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

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.

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 Card	NVIDIA B200	NVIDIA H200 (SXM5)	NVIDIA 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)
GPU	B200	H200 (Hopper)	H100 (Hopper)	H100 (Hopper)	A100 (Ampere)	A100 (Ampere)	GV100 (Volta)	GV100 (Volta)	GP100 (Pascal)	GP100 (Pascal)	GM200 (Maxwell)	GK110 (Kepler)
Process Node	4nm	4nm	4nm	4nm	7nm	7nm	12nm	12nm	16nm	16nm	28nm	28nm
Transistors	208 Billion	80 Billion	80 Billion	80 Billion	54.2 Billion	54.2 Billion	21.1 Billion	21.1 Billion	15.3 Billion	15.3 Billion	8 Billion	7.1 Billion
GPU Die Size	TBD	814mm2	814mm2	814mm2	826mm2	826mm2	815mm2	815mm2	610 mm2	610 mm2	601 mm2	551 mm2
SMs	160	132	132	114	108	108	80	80	56	56	24	15
TPCs	80	66	66	57	54	54	40	40	28	28	24	15
L2 Cache Size	TBD	51200 KB	51200 KB	51200 KB	40960 KB	40960 KB	6144 KB	6144 KB	4096 KB	4096 KB	3072 KB	1536 KB
FP32 CUDA Cores Per SM	TBD	128	128	128	64	64	64	64	64	64	128	192
FP64 CUDA Cores / SM	TBD	128	128	128	32	32	32	32	32	32	4	64
FP32 CUDA Cores	TBD	16896	16896	14592	6912	6912	5120	5120	3584	3584	3072	2880
FP64 CUDA Cores	TBD	16896	16896	14592	3456	3456	2560	2560	1792	1792	96	960
Tensor Cores	TBD	528	528	456	432	432	640	640	N/A	N/A	N/A	N/A
Texture Units	TBD	528	528	456	432	432	320	320	224	224	192	240
Boost Clock	TBD	~1850 MHz	~1850 MHz	~1650 MHz	1410 MHz	1410 MHz	1601 MHz	1530 MHz	1480 MHz	1329MHz	1114 MHz	875 MHz
TOPs (DNN/AI)	20,000 TOPs	3958 TOPs	3958 TOPs	3200 TOPs	2496 TOPs	2496 TOPs	130 TOPs	125 TOPs	N/A	N/A	N/A	N/A
FP16 Compute	10,000 TFLOPs	1979 TFLOPs	1979 TFLOPs	1600 TFLOPs	624 TFLOPs	624 TFLOPs	32.8 TFLOPs	30.4 TFLOPs	21.2 TFLOPs	18.7 TFLOPs	N/A	N/A
FP32 Compute	90 TFLOPs	67 TFLOPs	67 TFLOPs	800 TFLOPs	156 TFLOPs (19.5 TFLOPs standard)	156 TFLOPs (19.5 TFLOPs standard)	16.4 TFLOPs	15.7 TFLOPs	10.6 TFLOPs	10.0 TFLOPs	6.8 TFLOPs	5.04 TFLOPs
FP64 Compute	45 TFLOPs	34 TFLOPs	34 TFLOPs	48 TFLOPs	19.5 TFLOPs (9.7 TFLOPs standard)	19.5 TFLOPs (9.7 TFLOPs standard)	8.2 TFLOPs	7.80 TFLOPs	5.30 TFLOPs	4.7 TFLOPs	0.2 TFLOPs	1.68 TFLOPs
Memory Interface	8192-bit HBM4	5120-bit HBM3e	5120-bit HBM3	5120-bit HBM2e	6144-bit HBM2e	6144-bit HBM2e	4096-bit HBM2	4096-bit HBM2	4096-bit HBM2	4096-bit HBM2	384-bit GDDR5	384-bit GDDR5
Memory Size	Up To 192 GB HBM3 @ 8.0 Gbps	Up To 141 GB HBM3e @ 6.5 Gbps	Up To 80 GB HBM3 @ 5.2 Gbps	Up To 94 GB HBM2e @ 5.1 Gbps	Up 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/s	16 GB HBM2 @ 900 GB/s	16 GB HBM2 @ 732 GB/s	16 GB HBM2 @ 732 GB/s 12 GB HBM2 @ 549 GB/s	24 GB GDDR5 @ 288 GB/s	12 GB GDDR5 @ 288 GB/s
TDP	700W	700W	700W	350W	400W	250W	250W	300W	300W	250W	250W	235W

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