions executing in Fermi is too costly to carry forward. It would be a case of tail wagging the dog if left that way for the future.
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That's not to say that NVidia can't tweak the current SMX layout. e.g. narrower SIMDs (but the same number) reducing the count of hardware threads required to avoid pure ALU stalls. But with essentially no data out there we've got no idea what the actual bottlenecks are.
Could we assume that NV has gained enough statistical data in compute workloads through the years, so they now feel more confident in "deferring" the complex scheduling in software? That would imply their architecture design philosophy in the G80~Fermi time-frame was guided by more cautious (but expensive) approach. Of course, this only affirms their perceived dedication to the parallel computing market.
The 680 v 580 comparison is sufficient evidence. They both need to feed their ALUs and one obviously does so more effectively in compute workloads.
That's all well and good but again actual performance carries more weight than what we think it should be doing.
You're right, the underlying reasons could be many. That doesn't change my point that a GK110 could be much faster at compute without being that much faster in games. Even if we discount the impact of the compiler and dual-issue the other potential culprits (caches, registers) you're raising aren't necessarily problems when processing the uniform workloads presented by current 3D games.
What I'm saying is actually very simple. GK104 kicks GF110 in the teeth in games but falls behind significantly in certain compute workloads relative to its peak performance. It's clear that nVidia has managed (intentionally or not) to cripple compute throughput without impacting 3D performance to the same extent. It's then likely that they can address those deficiences and restore compute performance without benefitting 3D performance to the same degree.
I could be and probably am wrong on the main culprits. Maybe it's not the compiler or the ILP requirement. Maybe it's the size of the register file or specific instructions that are responsible. Whatever it is, games aren't suffering from it and that's the gist of my point.
Since they can't hand-tune their compiler for every HPC workload imaginable I would be really surprised if they kept the static scheduling and dual-issue in the parts targeted for that market. It's one thing to explain to Anand that they havent optimized for LuxMark. It's a whole other ballgame trying to explain to paying customers why performance sucks and/or is dramatically inconsistent.
One thing to take into consideration - to my understanding GK104's FP64 ALUs (they're separate) can't be used for anything else - is it how likely that GK110 will employ the same design?
I mean, if we assume ~500mm^2 size, give or take few 10mm^2's, there's only so much room left - they need to have at least 96 FP64 units per SMX to get 1/2 ratio, and FP64 ALUs surely are bigger than FP32 ones, meaning that each SMX should be a LOT bigger, not to mention everything else the chip needs to have over GK104 to improve GPGPU speed
I mean, if we assume ~500mm^2 size, give or take few 10mm^2's, there's only so much room left - they need to have at least 96 FP64 units per SMX to get 1/2 ratio, and FP64 ALUs surely are bigger than FP32 ones, meaning that each SMX should be a LOT bigger, not to mention everything else the chip needs to have over GK104 to improve GPGPU speed
Jawed
Legend
http://mediasite.colostate.edu/Medi....aspx?peid=22c9d4e9c8cf474a8f887157581c458a1d
Start at 21 minutes in.
Welp, maybe the idea is to see what LuxMark and games have in common (for example). Both categories seem to run pretty well on ATI's older, VLIW tainted chips...so either we assume that NV's compiler people are a bunch of dopes who can't handle a much simpler case properly, or there's a (bunch of) hidden variable(s) that mess up our nice assumed 1:1 relation.
Then what's the reasoning not doing so on GK104?
It must be great to live in a world of uni-dimensional problems where everything can be proven with a single explanation.trinibwoy said:
The point that games are doing well and compute does not points to other factors than the compiler, IMHO.
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I meant the fact that GK104 has 8 FP64-only CUDA cores
Like I said, whether it's the compiler, dual-issue, a combination of both or any other hidden variables (for which we have no evidence) is tangential to my point that GK110's advantage in games will probably pale in comparison to its advantage in (SP) compute.
Life really is simple sometimes. nVidia has openly said they did not optimize for certain workloads. It's obvious that the 680 requires more hand holding than the 580. Thats the information we have.
To be honest, I'm not entirely sure that GK104 (or GF104, for that matter) actually has dedicated FP64-only ALUs. This may just be a convenient way for NVIDIA to represent FP64 capability on neat little diagrams.
I doubt so many reputable reviewers would be saying it has 8 FP64-only ALUs if it didn't
itsmydamnation
Veteran
Is a 32bit MADD/FMA ALU exactly 1/2 of a 64bit MADD/FMA ALU ( ie there are no extra bits needed to calculate to that precision?). Does it change the way the registers and caches load and store data etc? If there are difference like the above and they cost more power and die space then thats a likely explanation.
There are a lot of differences between 32 bit and 64 bit floating point. For example, the mantissa in a 32-bit float is 23 bits stored, 24 bits unpacked. The mantissa in a 64-bit float is 52 bits stored, 53 bits unpacked.
So, you need more than twice the bits in the adder and multiplier for double precision. Also, remember that the hardware cost of a fast adder grows superlinearly with the number of bits (n log n) and the hardware cost of a multiplier is even worse (n^2).
Just to illustrate, if the multiplier in a unit which operates on 32-bit floats costs n transistors, the multiplier in a unit which operates on 64-bit floats costs (53/24)^2 =4.9n transistors. This is an oversimplification, but it gives you a sense of the way the problem scales.
Is the reduction in ray tracing performance in GK104 not enough evidence for you?
Dodge.
All I am saying is that the compiler is not to blame for GK104's sucky compute performance. It's cache subsystem and the register file size vs ALU size trade off made here. It has too little RF and cache to do justice to it's ALUs in compute.
Static scheduling is not going anywhere. It's here to stay.
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