![]() ![]() The Titan black’s driver gives the user an option to choose the double precision performance between 1:3 and 1:24 FP32 (by switching the GPU to TCC mode). The 780 Ti is physically locked at 1:24 FP32 where has the Titan Black has an ace up it’s sleeve.įor the Titan Black, the magic happens in the driver. The answer is in the double precision capabilities. ![]() So if the 780 Ti and the Titan Black are practically the same in every respect, why is there a $300 difference in their price at launch (discounting memory size difference)? (Price Sources: GTX 780 Ti, GTX Titan Black, K40) The price difference based on market prices of other GPUs with similar memory size variations should not be that big either.Īt launch, the GTX 780 Ti was priced at $699, $999 for the Titan Black and an estimated $5500 for the K40c. This doesn’t affect performance very much (at least when the sizes fit in all GPUs). You could give the Tesla a pass because it has a lower clock speed.Īll three only vary significantly in three categories. Which the 780 Ti and Titan Black sit just around 5.1 TFlops, owing to their similar clock speeds, the Tesla K40c drops in at 4.3 TFlops. With respect to single precision performance, all three are fairly in the same ball park. The 780 Ti and Titan Black even have nearly same base clock speeds (~880MHz K40c is 745MHz) and identical memory clock speeds (7GHz K40 is 6GHz). All are Kepler GK110 based GPUs, with the same number of SMX and cores (15 SMX, 2880 cores) and the same bus width (384-bit). Lets take three almost identical cards: GTX 780 Ti, GTX Titan Black and the Tesla K40c. How double precision performs really depends on the architecture of the GPU. The numbers we discuss below will all be compute-bound performance numbers. If the algorithms are memory bound, such as matrix transpose, then most GPUs will attain the 1:2 performance. Keep in mind, for compute-bound algorithms, such as GEMM and FFT, the theoretical best case for FP64 performance is 1:2 FP32, simply because it involves computing with double the number of bits as FP32. Which means in an ideal case, running the same code by only changing float types to double types, would yield the single precision run time to be about 1/24th of the double precision time (time(FP32) = time(FP64)/24). So vendors like NVIDIA and AMD do not cram FP64 compute cores in their GPUs.įor example, on a GTX 780 Ti, the FP64 performance is 1/24 FP32. This is because they are targeted towards gamers and game developers, who do not really care about high precision compute. GPUs, at least consumer grade, are not built for high performance FP64. The Achilles heel is when it comes to 64-bit double precision math. For 2160p 4K, we were able to play Overwatch 2, Valorant at 61 fps to 129 fps and kept frame rates hovering around 95 fps.GPUs are really good at doing math. For 1080p Full HD, we were able to play Need For Speed: Heat, Just Cause 4, Shadow of the Tomb Raider, Call of Duty: Black Ops Cold War, Gears of War 5 at 67 fps to 72 fps and kept frame rates hovering around 69 fps.įor 1440p Quad HD, we were able to play Call of Duty: Black Ops 4, Death Stranding, F1 2019, Far Cry New Dawn, Apex Legends at 62 fps to 67 fps and kept frame rates hovering around 65 fps. The GTX 1660 consistently delivers great frame rate increases over the GTX 1060 6GB and it really justifies an upgrade. ![]() Spec for spec, this GTX 1660 leapfrogs its direct predecessor, the GTX 1060 6GB, by boasting 28.2 % more fps.įortunately, gaming performance was quite impressive. Meanwhile, the closest equivalent card is the which costs. Compare this to the GTX 1060 6GB, which came originally at a price of $ 254. The GTX 1660 is much more cheaper than the GTX 1060 6GB as it costs $ 220. After taking the time to fully test the Turing graphics card inside the GTX 1660, we can say without a doubt that it continues the trend. NVIDIA ’s x圆0 cards have always been defined by entry-level prices with performance that knocks on the door of mid-range graphics cards – especially when overclocked. The good news is, with the release of the GTX 1660 Ti, the GTX 1660 's price is getting more discount. The overall score is determined based on the calculated weightings for the individual components. The higher the better for higher resolution textures and future The higher the better.Ĭurrent CPU Impact on performance with respect to the highest performing CPU used for benchmark at the The higher the better.ĤK performance at 2160p resolution. The lower the better.įull HD performance at 1080p resolution. The lower the better for longer life of the graphics card. Power Supply Wattage required for overall system. The newer the better technology and performance optimization and
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