NVIDIA’s Ada Lovelace GPUs for the next generation GeForce RTX 40 Gaming graphics card will have a node advantage over AMD’s RDNA 3, as reported by Moore’s law is dead.
NVIDIA Ada Lovelace Gaming GPUs are rumored to use TSMC’s 4N Process Node, giving a slight advantage over AMD’s RDNA 3 GPUs
From what we know so far, NVIDIA was expected to use TSMC’s 5nm process node for their Ada Lovelace GPUs, which power next-generation gaming graphics cards aka the GeForce RTX 40 series. It appears that the specific knot has been revealed by Moore’s Law is Dead in a recent tweet. According to the latest rumor, the NVIDIA Ada Lovelace GPUs will be based on the TSMC 4N process node.
Note that I did not mention PCIe 5.0 in my Lovelace Slides: https://t.co/n7sdIL1Uku
Speaking of “4”, #NVIDIA Lovelace is really 4nm!
🤠🎉😋 More to say about the next Broken Silicon … https://t.co/jjJ1GSod0j
– Moore’s Law Is Dead (@mooreslawisdead) April 24, 2022
Yep, it’s the same TSMC 4N process node that drives the Hopper GPUs to the data center HPC market. What we know about the TSMC 4N process node is a revision of their 5nm process (not to be confused with 4nm / N4, which is a completely different node). The TSMC 4N process node is specially designed exclusively for NVIDIA and hosts a number of optimizations that allow for better power efficiency, performance and a smaller boost to density compared to the vanilla TSMC 5nm node.
The reasons why NVIDIA may have chosen TSMC’s 4N as the candidate for its next generation gaming GPU lineup are a bit obvious. The upcoming cards will be really power-intensive, and NVIDIA and the company will optimize them as much as they can, using the 4N process node. AMD, on the other hand, will use a mix of TSMC 5nm and 6nm process nodes for its upcoming MCM and monolithic GPUs based on the RDNA 3 graphics architecture, and although they do not bring the optimizations that 4N does, they will have an MCM approach as expected to be extremely effective.
So at the end of the day, NVIDIA gets the better node, while AMD delivers a better design approach. In the end, these will not mean much to end users who only want to play their games on the best possible hardware (graphics card) they can get their hands on.
NVIDIA CUDA GPU (RUMORED) Preliminary:
GPU | TU102 | GA102 | AD102 |
---|---|---|---|
Flagship SKU | RTX 2080 Ti | RTX 3090 Ti | RTX 4090? |
Architecture | Turing | Ampere | Ada Lovelace |
Treat | TSMC 12nm NFF | Samsung 8nm | TSMC 4N? |
Die Size | 754 mm2 | 628 mm2 | ~ 600mm2 |
Graphics Processing Clusters (GPC) | 6 | 7 | 12 |
Texture Processing Clusters (TPC) | 36 | 42 | 72 |
Streaming multiprocessors (SM) | 72 | 84 | 144 |
CUDA 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 (2080 Ti) | 24 GB (3090 Ti) | 24 GB (4090?) |
Memory speed | 14 Gbps | 21 Gbps | 24 Gbps? |
Memory bandwidth | 616 GB / s | 1,008 GB / s | 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 | 250W | 350W | 600W? |
Release | September 2018 | Sept. 20 | 2H 2022 (TBC) |