NVIDIA Ships First Volta-based DGX Systems
by Nate Oh on September 7, 2017 10:00 AM EST- Posted in
- GPUs
- Tesla
- NVIDIA
- Volta
- Machine Learning
- GV100
- Deep Learning
This Wednesday, NVIDIA has announced that they have shipped their first commercial Volta-based DGX-1 system to the MGH & BWH Center for Clinical Data Science (CCDS), a Massachusetts-based research group focusing on AI and machine learning applications in healthcare. In a sense, this serves as a generational upgrade as CCDS was one of the first research institutions to receive a Pascal-based first generation DGX-1 last December. In addition, NVIDIA is shipping a DGX Station to CCDS later this month.
At CCDS, these AI supercomputers will continue to be used in training deep neural networks for the purpose of evaluating medical images and scans, using Massachusetts General Hospital’s collection of phenotypic, genetics, and imaging data. In turn, this can assist doctors and medical practitioners in making faster and more accurate diagnoses and treatment plans.
First announced at GTC 2017, the DGX-1V server is powered by 8 Tesla V100s and priced at $149,000. The original iteration of the DGX-1 was priced at $129,000 with a 2P 16-core Haswell-EP configuration, but has since been updated to the same 20-core Broadwell-EP CPUs found in the DGX-1V, allowing for easy P100 to V100 drop-in upgrades. As for the DGX Station, this was also unveiled at GTC 2017, and is essentially a full tower workstation 1P version of the DGX-1 with 4 Tesla V100s. This water cooled DGX Station is priced at $69,000.
| Selected NVIDIA DGX Systems Specifications | ||||||
| DGX-1 (Volta) |
DGX-1 (Pascal) |
DGX-1 (Pascal, Original) |
DGX Station | |||
| GPU Configuration | 8x Tesla V100 | 8x Tesla P100 | 4x Tesla V100 | |||
| GPU FP16 Compute | General Purpose | 240 TFLOPS | 170 TFLOPS | 120 TFLOPS |
||
| Deep Learning | 960 TFLOPS | 480 TFLOPS | ||||
| CPU Configuration | 2x Intel Xeon E5-2698 v4 (20-core, Broadwell-EP) |
2x Intel Xeon E5-2698 v3 (16 core, Haswell-EP) |
1x Intel Xeon E5-2698 v4 (20-core, Broadwell-EP) |
|||
| System Memory | 512 GB DDR4-2133 (LRDIMM) |
256 GB DDR4 (LRDIMM) |
||||
| Total GPU Memory | 128 GB HBM2 (8x 16GB) |
64 GB HBM2 (4x 16GB) |
||||
| Storage | 4x 1.92 TB SSD RAID 0 | OS: 1x 1.92 TB SSD Data: 3x 1.92 TB SSD RAID 0 |
||||
| Networking | Dual 10GbE 4 InfiniBand EDR |
Dual 10Gb LAN | ||||
| Max Power | 3200W | 1500W | ||||
| Dimensions | 866mm x 444mm x 131mm (3U Rackmount) |
518mm x 256mm x 639mm (Tower) |
||||
| Other Features | Ubuntu Linux Host OS DGX Software Stack (see Datasheet) |
Ubuntu Desktop Linux OS DGX Software Stack (see Datasheet) 3x DisplayPort |
||||
| Price | $149,000 | Varies | $129,000 | $69,000 | ||
Taking a step back, this is a continuation of NVIDIA’s rollout of Volta-based professional/server products, with DGX Volta meeting its Q3 launch date, and OEM Volta targeted at Q4. In the past months, the first Tesla V100 GPU accelerators were given out to researchers at the 2017 Conference on Computer Vision and Pattern Recognition (CVPR) in July, while a PCIe version of the Tesla V100 was formally announced during ISC 2017 in June.
Source: NVIDIA
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Yojimbo - Thursday, September 7, 2017 - link
You'll have to ask them what they'll do. I assume they will sell it on the open market just like any other good or service. They are spending money to develop a system that they think people will find valuable. That is, it will be cheaper and/or higher quality than current methods. So I am guessing that any interested medical institution would have to pay for the use of the trained neural network just like they'd have to pay for the use of a trained doctor or medical billing software. I'm not sure why you think this labor and enterprise would be "greedy" for looking for a return on their investment.MrSpadge - Friday, September 8, 2017 - link
Using the trained networks will definitely require a lot less number crunching power - depending on how many images and at what resolution are needed. This will probably still require modern GPUs, but not 8xGV100.gfkBill - Friday, September 8, 2017 - link
Obligatory Ethereum mining reference - that's about the equivalent of 140 GTX1060's in memory bandwidth. But at a cost of about 4x buying that many 1060's :)Ironchef3500 - Friday, September 8, 2017 - link
holy shitsparkuss - Friday, September 8, 2017 - link
I just enjoy the picture composition,......with orders of magnitude of computational power in hand, the stalwart whiteboard keeps watch, proud in knowing it still is needed to keep the world on track.
dagnamit - Wednesday, September 13, 2017 - link
Yes, but can it run Crysis?Zingam - Thursday, September 14, 2017 - link
No!fmttech - Sunday, July 29, 2018 - link
looks like NVIDIA DGX is breakthrough technology looking forward to what's next. https://www.future-micro.ca