wolf
Performance Enthusiast
- Joined
- May 7, 2007
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| System Name | MightyX |
|---|---|
| Processor | Ryzen 5800X3D |
| Motherboard | Gigabyte X570 I Aorus Pro WiFi |
| Cooling | Scythe Fuma 2 |
| Memory | 32GB DDR4 3600 CL16 |
| Video Card(s) | Asus TUF RTX3080 Deshrouded |
| Storage | WD Black SN850X 2TB |
| Display(s) | LG 42C2 4K OLED |
| Case | Coolermaster NR200P |
| Audio Device(s) | LG SN5Y / Focal Clear |
| Power Supply | Corsair SF750 Platinum |
| Mouse | Corsair Dark Core RBG Pro SE |
| Keyboard | Glorious GMMK Compact w/pudding |
| VR HMD | Meta Quest 3 |
| Software | case populated with Artic P12's |
| Benchmark Scores | 4k120 OLED Gsync bliss |
This week NVIDIA announced their latest innovation to the HPC landscape, the DGX SaturnV. Destined for the likes of universities and companies with a need for deep learning capabilities, the DGX SaturnV sets a new benchmark for energy efficiency in High Performance Computing. While not managing the title of the fastest supercomputer this year, the SaturnV takes a respectable placing of 28th in the top 500 list, while promising much lower running costs for performance on tap.
Capable of delivering 9.46 GFLOPS of computational speed per Watt of energy consumed, it bests last years best effort of 6.67 GFLOPS/W by 42%. The SaturnV is comprised of 125 DGX-1 deep learning systems, and each DGX-1 contains no less than eight Tesla P100 cards. Where a single GTX1080 can churn out 138 GFLOPS of FP16 calculations, a single Telsa P100 can deliver a massive 21.2 TFLOPS. The singular DGX-1 units are already in the field, including being used by NVIDIA themselves.
View at TechPowerUp Main Site
Capable of delivering 9.46 GFLOPS of computational speed per Watt of energy consumed, it bests last years best effort of 6.67 GFLOPS/W by 42%. The SaturnV is comprised of 125 DGX-1 deep learning systems, and each DGX-1 contains no less than eight Tesla P100 cards. Where a single GTX1080 can churn out 138 GFLOPS of FP16 calculations, a single Telsa P100 can deliver a massive 21.2 TFLOPS. The singular DGX-1 units are already in the field, including being used by NVIDIA themselves.
View at TechPowerUp Main Site
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