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SXM (socket)

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Computing node of TSUBAME 3.0 supercomputer showing four NVIDIA Tesla P100 SXM modules
Bare SXM sockets next to sockets with GPUs installed

SXM (Server PCI Express Module)[1] is a high bandwidth socket solution for connecting Nvidia Compute Accelerators to a system. Each generation of Nvidia Tesla since P100 models, the DGX computer series and the HGX boards come with an SXM socket type that realizes high bandwidth, power delivery and more for the matching GPU daughter cards.[2] Nvidia offers these combinations as an end-user product e.g. in their models of the DGX system series. Current socket generations are SXM for Pascal based GPUs, SXM2 and SXM3 for Volta based GPUs, SXM4 for Ampere based GPUs, and SXM5 for Hopper based GPUs. These sockets are used for specific models of these accelerators, and offer higher performance per card than PCIe equivalents.[2] The DGX-1 system was the first to be equipped with SXM-2 sockets and thus was the first to carry the form factor compatible SXM modules with P100 GPUs and later was unveiled to be capable of allowing upgrading to (or being pre-equipped with) SXM2 modules with V100 GPUs.[3][4]

SXM boards are typically built with four or eight GPU slots, although some solutions such as the Nvidia DGX-2 connect multiple boards to deliver high performance. While third party solutions for SXM boards exist, most System Integrators such as Supermicro use prebuilt Nvidia HGX boards, which come in four or eight socket configurations.[5] This solution greatly lowers the cost and difficulty of SXM based GPU servers, and enables compatibility and reliability across all boards of the same generation.

SXM modules on e.g. HGX boards, particularly recent generations, may have NVLink switches to allow faster GPU-to-GPU communication. This as well reduces bottlenecks which would normally be located within CPU and PCIe.[2][6] The GPUs on the daughter cards are just using NVLink as their main communication protocol. For example a Hopper-based H100 SXM5 based GPU can use up to 900 GB/s of bandwidth across 18 NVLink 4 channels, with each contributing a 50 GB/s of bandwidth;[7] This compared to PCIe 5.0, which can handle up to 64 GB/s of bandwidth within a x16 slot.[8] This high bandwidth also means that GPUs can share memory over the NVLink bus, allowing an entire HGX board to present to the host system as a single, massive GPU.[9]

Power delivery is also handled by the SXM socket, negating the need for external power cables such as those needed in PCIe equivalent cards. This, combined with the horizontal mounting allows cooling options of higher efficiency which in turn allows the SXM based GPUs to operate at a much higher TDP. The Hopper-based H100, for example, can draw up to 700W solely from the SXM socket.[10] The lack of cabling also makes assembling and repairing of large systems much easier, and also reduces the possible points of failure.[2]

The early Nvidia Tegra automotive targeted evaluation board, 'Drive PX2', had two MXM (Mobile PCI Express Module) sockets on both sides of the card, this dual MXM design can be considered a predecessor to the Nvidia Tesla implementation of the SXM socket.

Comparison of accelerators used in DGX:[11][12][13]

Model Architecture Socket FP32
CUDA
cores
FP64 cores
(excl. tensor)
Mixed
INT32/FP32
cores
INT32
cores
Boost
clock
Memory
clock
Memory
bus width
Memory
bandwidth
VRAM Single
precision
(FP32)
Double
precision
(FP64)
INT8
(non-tensor)
INT8
dense tensor
INT32 FP4
dense tensor
FP16 FP16
dense tensor
bfloat16
dense tensor
TensorFloat-32
(TF32)
dense tensor
FP64
dense tensor
Interconnect
(NVLink)
GPU L1 Cache L2 Cache TDP Die size Transistor
count
Process Launched
B200 Blackwell SXM6 N/A N/A N/A N/A N/A 8 Gbit/s HBM3e 8192-bit 8 TB/sec 192 GB HBM3e N/A N/A N/A 4.5 POPS N/A 9 PFLOPS N/A 2.25 PFLOPS 2.25 PFLOPS 1.2 PFLOPS 40 TFLOPS 1.8 TB/sec GB100 N/A N/A 1000 W N/A 208 B TSMC 4NP Q4 2024 (expected)
B100 Blackwell SXM6 N/A N/A N/A N/A N/A 8 Gbit/s HBM3e 8192-bit 8 TB/sec 192 GB HBM3e N/A N/A N/A 3.5 POPS N/A 7 PFLOPS N/A 1.98 PFLOPS 1.98 PFLOPS 989 TFLOPS 30 TFLOPS 1.8 TB/sec GB100 N/A N/A 700 W N/A 208 B TSMC 4NP
H200 Hopper SXM5 16896 4608 16896 N/A 1980 MHz 6.3 Gbit/s HBM3e 6144-bit 4.8 TB/sec 141 GB HBM3e 67 TFLOPS 34 TFLOPS N/A 1.98 POPS N/A N/A N/A 990 TFLOPS 990 TFLOPS 495 TFLOPS 67 TFLOPS 900 GB/sec GH100 25344 KB (192 KB × 132) 51200 KB 1000 W 814 mm2 80 B TSMC 4N Q3 2023
H100 Hopper SXM5 16896 4608 16896 N/A 1980 MHz 5.2 Gbit/s HBM3 5120-bit 3.35 TB/sec 80 GB HBM3 67 TFLOPS 34 TFLOPS N/A 1.98 POPS N/A N/A N/A 990 TFLOPS 990 TFLOPS 495 TFLOPS 67 TFLOPS 900 GB/sec GH100 25344 KB (192 KB × 132) 51200 KB 700 W 814 mm2 80 B TSMC 4N Q3 2022
A100 80GB Ampere SXM4 6912 3456 6912 N/A 1410 MHz 3.2 Gbit/s HBM2e 5120-bit 1.52 TB/sec 80 GB HBM2e 19.5 TFLOPS 9.7 TFLOPS N/A 624 TOPS 19.5 TOPS N/A 78 TFLOPS 312 TFLOPS 312 TFLOPS 156 TFLOPS 19.5 TFLOPS 600 GB/sec GA100 20736 KB (192 KB × 108) 40960 KB 400 W 826 mm2 54.2 B TSMC N7 Q1 2020
A100 40GB Ampere SXM4 6912 3456 6912 N/A 1410 MHz 2.4 Gbit/s HBM2 5120-bit 1.52 TB/sec 40 GB HBM2 19.5 TFLOPS 9.7 TFLOPS N/A 624 TOPS 19.5 TOPS N/A 78 TFLOPS 312 TFLOPS 312 TFLOPS 156 TFLOPS 19.5 TFLOPS 600 GB/sec GA100 20736 KB (192 KB × 108) 40960 KB 400 W 826 mm2 54.2 B TSMC N7
V100 32GB Volta SXM3 5120 2560 N/A 5120 1530 MHz 1.75 Gbit/s HBM2 4096-bit 900 GB/sec 32 GB HBM2 15.7 TFLOPS 7.8 TFLOPS 62 TOPS N/A 15.7 TOPS N/A 31.4 TFLOPS 125 TFLOPS N/A N/A N/A 300 GB/sec GV100 10240 KB (128 KB × 80) 6144 KB 350 W 815 mm2 21.1 B TSMC 12FFN Q3 2017
V100 16GB Volta SXM2 5120 2560 N/A 5120 1530 MHz 1.75 Gbit/s HBM2 4096-bit 900 GB/sec 16 GB HBM2 15.7 TFLOPS 7.8 TFLOPS 62 TOPS N/A 15.7 TOPS N/A 31.4 TFLOPS 125 TFLOPS N/A N/A N/A 300 GB/sec GV100 10240 KB (128 KB × 80) 6144 KB 300 W 815 mm2 21.1 B TSMC 12FFN
P100 Pascal SXM/SXM2 N/A 1792 3584 N/A 1480 MHz 1.4 Gbit/s HBM2 4096-bit 720 GB/sec 16 GB HBM2 10.6 TFLOPS 5.3 TFLOPS N/A N/A N/A N/A 21.2 TFLOPS N/A N/A N/A N/A 160 GB/sec GP100 1344 KB (24 KB × 56) 4096 KB 300 W 610 mm2 15.3 B TSMC 16FF+ Q2 2016

References

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  1. ^ Michael Brown, W.; et al. (2012). "An Evaluation of Molecular Dynamics Performance on the Hybrid Cray XK6 Supercomputer". Procedia Computer Science. 9: 186–195. doi:10.1016/j.procs.2012.04.020.
  2. ^ a b c d Proud, Matt. "Achieving Maximum Compute Throughput: PCIe vs. SXM2". The Next Platform. Retrieved 2022-03-31.
  3. ^ Volta architecture whitepaper nvidia.com
  4. ^ DGX 1 User Guide nvidia.com
  5. ^ servethehome (2020-05-14). "NVIDIA A100 4x GPU HGX Redstone Platform". ServeTheHome. Retrieved 2022-03-31.
  6. ^ "NVLink & NVSwitch for Advanced Multi-GPU Communication". NVIDIA.
  7. ^ "Nvidia's H100 – What It Is, What It Does, and Why It Matters". Data Center Knowledge | News and analysis for the data center industry. 2022-03-23. Retrieved 2022-03-31.
  8. ^ "Is PCIe 5.0 Worth It? The Benefits of PCIe 5.0 (2022)". www.techreviewer.com. Retrieved 2022-03-31.
  9. ^ "NVIDIA HGX A100: Powered by A100 GPUs and NVSwitch". NVIDIA. Retrieved 2022-03-31.
  10. ^ "NVIDIA H100 GPU full details: TSMC N4, HBM3, PCIe 5.0, 700W TDP, more". TweakTown. 2022-03-23. Retrieved 2022-03-31.
  11. ^ Smith, Ryan (March 22, 2022). "NVIDIA Hopper GPU Architecture and H100 Accelerator Announced: Working Smarter and Harder". AnandTech.
  12. ^ Smith, Ryan (May 14, 2020). "NVIDIA Ampere Unleashed: NVIDIA Announces New GPU Architecture, A100 GPU, and Accelerator". AnandTech.
  13. ^ "NVIDIA Tesla V100 tested: near unbelievable GPU power". TweakTown. September 17, 2017.
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