Intel® Xeon® Scalable Processors

Drive actionable insight, count on hardware-based security, and deploy dynamic service delivery with Intel® Xeon® Scalable processors. Support your hybrid cloud infrastructure and most demanding applications – including in-memory analytics, artificial intelligence, autonomous driving, high performance computing (HPC), and network transformation.

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Intel® Xeon® Platinum Processors

  • Demanding, mission-critical AI, analytics, hybrid-cloud workloads
  • Best performance
  • 2,4,8+ socket scalability

Intel® Xeon® Gold Processors

  • Workload-optimized performance, advanced reliability
  • Highest memory speed, capacity, and interconnects
  • Enhanced 2-4 socket scalability

Intel® Xeon® Silver Processors

  • Essential performance and power efficiency
  • Improved memory speed
  • Moderate range compute, network, and storage

Intel® Xeon® Bronze Processors

  • Affordable performance for small business and basic storage
  • Hardware-enhanced security
  • Reliable 2-socket scalability

Do More with Your Cloud Investment

Deliver the powerful performance per dollar you need on Intel® technology. Critical data-heavy workloads such as database, high performance computing (HPC), and web perform better at a lower total cost of ownership on Intel® architecture-based clouds.1 2 3 4 5

2.84x Higher Performance

Up to 2.84x higher performance/$ on database workloads, including HammerDB PostgreSQL*, and MongoDB*.1

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4.15x Higher Performance

Up to 4.15x higher performance/$ on High Performance LINPACK* and LAMMPS*.2

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1.74x Better Performance

Better performance/$ on Server-Side Java and 1.74x better performance /$ on WordPress PHP/HHVM.3

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2.25x Higher Performance

Up to 2.25x higher performance/$ for memory bandwidth applications.4

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The Intel Data-Centric Portfolio

Move Faster

Move Data Faster with Intel® Ethernet

Move data faster and accelerate delivery of new services and capabilities with Intel® Ethernet.

Learn more about Intel® Ethernet ›

Store More

Once-in-a-Generation Innovation

Optimize, store, and move larger, more complicated data sets with Intel® Optane™ DC technology. Available in a variety of products and solutions, this revolutionary innovation fills critical gaps in the storage and memory hierarchy delivering persistent memory, large memory pools, fast caching and fast storage.

Intel® Optane™ DC persistent memory ›

Intel® Optane™ DC SSDs ›

Process Everything

Performance to Propel Insights

Intel’s industry-leading, workload optimized platforms, with built-in AI acceleration, provide the seamless performance foundation, to help speed data’s transformative impact, from the multi-cloud to the intelligent edge and back.

Intel® Xeon® processors ›

Intel® FPGA ›

Intel® Xeon® Scalable Platform: The Foundation for Data-Centric Innovation

Groundbreaking platform innovations for digital transformation.

Performance to Propel Insights

2nd Gen Intel® Xeon® Scalable processors deliver industry leading, workload optimized performance, with built-in AI acceleration, providing a seamless performance foundation, to help speed data’s transformative impact, from the multi-cloud to the intelligent edge and back.

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Business Resilience with Hardware-Enhanced Security

Enhanced data protection by design. Intel’s hardware-enhanced security helps to thwart malicious exploits while maintaining workload integrity and performance. Encryption efficiency to provide trusted data service delivery at rest, in use, and in-flight.

Intel® Security Libraries for Data Center (Intel® SecL - DC)

Build a Trusted Infrastructure

Agile Service Delivery

Platform innovations and hardware-enhanced virtualization across compute, network, storage, all with support for a new class of memory innovation that fuels the cost-efficient, flexible, scalable multi-cloud, to consistently deliver amazing business-to-business and business-to-consumer experiences.

Intel® Infrastructure Management Technologies

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Transform Critical Data-Centric Workloads

See how 2nd Gen Intel® Xeon® Scalable processors and Intel’s industy-leading data-centric portfolio can help you modernize your infrastructure and accelerate data insights across AI, analytics, cloud, and HPC.

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Accelerate Time to Value with Intel® Select Solutions

Simplify your data center deployment with rigorously benchmark tested and verified solutions optimized for real-world performance. These solutions accelerate infrastructure deployment on Intel® Xeon® processors for today’s critical workloads.

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Learn More About Intel's Data-Centric Platform

Watch the video to discover how Intel's data-centric portfolio of products unlocks benefits from the heart of the data center to the edge and back.

Product and Performance Information

1

Results calculated by Intel P2CA using AWS pricing ($/hour, standard 1-year term, no up-front) as of 12th January, 2019.
Performance per dollar testing done on AWS* EC2 R5 and R5a instances (https://aws.amazon.com/ec2/instance-types/), comparing 96 vCPU Intel® Xeon® Scalable processor performance per dollar to AMD EPYC* processor performance per dollar.

Workload: HammerDB* PostgreSQL*
Results: AMD EPYC performance per dollar = baseline of 1; Intel® Xeon® Scalable processor performance per dollar = 1.85X (higher is better)
Database: HammerDB – PostgreSQL (higher is better):
AWS R5.24xlarge (Intel) Instance, HammerDB 3.0 PostgreSQL 10.2, Memory: 768GB, Hypervisor: KVM; Storage Type: EBS io1, Disk Volume 200GB, Total Storage 200GB, Docker version: 18.06.1-ce, RedHat* Enterprise Linux 7.6, 3.10.0-957.el7.x86_64, 6400MB shared_buffer, 256 warehouses, 96 users. Score “NOPM” 439931, measured by Intel on 12/11/18-12/14/18.
AWS R5a.24xlarge (AMD) Instance, HammerDB 3.0 PostgreSQL 10.2, Memory: 768GB, Hypervisor: KVM; Storage Type: EBS io1, Disk Volume 200GB, Total Storage 200GB, Docker version: 18.06.1-ce, RedHat* Enterprise Linux 7.6, 3.10.0-957.el7.x86_64, 6400MB shared_buffer, 256 warehouses, 96 users. Score “NOPM” 212903, measured by Intel on 12/20/18.

Workload: MongoDB*
Results: AMD EPYC performance per dollar = baseline of 1; Intel® Xeon® Scalable processor performance per dollar = 2.84X (higher is better)
Database: MongoDB (higher is better):
AWS R5.24xlarge (Intel) Instance, MongoDB v4.0, journal disabled, sync to filesystem disabled, wiredTigeCache=27GB, maxPoolSize = 256; 7 MongoDB instances, 14 client VMs, 1 YCSB client per VM, 96 threads per YCSB client, RedHat* Enterprise Linux 7.5, Kernel 3.10.0-862.el7.x86_64, Score 1229288 ops/sec, measured by Intel on 12/10/18.
AWS R5a.24xlarge (AMD) Instance, MongoDB v4.0, journal disabled, sync to filesystem disabled, wiredTigeCache=27GB, maxPoolSize = 256; 7 MongoDB instances, 14 client VMs, 1 YCSB client per VM, 96 threads per YCSB client, RedHat* Enterprise Linux 7.5, Kernel 3.10.0-862.el7.x86_64, Score 388596 ops/sec, measured by Intel on 12/10/18.
For more details visit www.intel.com/benchmarks.

2

Results calculated by Intel P2CA using AWS pricing ($/hour, standard 1-year term, no up-front) as of 12th January, 2019.
Performance per dollar testing done on AWS* EC2 M5 and M5a instances (https://aws.amazon.com/ec2/instance-types/), comparing 96 vCPU Intel® Xeon® Scalable processor performance per dollar to AMD EPYC* processor performance per dollar.

Workload: LAMMPS*
Results: AMD EPYC performance per dollar = baseline of 1; Intel® Xeon® Scalable processor performance per dollar = 4.15X (higher is better)
HPC Materials Science – LAMMPS (higher is better):
AWS M5.24xlarge (Intel) Instance, LAMMPS version: 2018-08-22 (Code: https://lammps.sandia.gov/download.html), Workload: Water – 512K Particles, Intel ICC 18.0.3.20180410, Intel® MPI Library for Linux* OS, Version 2018 Update 3 Build 20180411, 48 MPI Ranks, RedHat* Enterprise Linux 7.5, Kernel 3.10.0-862.el7.x86_64, OMP_NUM_THREADS=2, Score 137.5 timesteps/sec, measured by Intel on 10/31/18.
AWS M5a.24xlarge (AMD) Instance, LAMMPS version: 2018-08-22 (Code: https://lammps.sandia.gov/download.html), Workload: Water – 512K Particles, Intel ICC 18.0.3.20180410, Intel® MPI Library for Linux* OS, Version 2018 Update 3 Build 20180411, 48 MPI Ranks, RedHat* Enterprise Linux 7.5, Kernel 3.10.0-862.el7.x86_64, OMP_NUM_THREADS=2, Score 55.8 timesteps/sec, measured by Intel on 11/7/18.
Changes for AMD to support AVX2 (AMD only supports AVX2, so these changes were necessary):
sed -i 's/-xHost/-xCORE-AVX2/g' Makefile.intel_cpu_intelmpi
sed -i 's/-qopt-zmm-usage=high/-xCORE-AVX2/g' Makefile.intel_cpu_intelmpi

Workload: High-performance Linpack*
Results: AMD EPYC performance per dollar = baseline of 1; Intel® Xeon® Scalable processor performance per dollar = 4.15X (higher is better)
HPC Linpack (higher is better):
AWS M5.24xlarge (Intel) Instance, HP Linpack Version 2.2 (https://software.intel.com/en-us/articles/intel-mkl-benchmarks-suite Directory: benchmarks_2018.3.222/linux/mkl/benchmarks/mp_linpack/bin_intel/intel64), Intel ICC 18.0.3.20180410 with AVX512, Intel® MPI Library for Linux* OS, Version 2018 Update 3 Build 20180411, RedHat* Enterprise Linux 7.5, Kernel 3.10.0-862.el7.x86_64, OMP_NUM_THREADS=24, 2 MPI processes, Score 3152 GB/s, measured by Intel on 10/31/18.
AWS M5a.24xlarge (AMD) Instance, HP Linpack Version 2.2, (HPL Source: http://www.netlib.org/benchmark/hpl/hpl-2.2.tar.gz; Version 2.2; icc (ICC) 18.0.2 20180210 used to compile and link to BLIS library version 0.4.0; https://github.com/flame/blis; Addt’l Compiler flags: -O3 -funroll-loops -W -Wall –qopenmp; make arch=zen OMP_NUM_THREADS=8; 6 MPI processes.), Intel ICC 18.0.3.20180410 with AVX2, Intel® MPI Library for Linux* OS, Version 2018 Update 3 Build 20180411, RedHat* Enterprise Linux 7.5, Kernel 3.10.0-862.el7.x86_64, OMP_NUM_THREADS=8, 6 MPI processes, Score 677.7 GB/s, measured by Intel on 11/7/18.

3

Results calculated by Intel P2CA using AWS pricing ($/hour, standard 1-year term, no up-front) as of 12th January, 2019.
Performance per dollar testing done on AWS* EC2 M5 and M5a instances (https://aws.amazon.com/ec2/instance-types/), comparing 96 vCPU Intel® Xeon® Scalable processor performance per dollar to AMD EPYC* processor performance per dollar.

Workload: Server Side Java* 1 JVM
Results: AMD EPYC performance per dollar = baseline of 1; Intel® Xeon® Scalable processor performance per dollar = 1.74X (higher is better)
Server Side Java (higher is better):
AWS M5.24xlarge (Intel) Instance, Java Server Benchmark No NUMA binding, 2JVM, OpenJDK 10.0.1, RedHat* Enterprise Linux 7.5, Kernel 3.10.0-862.el7.x86_64, Score 101767 Transactions/sec, measured by Intel on 11/16/18.
AWS M5a.24xlarge (AMD) Instance, Java Server Benchmark No NUMA binding, 2JVM, OpenJDK 10.0.1, RedHat* Enterprise Linux 7.5, Kernel 3.10.0-862.el7.x86_64, Score 52068 Transactions/sec, measured by Intel on 11/16/18.

Workload: Wordpress* PHP/HHVM*
Results: AMD EPYC performance per dollar = baseline of 1; Intel® Xeon® Scalable processor performance per dollar = 1.75X (higher is better)
Web Front End Wordpress (higher is better):
AWS M5.24xlarge (Intel) Instance, oss-performance/wordpress Ver 4.2.0; Ver 10.2.19-MariaDB-1:10.2.19+maria~bionic; Workload Version': u'4.2.0; Client Threads: 200; PHP 7.2.12-1; perfkitbenchmarker_version="v1.12.0-944-g82392cc; Ubuntu 18.04, Kernel Linux 4.15.0-1025-aws, Score 3626.11 TPS, measured by Intel on 11/16/18.
AWS M5a.24xlarge (AMD) Instance, oss-performance/wordpress Ver 4.2.0; Ver 10.2.19-MariaDB-1:10.2.19+maria~bionic; Workload Version': u'4.2.0; Client Threads: 200; PHP 7.2.12-1; perfkitbenchmarker_version="v1.12.0-944-g82392cc; Ubuntu 18.04, Kernel Linux 4.15.0-1025-aws, Score 1838.48 TPS, measured by Intel on 11/16/18.
For more details visit www.intel.com/benchmarks.

4

AWS M5.4xlarge (Intel) Instance, McCalpin Stream (OMP version), (Source: https://www.cs.virginia.edu/stream/FTP/Code/stream.c); Intel ICC 18.0.3 20180410 with AVX512, -qopt-zmm-usage=high, -DSTREAM_ARRAY_SIZE=134217728 -DNTIMES=100 -DOFFSET=0 –qopenmp, -qoptstreaming-stores always -o $OUT stream.c, Red Hat* Enterprise Linux 7.5, Kernel 3.10.0-862.el7.x86_64, OMP_NUM_THREADS: 8, KMP_AFFINITY: proclist=[0-7:1], granularity=thread, explicit, Score 81216.7 MB/s, measured by Intel on 12/6/18.
AWS M5a.4xlarge (AMD) Instance, McCalpin Stream (OMP version), (Source: https://www.cs.virginia.edu/stream/FTP/Code/stream.c); Intel ICC 18.0.3 20180410 with AVX2, -DSTREAM_ARRAY_SIZE=134217728, -DNTIMES=100 -DOFFSET=0 -qopenmp -qopt-streaming-stores always -o $OUT stream.c, Red Hat* Enterprise Linux 7.5, Kernel 3.10.0-862.el7.x86_64, OMP_NUM_THREADS: 8, KMP_AFFINITY : proclist=[0-7:1], granularity=thread,explicit, Score 32154.4 MB/s, measured by Intel on 12/6/18.
OpenFOAM Disclaimer: This offering is not approved or endorsed by OpenCFD Limited, producer and distributor of the OpenFOAM software via www.openfoam.com, and owner of the OpenFOAM* and OpenCFD* trademark.
AWS pricing as of 12th January 2019 Standard 1-Year term Reserved Instance Pricing (https://aws.amazon.com/ec2/pricing/reserved-instances/pricing/) On Demand Linux/Unix Usage Pricing per hour (https://aws.amazon.com/ec2/pricing/on-demand/).

5

Up to 30x Inference Throughput Improvement on Intel® Xeon® Platinum 9282 processor with Intel® Deep Learning Boost (Intel® DL Boost): Tested by Intel as of 2/26/2019. Platform: Dragon rock 2 socket Intel® Xeon® Platinum 9282 processor (56 cores per socket), HT ON, turbo ON, Total Memory 768 GB (24 slots/ 32 GB/ 2933 MHz), BIOS:SE5C620.86B.0D.01.0241.112020180249, CentOS 7 Kernel 3.10.0-957.5.1.el7.x86_64, Deep Learning Framework: Intel® Optimization for Caffe* version: https://github.com/intel/caffe d554cbf1, ICC 2019.2.187, MKL DNN version: v0.17 (commit hash: 830a10059a018cd2634d94195140cf2d8790a75a), model: https://github.com/intel/caffe/blob/master/models/intel_optimized_models/int8/resnet50_int8_full_conv.prototxt, BS=64, No datalayer syntheticData:3x224x224, 56 instance/2 socket, Datatype: INT8 vs Tested by Intel as of July 11th 2017: 2S Intel® Xeon® Platinum 8180 processor CPU @ 2.50GHz (28 cores), HT disabled, turbo disabled, scaling governor set to "performance" via intel_pstate driver, 384GB DDR4-2666 ECC RAM. CentOS Linux* release 7.3.1611 (Core), Linux* kernel 3.10.0-514.10.2.el7.x86_64. SSD: Intel® SSD Data Center S3700 Series (800GB, 2.5in SATA 6Gb/s, 25nm, MLC). Performance measured with: Environment variables: KMP_AFFINITY='granularity=fine, compact‘, OMP_NUM_THREADS=56, CPU freq set with CPU Power frequency-set -d 2.5G -u 3.8G -g performance. Caffe: (http://github.com/intel/caffe/), revision f96b759f71b2281835f690af267158b82b150b5c. Inference measured with “caffe time --forward_only” command, training measured with "caffe time" command. For "ConvNet" topologies, synthetic dataset was used. For other topologies, data was stored on local storage and cached in memory before training. Topology specs from https://github.com/intel/caffe/tree/master/models/intel_optimized_models(ResNet-50). Intel® C++ Compiler ver. 17.0.2 20170213, Intel® Math Kernel Library (Intel® MKL) small libraries version 2018.0.20170425. Caffe run with "numactl -l".