It depends on screen size as well. I find 1440p at 24 inches (my preferred monitor size) to be really unpleasant. Likewise I find 1080p at 27" to be unpleasant.
like all things in life, it comes down to 3 inches.
It’s high time to start shutting down some of these myths. There have been too many poorly written and misleading articles published on various tech “news” websites, generating hype out of nothing. Pascal is entirely focused on HPC (high-performance compute, a.k.a. supercomputers and servers) and NVIDIA hasn’t said so much as a word about gaming. But at every turn people keep trying as hard as they can to interpret every statement as "amazing for gamers!", and every time NVIDIA specifically says “compute performance” the words somehow turn into “gaming performance” in people’s minds, leading to a lot of false impressions and expectations. I'm not saying Pascal won't have amazing gaming performance. I'm saying we have no information about Pascal's gaming performance so far. Pascal might be great for gaming, it might be rubbish. NVIDIA has said nothing on the topic, basically none of what they've said so far is really applicable to gaming.
But anyway... let’s get busting!
"10× the Performance of Maxwell GM200!"
"NVLink!"
"8-Way SLI!"
"32 GiB of Memory!"
"HBM2 (3D Memory)!"
The things NVIDIA has actually claimed specifically:
NVLink will be useful as a replacement for PCI Express in supercomputers, and will have 80 GB/s of total bandwidth shared between the CPU and the number of GPUs in the system. (NVIDIA developer blog)
NVLink can be used as a GPU-GPU interconnect without replacing PCIe as the system interconnect, which provides great benefit for HPC and multi-GPU accelerated computing algorithms. No word on what this means for regular desktop cards and multi-GPU gaming. (NVIDIA developer blog)
2× the power efficiency (performance per watt) in SGEMM operations compared to Maxwell GM200; that’s a bit out of my depth so I don’t know how relevant that is to gaming applications, but I do think it’s important to notice that NVIDIA was very specific not to claim 2× power efficiency just as a general statement, so it probably won’t be, otherwise they would have just said that. (slide from keynote)
4× FP16 performance in mixed precision mode compared to Maxwell GM200; not really relevant for gaming, though it could mean the FP32 performance of Pascal is 2× that of Maxwell, this is only speculation so I don't know why I'm even mentioning it in this section (slide from keynote)
Very roughly 10× the overall throughput for deep learning problems compared to Maxwell GM200 (slide from keynote)
Up to 32 GiB of 3D memory (HBM) in highest-end cards (and not necessarily highest-end GeForce cards) (slide from keynote)
Up to 3× the memory bandwidth of Maxwell GM200 (so, ≈1 TB/s) (slide from keynote)
8 GPUs in a future Pascal-based deep learning devkit (SLI not mentioned) (end of: https://www.youtube.com/watch?v=vdNRqZSRgfA)
So, I don’t mean to dampen the mood or say Pascal won’t be great, not at all; the reality is we have absolutely no idea how Pascal will be for gaming, there’s been no information about that topic yet. It might be only a marginal improvement, it might be totally amazing. Everything we’ve heard so far is about compute capabilities. As much as the sensationalist “news” sites across the web want to make it seem like all these things are applicable to gaming, they simply aren’t. So far the Pascal architecture seems to be entirely centered around high-performance compute and accelerated computing.
We’ll see what kind of gaming performance Pascal brings to the table in due time. For now, just sit back, relax, and be careful of what you read on the Internet.
NVIDIA has released specifications for the GP100 GPU ("Big Pascal"), as well as the NVIDIA Tesla P100, a compute acceleration module which will use the GP100 GPU.
Specifications of the GP100 GPU include:
3840 FP32 cores, 1920 FP64 cores (1/2 FP32)
Cores are arranged in to 60 groups of cores called SMs, with 64 FP32 cores and 32 FP64 cores in each group
240 texture units (4 per SM)
4096-bit HBM2 memory interface (8 × 512-bit)
4 MiB L2 cache
15.3 billion transistors
610 mm2 die area
Manufactured by TSMC on a 16 nm fabrication process
Specifications for the Tesla P100 compute accelerator include:
A GP100 GPU with 4 SMs disabled (56 out of 60 enabled), for a total of 3584 FP32 cores active (1792 FP64 cores)
A 1328 MHz base frequency and 1480 MHz boost frequency
224 texture units enabled
Up to 16 GiB of HBM2 DRAM on a full 4096-bit memory interface
300 watt TDP
5.3 FP64 TFLOPs at boost frequency (3× compared to Kepler GK110's 1.7 TFLOPs, and 25× compared to Maxwell GM200's pathetic 0.2 TFLOPs)
With FP64 = 1/2 FP32, this implies 10.6 TFLOPs in theoretical FP32 performance, which is 16% faster than the theoretical performance of a Maxwell GM200 GPU at equal frequency (1.4 GHz), and 72% faster than a 1.0 GHz Maxwell GM200 GPU (TITAN X stock frequency). Also keep in mind that this is with only 56 out of 60 SMs enabled.
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EDIT:
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Aasem55 reacted to Dredgy in 1440p vs 1080p
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