May 29, 2022

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NVIDIA Ada Lovelace GPUs have node advantage over AMD RDNA 3, rumored to use TSMC 4N process

NVIDIA Ada Lovelace GPUs To Have A Node Advantage Over AMD RDNA 3, Rumored To Utilize TSMC 4N Process

nvidia Ada Lovelace GPUs Next-gen GeForce RTX 40 gaming graphics cards will have a node advantage over AMD’s RDNA 3, as I mentioned before Moore’s Law died.

NVIDIA Ada Lovelace gaming GPUs are rumored to use a TSMC 4N processing node, giving a slight advantage over AMD RDNA 3 GPUs

From what we know so far, it was NVIDIA is expected To take advantage of TSMC’s 5nm process node for Ada Lovelace GPUs that support the next generation of gaming graphics cards known as the GeForce RTX 40 series. The specific node appears to have been revealed by Moore’s Mitt’s Law in a recent tweet. According to the latest rumor, NVIDIA Ada Lovelace GPUs will be based on the TSMC 4N process node.

AMD Ryzen 7000 CPUs and AM5 platform will only support DDR5 memory, and come with EXPO ‘Memory Profile’ technology

Yes, this is the same TSMC 4N process node running a file Huber GPUs For the HPC data center market. As for what we know about the TSMC 4N process node, it is a review of the 5nm process (not to be confused with 4nm/N4 which is a completely different node). The TSMC 4N process node was designed specifically for NVIDIA and hosts a suite of improvements that allow for improved power efficiency and performance and a slight increase in density versus the vanilla TSMC 5nm node.

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The reasons why NVIDIA chose TSMC’s 4N as a candidate for its next-generation gaming GPU lineup are fairly straightforward. Upcoming cards He’d be really power hungry NVIDIA and the company will work to improve it as much as possible through the use of the 4N process node. On the other hand, AMD will use a combination of TSMC Processing nodes of 5 nm and 6 nm For upcoming MCM and monolithic GPUs based on RDNA 3 . graphics architecture And while they don’t bring the improvements that 4N offers, they will showcase an MCM approach that is expected to be highly efficient.

So at the end of the day, NVIDIA gets a better node while AMD offers a better design approach. At the end of the day, these things won’t matter much to the end users who just want to play their games on the best possible hardware (graphics cards) they can get.

NVIDIA CUDA GPU (Rumoured) Introductory:

GPU TU102 GA102 M 102
Major SKU RTX 2080 Ti RTX 3090 Ti RTX 4090?
building Turing Ampere Ada Lovelace
to treat TSMC 12nm NFF Samsung 8nm TSMC 4N?
die size 754 mm 2 628 mm 2 ~ 600 mm 2
Graphics Processing Kits (GPC) 6 7 12
Textile Processing Kits (TPC) 36 42 72
multiprocessor flow (SM) 72 84 144
koda cores 4608 10752 18432
L2 cache 6 MB 6 MB 96 MB
Theoretical TFLOPs 16 TFLOPs 40 TFLOPs ~90 TFLOPs?
memory type GDDR6 GDDR6X GDDR6X
Memory capacity 11 GB (2080T) 24 GB (3090 Ti) 24 GB (4090?)
Memory speed 14 Gbps 21 Gbps 24 Gbps?
memory bandwidth 616 GB/sec 1.008 GB/sec 1152 Gb / s?
Memory bus 384 bit 384 bit 384 bit
PCIe interface PCIe Gen 3.0 PCIe Gen 4.0 PCIe Gen 4.0
TGP 250 watts 350 watts 600 watts?
Release September 2018 September 20 2H 2022 (TBC)
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