Overclocking

For our final evaluation of the GTX 1080 and GTX 1070 Founders Edition cards, let’s take a look a overclocking.

Whenever I review an NVIDIA reference card, I feel it’s important to point out that while NVIDIA supports overclocking – why else would they include fine-grained controls like GPU Boost 3.0 – they have taken a hard stance against true overvolting. Overvolting is limited to NVIDIA’s built in overvoltage function, which isn’t so much a voltage control as it is the ability to unlock 1-2 more boost bins and their associated voltages. Meanwhile TDP controls are limited to whatever value NVIDIA believes is safe for that model card, which can vary depending on its GPU and its power delivery design.

For GTX 1080FE and its 5+1 power design, we have a 120% TDP limit, which translates to an absolute maximum TDP of 216W. As for GTX 1070FE and its 4+1 design, this is reduced to a 112% TDP limit, or 168W. Both cards can be “overvolted” to 1.093v, which represents 1 boost bin. As such the maximum clockspeed with NVIDIA’s stock programming is 1911MHz.

GeForce GTX 1080FE Overclocking
  Stock Overclocked
Core Clock 1607MHz 1807MHz
Boost Clock 1734MHz 1934MHz
Max Boost Clock 1898MHz 2088MHz
Memory Clock 10Gbps 11Gbps
Max Voltage 1.062v 1.093v

 

GeForce GTX 1070FE Overclocking
  Stock Overclocked
Core Clock 1506MHz 1681MHz
Boost Clock 1683MHz 1858MHz
Max Boost Clock 1898MHz 2062MHz
Memory Clock 8Gbps 8.8Gbps
Max Voltage 1.062v 1.093v

Both cards ended up overclocking by similar amounts. We were able to take the GTX 1080FE another 200MHz (+12% boost) on the GPU, and another 1Gbps (+10%) on the memory clock. The GTX 1070 could be pushed another 175MHz (+10% boost) on the GPU, while memory could go another 800Mbps (+10%) to 8.8Gbps.

Both of these are respectable overclocks, but compared to Maxwell 2 where our reference cards could do 20-25%, these aren’t nearly as extreme. Given NVIDIA’s comments on the 16nm FinFET voltage/frequency curve being steeper than 28nm, this could be first-hand evidence of that. It also indicates that NVIDIA has pushed GP104 closer to its limit, though that could easily be a consequence of the curve.

Given that this is our first look at Pascal, before diving into overall performance, let’s first take a look at an overclocking breakdown. NVIDIA offers 4 knobs to adjust when overclocking: overvolting (unlocking additional boost bins), increasing the power/temperature limits, the memory clock, and the GPU clock. Though all 4 will be adjusted for a final overclock, it’s often helpful to see whether it’s GPU overclocking or memory overclocking that delivers the greater impact, especially as it can highlight where the performance bottlenecks are on a card.

To examine this, we’ve gone ahead and benchmarked the GTX 1080 4 times: once with overvolting and increased power/temp limits (to serve as a baseline), once with the memory overclocked added, once with GPU overclock added, and finally with both the GPU and memory overclocks added.

GeForce GTX 1080FE Overclocking Breakdown

GeForce GTX 1080 Overclocking Performance
  Power/Temp Limit (+20%) Core (+12%) Memory (+10%) Cumulative
Tomb Raider
+3%
+4%
+1%
+10%
Ashes
+1%
+9%
+1%
+10%
Crysis 3
+4%
+4%
+2%
+11%
The Witcher 3
+2%
+6%
+3%
+10%
Grand Theft Auto V
+1%
+4%
+2%
+8%

Across all 5 games, the results are clear and consistent: GPU overclocking contributes more to performance than memory overclocking. To be sure, both contribute, but even after compensating for the fact that the GPU overclock was a bit greater than the memory overclock (12% vs 10%), we still end up with the GPU more clearly contributing. Though I am a bit surprised that increasing the power/temperature limit didn't have more of an effect.

OC: Rise of the Tomb Raider - 3840x2160 - Very High Quality (DX11)

OC: Ashes of the Singularity - 3840x2160 - Extreme Quality (DX12)

OC: Crysis 3 - 3840x2160 - Very High Quality + FXAA

OC: The Witcher 3 - 3840x2160 - Ultra Quality (No Hairworks)

OC: Grand Theft Auto V - 3840x2160 - Very High Quality

OC:  Grand Theft Auto V - 99th Percentile Framerate - 3840x2160 - Very High Quality

Overall we’re looking at an 8%-10% increase in performance from overclocking. It’s enough to further stretch the GTX 1080FE and GTX 1070FE’s leads, but it won’t radically alter performance.

OC: Load Power Consumption - Crysis 3

OC: Load Power Consumption - FurMark

OC: Load GPU Temperature - Crysis 3

OC: Load GPU Temperature - FurMark

OC: Load Noise Levels - Crysis 3

OC: Load Noise Levels - FurMark

Finally, let’s see the cost of overclocking in terms of power, temperature, and noise. For the GTX 1080FE, the power cost at the wall proves to be rather significant. An 11% Crysis 3 performance increase translates into a 60W increase in power consumption at the wall, essentially moving GTX 1080FE into the neighborhood of NVIDIA’s 250W cards like the GTX 980 Ti. The noise cost is also not insignificant, as GTX 1080FE has to ramp up to 52.2dB(A), a 4.6dB(A) increase in noise. Meanwhile FurMark essentially confirms these findings, with a smaller power increase but a similar increase in noise.

As for the GTX 1070FE, neither the increase in power consumption nor noise is quite as high as GTX 1080FE, though the performance uplift is also a bit smaller. The power penalty is just 21W at the wall for Crysis 3 and 38W for FurMark. This translates to a 2-3dB(A) increase in noise, topping out at 50.0dB for FurMark.

Power, Temperature, & Noise Final Words
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  • Robalov - Tuesday, July 26, 2016 - link

    Feels like it took 2 years longer than normal for this review :D Reply
  • extide - Wednesday, July 27, 2016 - link

    The venn diagram is wrong -- for GP104 it says 1:64 speed for FP16 -- it is actually 1:1 for FP16 (ie same speed as FP32) (NOTE: GP100 has 2:1 FP16 -- meaning FP16 is twice as fast as FP32) Reply
  • extide - Wednesday, July 27, 2016 - link

    EDIT: I might be incorrect about this actually as I have seen information claiming both .. weird. Reply
  • mxthunder - Friday, July 29, 2016 - link

    its really driving me nuts that a 780 was used instead of a 780ti. Reply
  • yhselp - Monday, August 8, 2016 - link

    Have I understood correctly that Pascal offers a 20% increase in memory bandwidth from delta color compression over Maxwell? As in a total average of 45% over Kepler just from color compression? Reply
  • flexy - Sunday, September 4, 2016 - link

    Sorry, late comment. I just read about GPU Boost 3.0 and this is AWESOME. What they did, is expose what previously was only doable with bios modding - eg assigning the CLK bins different voltages. The problem with overclocking Kepler/Maxwell was NOT so much that you got stuck with the "lowest" overclock as the article says, but that simply adding a FIXED amount of clocks across the entire range of clocks, as you would do with Afterburner etc. where you simply add, say +120 to the core. What happened here is that you may be "stable" at the max overclock (CLK bin), but since you added more CLKs to EVERY clock bin, the assigned voltages (in the BIOS) for each bin might not be sufficient. Say you have CLK bin 63 which is set to 1304Mhz in a stock bios. Now you use Afterburner and add 150 Mhz, now all of a sudden this bin amounts to 1454Mhz BUT STILL at the same voltage as before, which is too low for 1454Mhz. You had to manually edit the table in the BIOS to shift clocks around, especially since not all Maxwell cards allowed adding voltage via software. Reply
  • Ether.86 - Tuesday, November 1, 2016 - link

    Astonishing review. That's the way Anandtech should be not like the mobile section which sucks... Reply
  • Warsun - Tuesday, January 17, 2017 - link

    Yeah looking at the bottom here.The GTX 1070 is on the same level as a single 480 4GB card.So that graph is wrong.
    http://www.hwcompare.com/30889/geforce-gtx-1070-vs...
    Remember this is from GPU-Z based on hardware specs.No amount of configurations in the Drivers changes this.They either screwed up i am calling shenanigans.
    Reply
  • marceloamaral - Thursday, April 13, 2017 - link

    Nice Ryan Smith! But, my question is, is it truly possible to share the GPU with different workloads in the P100? I've read in the NVIDIA manual that "The GPU has a time sliced scheduler to schedule work from work queues belonging to different CUDA contexts. Work launched to the compute engine from work queues belonging to different CUDA contexts cannot execute concurrently." Reply
  • marceloamaral - Thursday, April 13, 2017 - link

    Nice Ryan Smith! But, my question is, is it truly possible to share the GPU with different workloads in the P100? I've read in the NVIDIA manual that "The GPU has a time sliced scheduler to schedule work from work queues belonging to different CUDA contexts. Work launched to the compute engine from work queues belonging to different CUDA contexts cannot execute concurrently." Reply

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