Intel® Select Solutions for AI Inferencing are turnkey platforms that provide pre-bundled, verified, and optimized solutions for low-latency, high throughput inference performed on a CPU, not on a separate accelerator card.

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Base and Plus Configurations for the Intel Select Solutions for AI Inferencing v2

Ingredient

Intel Select Solutions for AI Inferencing v2 Base Configuration

Intel Select Solutions for AI Inferencing v2 Plus Configuration

Number of Nodes

Single-node configuration

Single-node configuration

Processor

2 x Intel® Xeon® Gold 6248 processor (2.50 GHz, 20 cores, 40 threads), or a higher number Intel® Xeon® Scalable processor

2 x Intel® Xeon® Platinum 8268 processor (2.90 GHz, 24 cores, 48 threads), or a higher number Intel Xeon Scalable processor

Memory

192 GB or higher (12 x 16 GB 2,666 MHz DDR4 ECC RDIMM)

384 GB (12 x 32 GB 2,934 MHz DDR4 ECC RDIMM)

Boot Drive

1 x 256 GB Intel® SSD DC P4101 Series (M.2 80 mm PCIe* 3.0 x4, 3D2, TLC) or higher

1 x 256 GB Intel SSD DC P4101 Series (M.2 80 mm PCIe* 3.0 x4, 3D2, TLC) or higher

Storage

Data drive: 1.6 TB NVM Express* (NVMe*) Intel® SSD DC P4510 Series

Cache drive: 375 GB Intel® Optane™ SSD DC P4800X U.2 NVMe* SSD

Data drive: 1.6 TB NVMe* Intel SSD DC P4510 Series

Cache drive: 375 GB Intel Optane SSD DC P4800X U.2 NVMe* SSD

Data Network

1 x Intel® Ethernet Converged Network Adapter (Intel® Ethernet CNA) XXV710-DA2 SFP28 DA Copper PCIe* x 8 dual-port 25/10/1 GbE

1 x Intel Ethernet Converged Network Adapter (Intel Ethernet CNA) XXV710-DA2 SFP28 DA Copper PCIe* x 8 dual-port 25/10/1 GbE

Management Network

Integrated 1 GbE port 0/RMM port

Integrated 1 GbE port 0/RMM port

Software

Linux OS

CentOS Linux release 7.6.1810/Red Hat Enterprise Linux* (RHEL) 7

CentOS Linux release 7.6.1810/Red Hat Enterprise Linux* (RHEL) 7

Intel® Math Kernel Library (Intel® MKL)

Intel Math Kernel Library (Intel MKL) version 2019 Update 4

Intel Math Kernel Library (Intel MKL) version 2019 Update 4

Intel® Distribution of OpenVINO™ Toolkit

2019 R1.0.1

2019 R1.0.1

OpenVINO™ Model Server

0.4

0.4

TensorFlow

1.14

1.14

PyTorch

1.2.0

1.2.0

MXNet

1.3.1

1.3.1

Intel® Distribution for Python*

2019 Update 1

2019 Update 1

Intel® Math Kernel Library for Deep Neural Networks (Intel® MKL-DNN)

0.19 (implied by the OpenVINO™ toolkit)

0.19 (implied by the OpenVINO toolkit)

Deep Learning Reference Stack (DLRS)

v4.0

v4.0

Source-to-Image

1.1.14

1.1.14

Docker

18.09

18.09

Kubernetes

v1.15.3

v1.15.3

Kubeflow

v0.6.1

v0.6.1

Helm

2.14.3

2.14.3

Seldon Core

0.3.2

0.3.2

Ceph

v14.2.1

v14.2.1

Min.io (Rook v1.0)

RELEASE.2019-04-23T23-50-36Z

RELEASE.2019-04-23T23-50-36Z

Rook

1.0.5

1.0.5

Other

Trusted Platform Module (TPM)

TPM 2.0

TPM 2.0

Minimum Performance Standards

Verified to meet or exceed the following minimum performance capabilities:

Classification Using ResNet-50 on OpenVINO Toolkit

1,900 images per second (91 percent top-5 accuracy)

2,650 images per second (91 percent top-5 accuracy)

Scaling in Emulated Real-World Scenario from 1 Node to 2 Nodes Up to 1.91x1 Up to 1.91x2

Business Value of Choosing a Plus Configuration Over a Base Configuration

The Plus configuration provides up to 39 percent faster inferencing performance.1

**Recommended, not required

Información sobre productos y desempeño

1

Prueba realizada por Intel el 9 de octubre de 2019. Configuración de prueba: Dos nodos, procesador: 2 x Intel® Xeon® Gold 6248 (2.50 GHz, 20 núcleos, 40 hilos), 12 x 16 GB 2,666 MHz DDR4 ECC RDIMM (192 GB de memoria total), unidad de inicio: 1 x 256 GB Intel® SSD DC serie P4101  (M.2 80 mm PCIe* 3.0 x4, 3D2, TLC), unidad de datos: 1.6 TB NVM Express* (NVMe*) Intel® SSD serie P4510, unidad de caché: 375 GB de Intel® Optane™ SSD DC P4800X U.2 NVMe* SSD, red de datos: 1 x 10Gb Intel® Ethernet Converged Network Adapter X722 (Intel® Ethernet CNA X722), red de administración: puerto 0 integrado de 1 gigabit Ethernet (GbE)/puerto RMM. Software: CentOS* versión de Linux 7.6.1810/Red Hat Enterprise Linux* (RHEL) 7, Intel® Math Kernel Library (Intel® MKL) versión 2019 actualización 4, distribución Intel® de OpenVINO™ kit de herramientas 2019 R1.0.1, OpenVINO™ servidor modelo 0.4, distribución de Intel® para Python* 2019 actualización 1, Intel® Math Kernel Library para Deep Neural Networks (Intel® MKL-DNN) 0.19, Deep Learning Reference Stack (DLRS) v4.0, Docker v18.09, Helm v2.14.3, Kubernetes v1.15.3, Kubeflow v0.6.1, Seldon Core v0.3.2, Rook v1.0.5, Ceph v14.2.1, Min.io (Rook v1.0) VERSIÓN.2019-04-23T23-50-36Z. Scalar en un escenario real y emulado: prueba de rendimiento: desempeño normal de la tecnología 1 (Intel® Hyper-Threading (Intel® HT Technology): desactivado).

2

Prueba realizada por Intel el 9 de octubre de 2019. Configuración de prueba: 2 nodos, procesador: 2 x Intel® Xeon® Platinum 8268 1 (2,90 GHz, 24 núcleos, 48 hilos), 12 x 16 GB 2,666 MHz DDR4 ECC RDIMM (192 GB de memoria total), unidad de arranque: 1 x 256 GB Intel® SSD serie DC P4101 (M.2 80 mm PCIe* 3.0 x4, 3D2, TLC), unidad de datos: 1.6 TB NVM Express* (NVMe*) Intel® SSD serie P4510, unidad de caché: Intel® Optane™ SSD DC P4800X U.2 NVMe* SSD 375 GB red de datos: adaptador de red 1 x 10Gb Intel® Ethernet Converged X722 (Intel® Ethernet CNA X722) red de gestión de Ethernet: puerto 0 integrado 1 gigabit Ethernet (GbE) /puerto RMM. Software: CentOS* versión de Linux 7.6.1810/Red Hat Enterprise Linux* (RHEL) 7, Intel® Math Kernel Library (Intel® MKL) versión 2019 actualización 4, distribución Intel® de OpenVINO™ kit de herramientas 2019 R1.0.1, OpenVINO™ servidor modelo 0.4, distribución de Intel® para Python* 2019 actualización 1, Intel® Math Kernel Library para Deep Neural Networks (Intel® MKL-DNN) 0.19, Deep Learning Reference Stack (DLRS) v4.0, Docker v18.09, Helm v2.14.3, Kubernetes v1.15.3, Kubeflow v0.6.1, Seldon Core v0.3.2, Rook v1.0.5, Ceph v14.2.1, Min.io (Rook v1.0) VERSIÓN.2019-04-23T23-50-36Z. Escalar en un escenario real y emulado: prueba de rendimiento: desempeño normal de la tecnología 1.91 (Intel® Hyper-Threading (Intel® HT Technology): desactivado).