1. Super Micro Technology Computing
X11 Generation

2. Intelligent Computing
Artificial Intelligence
Machine Learning
Neural Network
Deep Learning

3. GPU
Il GPU Computing affianca una GPU (unità di elaborazione grafica) a una CPU per accelerare l'elaborazione delle applicazioni scientifiche e tecniche.
Vengono demandate le porzioni più impegnative dei calcoli di ogni applicazione alle GPU, mentre la parte restante del codice viene eseguita dalla CPU
CPU hanno un numero di core contenuto e sono ottimizzate per l'elaborazione seriale, mentre le GPU hanno migliaia di core più piccoli ed efficienti progettati per l'elaborazione in parallelo

4. GPU Volta Key Details 5,120 CUDA cores; 640 Tensor cores
Tensor cores are new for Volta, matrix arithmetic units for accelerating for Machine Learning performance
Next Generation NVLINK
The Volta V100 is available in 2 form factors
Tesla V100 PCIe 16/32GB at 250W
Tesla V100 SXM2 16/32GB 300W
Tesla V100 SXM2
Tesla V100 PCIe

5. Volta Architecture 84 Volta SMs ● 64 FP32 cores ● 64 INT32 cores
● 8 Tensor Cores

6. Volta GPU Architecture
Massive Parallel Architecture costruita con migliaia di Core
Cuda Progammming Model usato per programmare le GPU Nvidia

7. MultiThread

8. Volta Key CPU Core Set Istruzione più complesso Elevato Clock Rate
Cache più impegnativa
GPU Core
Meno cache
Più semplice Set istruzione
Basso Clock

9. What is a GPU Server GPU servers
Optimized to mechanically hold and secure a large number of GPU
Optimized for Power Delivery, come with large power supplies to feed power hungry GPUs
Optimized for Thermals, large fans (even liquid cooling) to cool hot GPUs

10. Single Root Complex SYS-4029GP-TRT SYS-4029GP-TRT2 9 10 1 5 1 5 2 6 23 7 3 7 4 8 4 8 9 10

11. PCIE P2P BENCHMARKS
25.2
19.9
21.5
16.8
13.8
6.7
6.6
6.8
25.2
21.5
20.1
16.8
13.9
6.6
6.2
6.7
Single Root Has 21% better Throughput, 60% better Latency over Dual Root Systems
DUAL
SINGLE

12. NVLINK NVLink Fabric Interconnessione più veloce tra le GPU
Banda Passante 300 GBs
Hybrid Cube Fabric
X 10 rispetto al PCI e
6 Links per GPU

13. SYS-4029GP-TXRT/TVRT Key Applications: Key Features:
Processor Support
Dual socket P (LGA 3647) supports Intel® Xeon® Scalable Processors, 3 UPI up to 10.4GT/s
Oct Tesla SXM2 (Pascal/Volta) GPUs
Memory Capacity
Up to 3TB ECC 3DS LRDIMM, up to DDR4-2666MHz; 24 DIMM slots
Expansion Slots
4 PCI-e 3.0 x16 LP (via RDMA for IB EDR)
2 PCI-e 3.0 x16 LP
I/O ports
1x VGA, 2x 10G-BaseT LAN, 3x USB 3.0, and 1x IPMI dedicated LAN port, 1x M.2 NVMe
Drive Bays
16 hot-swap 2.5” drives bay (Support up to 8x NVMe)
System Cooling
8 heavy duty fans optimize to support 8 GPU cards
Power Supply
4 x 2200W (2+2) Titanium Level efficiency redundant power supply 1 2 3 4 5 6 7
Use Case: Big Data Analytics
Target Market: Big Data Analytics
Companies involved with Big Data Analytics is finding ways to improve life through AI by making things think through cutting edge, in-house-developed artificial intelligence technology.
Challenge
Customer needs a platform to combine big data, and heterogeneous computing to train data for the more intelligent Internet of Things. Visual understanding includes multiple layers of building basic data to motifs to part of objects to higher level of objects.
Recommendation
End customers consistently choose SYS-4028GR-TR with Nvidia GPUs for highest level of parallel computation per node for their AI training module.
Key Applications:
Key Features:
Artificial Intelligence
Big Data Analytics, HPC
Research Lab/National Lab
Astrophysics, Business Intelligence
NVIDIA Tesla V100 Enabled Design for 8 GPUs
Optimized for GPU Direct RDMA
Support up to 8 x NVMe U.2 drives 15

14. SYS-4029GP-TRT2 Key Applications: Key Features:
Processor Support
Dual socket P (LGA 3647) supports Intel® Xeon® Scalable Processors, 3 UPI up to 10.4GT/s
Memory Capacity
Up to 3TB ECC 3DS LRDIMM, up to DDR4-2666MHz; 24 DIMM slots
Expansion Slots
11 PCI-e 3.0 x16 (10 double-wide slots for GPU)
1 PCI-e3.0 x8
I/O ports
1x VGA, 2x 10GbaseT LAN, 4x USB 3.0, and 1x IPMI dedicated LAN port, 1x M.2 NVMe
System management
On board BMC (Baseboard Management Controllers) supports IPMI2.0, media/KVM over LAN with dedicated LAN for system management
Drive Bays
24 hot-swap 2.5” NVMe drives bay
System Cooling
8 heavy duty fans optimize to support 8 GPU cards
Power Supply
4x 2000W (2+2) Titanium Level efficiency redundant power supply 1 3 4
Artificial Intelligence
Big Data Analytics
High-performance Computing
Research Lab/National Lab
Astrophysics, Business Intelligence 2 8 1 2 5 7 3
Key Features: 4
10 x16 PCIe3 GPUs under a single PCIe Root Complex
Supports GPU Direct RDMA
Supports up to 205W CPUs 6 5
CPU
LOM
PCIe Switch 6 7 8 16

15. SYS-1029GQ-TXRT/TVRT Key Features: Key Applications:
Processor Support
Dual socket P (LGA 3647) supports Intel® Xeon® Scalable Processors, 3 UPI up to 10.4GT/s
Quad Tesla SXM2 GPU (P100/V100)
Memory Capacity
Up to 1.5TB ECC 3DS LRDIMM, up to DDR4-2666MHz; 12 DIMM slots
Expansion Slots
2 x16 (FHFL/LP) from PLX;
2 x16 (FHFL/LP) from CPU
I/O ports
1x VGA, 2x 10GbaseT LAN, 2x USB 3.0,
and 1x IPMI dedicated LAN port
Drive Bays
Optional 2x 2.5” NVMe drives bays; 4x total 2.5” HDD bays
System Cooling
7 counter rotating fans with optimal fan speed
Power Supply
2000W Titanium redundant power supply 4 1 7 3 2 1 2 3 3 5 6 4 5 6
Key Features: 7
Key Applications:
NVIDIA Tesla V100 Enabled Design
Optimized for GPU Direct RDMA
Optional NVMe support
HPC
Artificial Intelligence
Big Data Analytics
Research Lab 17