Super Micro Technology Computing X11 Generation

Intelligent Computing Artificial Intelligence Machine Learning Neural Network Deep Learning

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

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

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

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

MultiThread

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

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

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

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 0 1 2 3 4 5 6 7 SINGLE 0 1 2 3 4 5 6 7

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

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

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

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

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