4 ms·

Nvidia's new mobile superchip

8 points by flying_whale 12y ago

trsohmers 12y ago
Too bad NVIDIA's (theoretical) FLOP numbers are always single precision (which is misleading if you are comparing it to supercomputers), as their theoretical double precision FLOPs are always ~1/4th of their theoretical single precision numbers. The other problem is that the CUDA shader cores are relatively from the ARM cores, which adds signifigant latency. While this isn't really a problem for video rendering and other GPU tasks, this makes it significantly worse for any sort of processing that has a lot of random accesses (most compute-heavy workloads). I don't get why NVIDIA tries to brag about compute performance, which always under delivers compared to what they claim, when their chips are the best when it comes to what most end users actually care about... media/video processing. (Disclaimer: I am founder of a startup, http://rexcomputing.com http://rexcomputing.com, working on a new processor for high performance computing applications, which would be competing with this chip for supercomputers, but not in any mobile/consumer tech.)
- stuntprogrammer 12y ago
  In this case, I believe it's 1TF of FP16, or 500GFlops FP32. You're likely looking at 16GF FP64. I've also heard, though unconfirmed, that on the CPU side it's quad A57 + quad A53 rather than Denver derivatives.
  - trsohmers 12y ago
    For theoretical FP64 flops, it should be closer to 128GFLOPs. Assuming 10W TDP, that would put it at 12.8GFLOP/Watt, putting it right there at the (Double precision) GFLOP/Watt ratio for pretty much all the top chips for 2015 (coming from Intel, AMD, Nvidia, etc). I guess it is nice that it is an SoC, but I'm not super impressed (then again, I am biased). Anandtech (http://www.anandtech.com/show/8811/nvidia-tegra-x1-preview http://www.anandtech.com/show/8811/nvidia-tegra-x1-preview) is reporting that it is a Big.little A57/A53 combo...I'm not completely surprised that they went with off the shelf ARM cores instead of Denver, but it makes me think they are putting Denver off to the pasture (especially since they say they are not going to be going after the HPC or Server markets with it). Denver has some interesting code morphing (a la Transmeta) tech, but has in order instruction pipelining. This saves a lot of complexity for the chip, but decreases performance in most usecases (but NVIDIA claims that it is more efficient 80% of the time for the average mobile user). Maybe NVIDIA determined that out of order execution that the ARM reference A57/A53 cores provide is better for the applications they seem to be targeting with the X1 (automotive).
    - stuntprogrammer 12y ago
      For your 128GF I take it you are assuming 1:4 with FP32. That would be unexpected. E.g. in contrast to AMD parts, the recent NV parts based on Maxwell2 (such as GM204 in the gtx980) are 1:32 for FP64:FP32. I would expect that ratio to hold in this part, and the SMs are likely highly similar, giving the ~16GF number I used. I haven't seen the automotive workloads, but they strike me as repetitive and regular enough that a Denver style part would do ok. That said, I'm not shocked by the use of A57+A53. (Disclaimer: I worked on an early version of Denver on the code morphing software, and at an ARM server vendor on A57 based SOC).
mschuster91 12y ago
Last decade's supercomputer(!) in today's pocket. Really, the sheer speed at which computing technology evolves is mind-blowing. I don't even want to guess where we are in ten years...
- flying_whale 12y ago
  It's actually quite interesting to think about it. Considering Intel hitting 14nm with Broadwell, there's only a certain limit to which we can push things or make them smaller. There has to be a point of saturation with things. BUT that's where the interesting part will be. The new revolutions that spring up new manufacturing materials which can defy the limits of the current ones.

8 points by flying_whale 12y ago

Too bad NVIDIA's (theoretical) FLOP numbers are always single precision (which is misleading if you are comparing it to supercomputers), as their theoretical double precision FLOPs are always ~1/4th of their theoretical single precision numbers. The other problem is that the CUDA shader cores are relatively from the ARM cores, which adds signifigant latency. While this isn't really a problem for video rendering and other GPU tasks, this makes it significantly worse for any sort of processing that has a lot of random accesses (most compute-heavy workloads). I don't get why NVIDIA tries to brag about compute performance, which always under delivers compared to what they claim, when their chips are the best when it comes to what most end users actually care about... media/video processing. (Disclaimer: I am founder of a startup, http://rexcomputing.com http://rexcomputing.com, working on a new processor for high performance computing applications, which would be competing with this chip for supercomputers, but not in any mobile/consumer tech.)

stuntprogrammer 12y ago
In this case, I believe it's 1TF of FP16, or 500GFlops FP32. You're likely looking at 16GF FP64. I've also heard, though unconfirmed, that on the CPU side it's quad A57 + quad A53 rather than Denver derivatives.
- trsohmers 12y ago
  For theoretical FP64 flops, it should be closer to 128GFLOPs. Assuming 10W TDP, that would put it at 12.8GFLOP/Watt, putting it right there at the (Double precision) GFLOP/Watt ratio for pretty much all the top chips for 2015 (coming from Intel, AMD, Nvidia, etc). I guess it is nice that it is an SoC, but I'm not super impressed (then again, I am biased). Anandtech (http://www.anandtech.com/show/8811/nvidia-tegra-x1-preview http://www.anandtech.com/show/8811/nvidia-tegra-x1-preview) is reporting that it is a Big.little A57/A53 combo...I'm not completely surprised that they went with off the shelf ARM cores instead of Denver, but it makes me think they are putting Denver off to the pasture (especially since they say they are not going to be going after the HPC or Server markets with it). Denver has some interesting code morphing (a la Transmeta) tech, but has in order instruction pipelining. This saves a lot of complexity for the chip, but decreases performance in most usecases (but NVIDIA claims that it is more efficient 80% of the time for the average mobile user). Maybe NVIDIA determined that out of order execution that the ARM reference A57/A53 cores provide is better for the applications they seem to be targeting with the X1 (automotive).
  - stuntprogrammer 12y ago
    For your 128GF I take it you are assuming 1:4 with FP32. That would be unexpected. E.g. in contrast to AMD parts, the recent NV parts based on Maxwell2 (such as GM204 in the gtx980) are 1:32 for FP64:FP32. I would expect that ratio to hold in this part, and the SMs are likely highly similar, giving the ~16GF number I used. I haven't seen the automotive workloads, but they strike me as repetitive and regular enough that a Denver style part would do ok. That said, I'm not shocked by the use of A57+A53. (Disclaimer: I worked on an early version of Denver on the code morphing software, and at an ARM server vendor on A57 based SOC).

mschuster91 12y ago

Last decade's supercomputer(!) in today's pocket. Really, the sheer speed at which computing technology evolves is mind-blowing. I don't even want to guess where we are in ten years...

flying_whale 12y ago
It's actually quite interesting to think about it. Considering Intel hitting 14nm with Broadwell, there's only a certain limit to which we can push things or make them smaller. There has to be a point of saturation with things. BUT that's where the interesting part will be. The new revolutions that spring up new manufacturing materials which can defy the limits of the current ones.