Information Abstract:
- NVIDIA CUDA-X libraries and AI fashions are accelerating TSMC workloads throughout lithography, transistor and course of simulation, superior course of management and fab operations optimization.
- TSMC is utilizing NVIDIA Metropolis and NVIDIA TAO Toolkit to advance automated defect inspection with imaginative and prescient AI, bettering detection of nanometer-scale defects whereas lowering repeated labeling and retraining.
NVIDIA GTC Taipei—NVIDIA in the present day introduced that TSMC, the world’s main semiconductor firm, is utilizing NVIDIA accelerated computing and AI to advance semiconductor design and manufacturing.
As chips transfer to extra superior nodes, bringing them from design to high-volume manufacturing has turn out to be one of many world’s most advanced computing challenges. Computational lithography, transistor simulation, course of management and wafer inspection now require massive-scale simulation and real-time optimization, and AI programs that may present help throughout physics, photos and different purposes.
TSMC is utilizing NVIDIA applied sciences to speed up this transformation, making use of accelerated computing and AI throughout the semiconductor design and manufacturing lifecycle to enhance turnaround time, vitality effectivity, yield and operational productiveness in superior fabs.
“NVIDIA and TSMC have labored collectively for almost three a long time to push the boundaries of computing,” stated Jensen Huang, founder and CEO of NVIDIA. “TSMC is bringing NVIDIA AI and accelerated computing into the fab itself, tackling among the world’s most advanced design and manufacturing challenges with simulation, optimization and AI to enhance velocity, effectivity and yield for the subsequent era of chips.”
“TSMC and NVIDIA have constructed a long-standing partnership rooted in advancing the applied sciences that make the subsequent era of computing attainable,” stated C.C. Wei, chairman and CEO of TSMC. “By utilizing NVIDIA accelerated computing and AI throughout fab operations optimization, lithography, course of management and inspection, TSMC is strengthening our expertise management and manufacturing excellence to help our clients’ future merchandise and success.”
TSMC Accelerates Processes With NVIDIA CUDA-X Libraries and AI
Superior semiconductor design and manufacturing require huge computational workloads and extremely coordinated fab operations, spanning chip-design switch, transistor modeling, course of management and fab productiveness.
TSMC is utilizing NVIDIA CUDA-X™ libraries and AI fashions to speed up these workloads on NVIDIA GPUs:
- Computational lithography: TSMC is utilizing NVIDIA cuLitho, a GPU-accelerated library for lithography — a printing technique for chip masks design. This expertise delivers a 20-50% enchancment in price effectiveness or cycle time in contrast with CPU-based computational lithography, whereas sustaining the identical price of possession.
- Transistor, tools and course of simulation: TSMC is utilizing NVIDIA cuEST, a GPU-accelerated digital construction simulation library for 50x sooner chemistry simulations, on common, for semiconductor materials design.
- Superior course of management: TSMC is utilizing the NVIDIA cuML machine studying library to speed up large-scale analytics on NVIDIA GPUs. This lets TSMC velocity algorithms and distill lots of of 1000’s of course of parameters spanning 1000’s of steps as precision inputs for machine studying fashions — making important discount in course of variation.
- Fab operations optimization: GPU-accelerated scheduling computation utilizing CUDA has led to notable enhancements in fab productiveness with NVIDIA H200 GPUs. By harnessing CUDA-powered computation on NVIDIA H200 GPUs, TSMC has enhanced its functionality to handle advanced constraints, thereby streamlining manufacturing paths and maximizing fab productiveness.
TSMC Advances Defect Inspection With NVIDIA Metropolis and AI Fashions
As chips turn out to be extra superior, even the smallest defects can have an effect on high quality and yield, making sooner and extra correct inspection important to semiconductor design and manufacturing.
TSMC is utilizing the NVIDIA Metropolis platform and NVIDIA TAO Toolkit to enhance superior defect classification. Utilizing imaginative and prescient AI, TSMC has improved detection of defects at nanometer scale.
These capabilities assist TSMC enhance high quality inspection whereas lowering the necessity for repeated labeling and retraining as course of situations, inspection instruments and defect sorts change.
TSMC Faucets NVIDIA Omniverse to Construct FabTwin
Superior semiconductor fabs are among the many most advanced fabs ever constructed, requiring exact coordination throughout instruments, supplies, robots, people and facility programs.
TSMC is exploring NVIDIA Omniverse™ libraries to construct FabTwin, a digital fab setting for evaluating course of instrument layouts and associated simulation workflows. By testing design eventualities digitally earlier than bodily implementation, TSMC can evaluate advanced configurations extra flexibly and establish potential constraints earlier. This virtual-first strategy vastly improves planning effectivity and accelerates essential decision-making earlier than any bodily or capital commitments are made.
Watch Huang’s keynote and be taught extra at NVIDIA GTC Taipei.
