TSMC Outlines 16nm, 10nm Plans
Jessica Lipsky
4/8/2015 00:01 AM EDT
SAN JOSE, Calif. — Taiwan Semiconductor Manufacturing Company (TSMC) announced plans to roll out a compact, low-power version of its 16nm FinFET process and revealed its road map for smaller process nodes. The company will begin volume production of its 16nm FinFET Plus (16FF+) in the middle of this year and break ground on a new 10nm fab next year.
A year after volume production of 20nm chips, TSMC announced it will begin volume production of its 16FF+ in the middle of 2015. TSMC claims the chips made using FinFET Plus have 10% better performance than competing silicon, consume 50% less power than a 20nm SoC, and have a cycle time twice that of 20nm chips.
The foundry will have more than 50 tape-outs by year’s end, covering applications processors, GPUs, automotive, and network processors, said TSMC President and Co-CEO Mark Liu said at the TSMC 2015 Technology Symposium Tuesday.
|
|
E-mail This Article |
|
Printer-Friendly Page |
Related News
- TSMC plans 1.6nm process for 2026
- TSMC Preps 10nm, Tunes 16nm
- MediaTek to Stay with TSMC for Finer-Node Chips
- TSMC Certifies Synopsys Design Tools for 16-nm FinFET Plus Production and for 10-nm Early Design Starts
- Synopsys Tools Achieve TSMC Certification for 16-nm FinFET+ Process and Entered 10-nm FinFET Collaboration
Breaking News
- RISC-V International Promotes Andrea Gallo to CEO
- See the 2025 Best Edge AI Processor IP at the Embedded Vision Summit
- Andes Technology Showcases RISC-V AI Leadership at RISC-V Summit Europe 2025
- RISC-V Royalty-Driven Revenue to Exceed License Revenue by 2027
- Keysom Unveils Keysom Core Explorer V1.0
Most Popular
- RISC-V International Promotes Andrea Gallo to CEO
- See the 2025 Best Edge AI Processor IP at the Embedded Vision Summit
- Andes Technology Showcases RISC-V AI Leadership at RISC-V Summit Europe 2025
- Ceva, Inc. Announces First Quarter 2025 Financial Results
- Cadence Unveils Millennium M2000 Supercomputer with NVIDIA Blackwell Systems to Transform AI-Driven Silicon, Systems and Drug Design






