TSMC expects 5nm by 2020, and 10nm to be profitable by 2017

TSMC is working towards EUV for 5nm by 2020, while 10nm will be profitable by the end of 2017.

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TSMC has been hitting its stride this year, with the delivery of the 16nm FinFET process for NVIDIA's current GeForce GTX 1080, GTX 1070 and the soon-to-be-released GTX 1060. But what about the future?

TSMC expects 5nm by 2020, and 10nm to be profitable by 2017 | TweakTown.com

Samsung has been pushing its Extreme Ultra-Violet Lithography (EUV) for the 7nm node, but TSMC isn't far behind, with the Taiwanese giant set to start 7nm node trials by the end of 2017. TSMC's co-CEO, Mark Liu, said that the company plans to push into EUV for 5nm by the end of 2020. Liu added that the company will simplify the process, improve density and cut down on the overall costs of the new node.

TSMC has also said that it has made more than one improvement to its existing EUV infrastructure, while it claims to have implemented 125W EUV source into its ASML NXE:3350 equipment. TSMC also says it now has in-house EUV technologies for inspection, masking and repair for lithography. When it comes to 7nm, TSMC has hit integration for scanners, masks and photoresist, while they'll be adding two more EUV scanners in 2017.

The 10nm process promise is even better, with Liu saying TSMC will have 10nm generating revenues for the company by the end of 2017. Liu has said that the first 10nm product for TSMC has been hitting good yields, while 3 x 10nm customer products have been taped out so far.

NEWS SOURCE:wccftech.com

Anthony joined the TweakTown team in 2010 and has since reviewed 100s of graphics cards. Anthony is a long time PC enthusiast with a passion of hate for games built around consoles. FPS gaming since the pre-Quake days, where you were insulted if you used a mouse to aim, he has been addicted to gaming and hardware ever since. Working in IT retail for 10 years gave him great experience with custom-built PCs. His addiction to GPU tech is unwavering and has recently taken a keen interest in artificial intelligence (AI) hardware.

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