NVIDIA Allegedly Working on Hopper H100 PCIe Graphics Card With 120 GB HBM2e Memory Capacity

Hassan Mujtaba

NVIDIA is allegedly working on a brand new Hopper H100 GPU-based graphics card that would feature up to 120 GB HBM2e memory capacity.

NVIDIA Hopper H100 GPU-Powered PCIe Graphics Card With 120 GB HBM2e Memory Capacity Spotted

NVIDIA has so far officially announced two versions of the Hopper H100 GPU, an SXM5 board and a PCIe variant. Both feature differently configured Hopper H100 GPUs and while their VRAM capacity is the same at 80 GB, the former utilizes the brand new HBM3 standard while the latter utilizes the HBM2e standard.

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Now based on information by s-ss.cc (via MEGAsizeGPU), NVIDIA might be working on a brand new PCIe version of the Hopper H100 GPU. The new graphics card won't feature 80 GB HBM2e but will go all out with 120 GB of HBM2e memory.

As per the information available, the Hopper H100 PCIe graphics card not only comes with all six HBM2e stacks enabled for 120 GB memory across a 6144-bit bus interface, but it also comes with the same GH100 GPU configuration as the SXM5 variant. This is a total of 16,896 CUDA cores and memory bandwidth that exceeds 3 TB/s. The single-precision compute performance has been rated at 30 TFLOPs which is the same as the SXM5 variant.

So coming to the specifications, the NVIDIA Hopper GH100 GPU is composed of a massive 144 SM (Streaming Multiprocessor) chip layout which is featured in a total of 8 GPCs. These GPCs rock total of 9 TPCs which are further composed of 2 SM units each. This gives us 18 SMs per GPC and 144 on the complete 8 GPC configuration. Each SM is composed of up to 128 FP32 units which should give us a total of 18,432 CUDA cores. Following are some of the configurations you can expect from the H100 chip:

The full implementation of the GH100 GPU includes the following units:

  • 8 GPCs, 72 TPCs (9 TPCs/GPC), 2 SMs/TPC, 144 SMs per full GPU
  • 128 FP32 CUDA Cores per SM, 18432 FP32 CUDA Cores per full GPU
  • 4 Fourth-Generation Tensor Cores per SM, 576 per full GPU
  • 6 HBM3 or HBM2e stacks, 12 512-bit Memory Controllers
  • 60 MB L2 Cache

The NVIDIA H100 GPU with SXM5 board form-factor includes the following units:

  • 8 GPCs, 66 TPCs, 2 SMs/TPC, 132 SMs per GPU
  • 128 FP32 CUDA Cores per SM, 16896 FP32 CUDA Cores per GPU
  • 4 Fourth-generation Tensor Cores per SM, 528 per GPU
  • 80 GB HBM3, 5 HBM3 stacks, 10 512-bit Memory Controllers
  • 50 MB L2 Cache
  • Fourth-Generation NVLink and PCIe Gen 5

Now it is unknown if this is a test board or a future iteration of the Hopper H100 GPU that is being tested out. NVIDIA recently stated at GTC 22 that their Hopper GPU was now in full production and the first wave of products are rolling out next month. As yields get better, we may definitely see the 120 GB Hopper H100 PCIe graphics card and SXM5 variants in the market but for now, the 80 GB is what most customers are going to get.

NVIDIA HPC / AI GPUs

NVIDIA Tesla Graphics CardNVIDIA H100 (SMX5)NVIDIA H100 (PCIe)NVIDIA A100 (SXM4)NVIDIA A100 (PCIe4)Tesla V100S (PCIe)Tesla V100 (SXM2)Tesla P100 (SXM2)Tesla P100
(PCI-Express)
Tesla M40
(PCI-Express)
Tesla K40
(PCI-Express)
GPUGH100 (Hopper)GH100 (Hopper)GA100 (Ampere)GA100 (Ampere)GV100 (Volta)GV100 (Volta)GP100 (Pascal)GP100 (Pascal)GM200 (Maxwell)GK110 (Kepler)
Process Node4nm4nm7nm7nm12nm12nm16nm16nm28nm28nm
Transistors80 Billion80 Billion54.2 Billion54.2 Billion21.1 Billion21.1 Billion15.3 Billion15.3 Billion8 Billion7.1 Billion
GPU Die Size814mm2814mm2826mm2826mm2815mm2815mm2610 mm2610 mm2601 mm2551 mm2
SMs132114108108808056562415
TPCs66575454404028282415
FP32 CUDA Cores Per SM128128646464646464128192
FP64 CUDA Cores / SM128128323232323232464
FP32 CUDA Cores168961459269126912512051203584358430722880
FP64 CUDA Cores168961459234563456256025601792179296960
Tensor Cores528456432432640640N/AN/AN/AN/A
Texture Units528456432432320320224224192240
Boost ClockTBDTBD1410 MHz1410 MHz1601 MHz1530 MHz1480 MHz1329MHz1114 MHz875 MHz
TOPs (DNN/AI)3958 TOPs3200 TOPs1248 TOPs
2496 TOPs with Sparsity
1248 TOPs
2496 TOPs with Sparsity
130 TOPs125 TOPsN/AN/AN/AN/A
FP16 Compute1979 TFLOPs1600 TFLOPs312 TFLOPs
624 TFLOPs with Sparsity
312 TFLOPs
624 TFLOPs with Sparsity
32.8 TFLOPs30.4 TFLOPs21.2 TFLOPs18.7 TFLOPsN/AN/A
FP32 Compute67 TFLOPs800 TFLOPs156 TFLOPs
(19.5 TFLOPs standard)
156 TFLOPs
(19.5 TFLOPs standard)
16.4 TFLOPs15.7 TFLOPs10.6 TFLOPs10.0 TFLOPs6.8 TFLOPs5.04 TFLOPs
FP64 Compute34 TFLOPs48 TFLOPs19.5 TFLOPs
(9.7 TFLOPs standard)
19.5 TFLOPs
(9.7 TFLOPs standard)
8.2 TFLOPs7.80 TFLOPs5.30 TFLOPs4.7 TFLOPs0.2 TFLOPs1.68 TFLOPs
Memory Interface5120-bit HBM35120-bit HBM2e6144-bit HBM2e6144-bit HBM2e4096-bit HBM24096-bit HBM24096-bit HBM24096-bit HBM2384-bit GDDR5384-bit GDDR5
Memory SizeUp To 80 GB HBM3 @ 3.0 GbpsUp To 80 GB HBM2e @ 2.0 GbpsUp To 40 GB HBM2 @ 1.6 TB/s
Up To 80 GB HBM2 @ 1.6 TB/s
Up To 40 GB HBM2 @ 1.6 TB/s
Up To 80 GB HBM2 @ 2.0 TB/s
16 GB HBM2 @ 1134 GB/s16 GB HBM2 @ 900 GB/s16 GB HBM2 @ 732 GB/s16 GB HBM2 @ 732 GB/s
12 GB HBM2 @ 549 GB/s
24 GB GDDR5 @ 288 GB/s12 GB GDDR5 @ 288 GB/s
L2 Cache Size51200 KB51200 KB40960 KB40960 KB6144 KB6144 KB4096 KB4096 KB3072 KB1536 KB
TDP700W350W400W250W250W300W300W250W250W235W

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