NVIDIA Hopper H100 GPU Pictured In All Its Glory: The World’s Fastest 4nm GPU & World’s First With HBM3 Memory

NVIDIA's flagship Datacenter GPU, the Hopper H100, has been pictured in all its glory. (Image Credits: CNET)

At GTC 2022, NVIDIA unveiled its Hopper H100 GPU, a compute powerhouse designed for the next generation of data centers. It’s been a while since we talked about this mighty chip but it looks like NVIDIA gave a close-up of its flagship chip to select media.

NVIDIA Hopper H100 GPU: First With 4nm and HBM3 Technology Gets High-Res Pictures

CNET managed to get hold of not only the graphics board on which the H100 GPU is fused but also the H100 chip itself. The H100 GPU is a monster chip that comes packed with the latest 4nm tech and incorporates 80 Billion transistors along with the bleeding-edge HBM3 memory technology. As per the tech outlet, the H100 is built upon the PG520 PCB board which has over 30 power VRMs & a massive integral interposer that uses TSMC’s CoWoS tech to combine the Hopper H100 GPU with a 6-stack HBM3 design.

NVIDIA Hopper H100 GPU Pictured (Image Credits: CNET):

Out of the six stacks, two stacks are kept to ensure yield integrity. But the new HBM3 standard allows for up to 80 GB capacities at 3 TB/s speeds which are crazy. For comparison, the current fastest gaming graphics card, the RTX 3090 Ti, offers just 1 TB/s of bandwidth and 24 GB VRAM capacities. Other than that, the H100 Hopper GPU also packs in the latest FP8 data format, and through its new SXM connection, it helps accommodate the 700W power design that the chip is designed around.

NVIDIA Hopper H100 GPU Specifications At A Glance

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
  • Fourth-Generation NVLink and PCIe Gen 5

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

This is a 2.25x increase over the full GA100 GPU configuration. NVIDIA is also leveraging from more FP64, FP16 & Tensor cores within its Hopper GPU which would drive up performance immensely. And that’s going to be a necessity to rival Intel’s Ponte Vecchio which is also expected to feature 1:1 FP64.

The cache is another space where NVIDIA has given much attention, upping it to 48 MB in the Hopper GH100 GPU. This is a 20% increase over the 50 MB cache featured on the Ampere GA100 GPU and 3x the size of AMD’s flagship Aldebaran MCM GPU, the MI250X.

Rounding up the performance figures, NVIDIA’s GH100 Hopper GPU will offer 4000 TFLOPs of FP8, 2000 TFLOPs of FP16, 1000 TFLOPs of TF32 and 60 TFLOPs of FP64 Compute performance. These record-shattering figures decimate all other HPC accelerators that came before it. For comparison, this is 3.3x faster than NVIDIA’s own A100 GPU and 28% faster than AMD’s Instinct MI250X in the FP64 compute. In FP16 compute, the H100 GPU is 3x faster than A100 and 5.2x faster than MI250X which is literally bonkers.

The PCIe variant which is a cut-down model was recently listed over in Japan for over $30,000 US so one can imagine that the SXM variant with a beefier configuration will easily cost around $50 grand.

NVIDIA Ampere GA100 GPU Based Tesla A100 Specs:

NVIDIA Tesla Graphics Card NVIDIA H100 (SMX5) NVIDIA H100 (PCIe) NVIDIA A100 (SXM4) NVIDIA A100 (PCIe4) Tesla V100S (PCIe) Tesla V100 (SXM2) Tesla P100 (SXM2) Tesla P100
Tesla M40
Tesla K40
GPU GH100 (Hopper) GH100 (Hopper) GA100 (Ampere) GA100 (Ampere) GV100 (Volta) GV100 (Volta) GP100 (Pascal) GP100 (Pascal) GM200 (Maxwell) GK110 (Kepler)
Process Node 4nm 4nm 7nm 7nm 12nm 12nm 16nm 16nm 28nm 28nm
Transistors 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 814mm2 814mm2 826mm2 826mm2 815mm2 815mm2 610 mm2 610 mm2 601 mm2 551 mm2
SMs 132 114 108 108 80 80 56 56 24 15
TPCs 66 57 54 54 40 40 28 28 24 15
FP32 CUDA Cores Per SM 128 128 64 64 64 64 64 64 128 192
FP64 CUDA Cores / SM 128 128 32 32 32 32 32 32 4 64
FP32 CUDA Cores 16896 14592 6912 6912 5120 5120 3584 3584 3072 2880
FP64 CUDA Cores 16896 14592 3456 3456 2560 2560 1792 1792 96 960
Tensor Cores 528 456 432 432 640 640 N/A N/A N/A N/A
Texture Units 528 456 432 432 320 320 224 224 192 240
Boost Clock TBD TBD 1410 MHz 1410 MHz 1601 MHz 1530 MHz 1480 MHz 1329MHz 1114 MHz 875 MHz
TOPs (DNN/AI) 2000 TOPs
4000 TOPs
1600 TOPs
3200 TOPs
1248 TOPs
2496 TOPs with Sparsity
1248 TOPs
2496 TOPs with Sparsity
130 TOPs 125 TOPs N/A N/A N/A N/A
FP16 Compute 2000 TFLOPs 1600 TFLOPs 312 TFLOPs
624 TFLOPs with Sparsity
312 TFLOPs
624 TFLOPs with Sparsity
32.8 TFLOPs 30.4 TFLOPs 21.2 TFLOPs 18.7 TFLOPs N/A N/A
FP32 Compute 1000 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 60 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 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 80 GB HBM3 @ 3.0 Gbps Up To 80 GB HBM2e @ 2.0 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
L2 Cache Size 51200 KB 51200 KB 40960 KB 40960 KB 6144 KB 6144 KB 4096 KB 4096 KB 3072 KB 1536 KB
TDP 700W 350W 400W 250W 250W 300W 300W 250W 250W 235W

The post NVIDIA Hopper H100 GPU Pictured In All Its Glory: The World’s Fastest 4nm GPU & World’s First With HBM3 Memory by Hassan Mujtaba appeared first on Wccftech.

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