Future Proof Your Data Center with AI Acceleration Built In. Only on Intel.
The new 2nd Generation Intel® Xeon® Scalable processors with Intel® Deep Learning Boost (Intel® DL Boost) accelerates AI inference up to 30x, helping you get the most out of your investment.1
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Uncover new answers blazingly fast from your data.
Artificial Intelligence (AI)
Artificial Intelligence (AI) leads to remarkable breakthroughs for businesses and their customers. Explore the accelerated path from AI theory to real business value with deep learning boost.
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Advanced Analytics
Advanced Analytics reshapes the enterprise with new discoveries, better customer experiences, and new products and services. See how to build breakthrough in-memory analytics with Intel® Optane™ DC persistent memory.
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High Performance Computing (HPC)
Shorten time to innovation by using your high performance computing (HPC) infrastructure for Artificial Intelligence (AI) in three steps.
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Reimagine Your Architecture
Win in the data era with breakthrough Intel® technology.
Virtualization
Discover how to build out virtualized infrastructures to make the best use case of cloud-based resources, and ensure a seamless platform across public and private cloud environments.
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Hybrid Cloud
Hybrid clouds deliver the agility and security your business needs to innovate rapidly. Need help determining optimal placement for your workloads across private and publish clouds?
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Data-Centric Innovation
Move, store, and process data with confidence across the most demanding workloads: From multi-cloud to the edge and back.
Intel® Xeon® Scalable Processors
Workload-optimized to support high-demand applications and drive actionable insight.
Intel® Optane™ Technology
All-new premium class of memory that can change the ways we build and use computers.
Intel® Select Solution
Simplify and accelerate the deployment of your data center infrastructure.
Notices and Disclaimers:
Software and workloads used in performance tests may have been optimized for performance only on Intel® microprocessors. Performance tests, such as SYSmark* and MobileMark*, are measured using specific computer systems, components, software, operations, and functions. Any change to any of those factors may cause the results to vary. You should consult other information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products. For more complete information visit www.thailand.intel.com/benchmarks.
Performance results are based on testing as of the date indicated in the configuration details and may not reflect all publicly available security updates. See configuration disclosure for details. No product or component can be absolutely secure.
Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel® microprocessors. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel® microprocessors. Certain optimizations not specific to Intel microarchitecture are reserved for Intel® microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice. Notice Revision #20110804.
Cost reduction scenarios described are intended as examples of how a given Intel®-based product, in the specified circumstances and configurations, may affect future costs and provide cost savings. Circumstances will vary. Intel does not guarantee any costs or cost reduction.
Intel® Advanced Vector Extensions (Intel® AVX) provides higher throughput to certain processor operations. Due to varying processor power characteristics, utilizing AVX instructions may cause a) some parts to operate at less than the rated frequency and b) some parts with Intel® Turbo Boost Technology 2.0 to not achieve any or maximum turbo frequencies. Performance varies depending on hardware, software, and system configuration and you can learn more at http://www.intel.com/go/turbo.
Intel does not control or audit third-party benchmark data or the web sites referenced in this document. You should visit the referenced web site and confirm whether referenced data are accurate.
ข้อมูลผลิตภัณฑ์และประสิทธิภาพ
ปรับปรุงทรูพุตการอนุมาน 30 เท่าในโปรเซสเซอร์ Intel® Xeon® Platinum 9282 ที่มี Intel® Deep Learning Boost (Intel® DL Boost): ทดสอบโดย Intel เมื่อวันที่ 2/26/2019 แพลตฟอร์ม: โปรเซสเซอร์ Intel® Xeon® Platinum 9282 (56 คอร์ต่อซ็อกเก็ต) Dragon rock 2 ซ็อกเก็ต , เปิด HT, เปิดเทอร์โบ, หน่วยความจำทั้งหมด 768 GB (24 ช่อง/ 32 GB/ 2933 MHz), BIOS: SE5C620.86B.0D.01.0241.112020180249, Centos* 7 Kernel 3.10.0-957.5.1.el7, เฟรมเวิร์คการเรียนรู้เชิงลึก: Intel® Optimization for Caffe* เวอร์ชั่น: https://github.com/intel/caffe d554cbf1, ICC 2019.2.187, MKL DNN เวอร์ชั่น: v0.17 (คอมมิทแฮช: 830a10059a018cd2634d94195140cf2d8790a75a), โมเดล: https://github.com/intel/caffe/blob/master/models/intel_optimized_models/int8/resnet50_int8_full_conv.prototxt, BS=64, ไม่มี syntheticData: 3x224x224, 56 ระบบ/2 ซ็อกเก็ต, ชุดข้อมูล: INT8 เปรียบเทียบกับการทดสอบโดย Intel เมื่อวันที่ 11 กรกฎาคม 2017: CPU โปรเซสเซอร์ Intel® Xeon® Platinum 8180 2S @ 2.50GHz (28 คอร์), ปิด HT, ปิดเทอร์โบ, ตั้งตัวควบคุมการปรับขยายเป็น “ประสิทธิภาพ” ผ่านไดรเวอร์ intel_pstate driver, 384GB DDR4-2666 ECC RAM CentOS Linux* รีลีส 7.3.1611 (Core), Linux* kernel 3.10.0-514.10.2.el7.x86_64 SSD: ไดรฟ์ Intel® Solid State สำหรับศูนย์ข้อมูล ซีรี่ส์ S3700 (800GB, 2.5in SATA 6Gb/s, 25nm, MLC) วัดประสิทธิภาพด้วย: ตัวแปรสภาพแวดล้อม: KMP_AFFINITY=’granularity=fine, compact‘, OMP_NUM_THREADS=56, ตั้งความเร็วของ CPU ด้วย CPU Power Frequency-Set -d 2.5G -u 3.8G -g performance Caffe: (http://github.com/intel/caffe/), การปรับปรุงแก้ไข f96b759f71b2281835f690af267158b82b150b5c. วัดการอนุมานด้วยคำสั่ง “caffe time --forward_only” วัดการฝึกฝนด้วยคำสั่ง “caffe time” มีการใช้ชุดข้อมูลสังเคราะห์สำหรับทอพอโลยี “ConvNet” สำหรับทอพอโลยีอื่นๆ จะมีการจัดเก็บข้อมูลในอุปกรณ์จัดเก็บข้อมูลบนเครื่อง และแคชมาในหน่วยความจำก่อนการฝึก ข้อมูลจำเพาะทอพอโลยีจาก https://github.com/intel/caffe/tree/master/models/intel_optimized_models (ResNet-50) Intel® C++ คอมไพเลอร์เวอร์ชัน 17.0.2 20170213, Intel® Math Kernel Library (Intel® MKL) เวอร์ชั่นไลบรารีขนาดเล็ก 2018.0.20170425 รัน Caffe ด้วย "numactl -l"