Transform the Data Center with Workload Optimization

Today’s modern data centers are being transformed to meet the demands of increased networking bandwidth, increased processing with workloads like artificial intelligence, and with more stringent requirements like reduced query response time. Data center administrators expect all of these needs to be provided with a lower TCO while also enabling new services. Intel is helping customers meet these demands with Intel® accelerators that enhance the performance of specific workloads while improving power consumption.

Optimize Key Workloads with Intel® Accelerators

Designed and optimized to solve specific customer problems, Intel’s portfolio of accelerator solutions enables high-performance, hardware-based workload acceleration with excellent cost and power efficiency. See how.

Find out why cloud, communications, and other service providers in the visual computing market choose Intel® Visual Compute Accelerator (Intel® VCA) to give them a competitive edge.

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Find valuable developer information and resources for deep learning solutions and applications with Intel® Nervana™ products.

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Intel is transforming the communications systems inside and outside of the data center.

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Intel® Board Level Solutions

Intel® acceleration cards target specific workloads that can be better managed with optimized acceleration.

Designed to deliver graphics-intensive workloads such as 3D CAD and cloud gaming applications. Three Intel® Xeon® processor E3-1500 v5. Built around the energy efficient Intel® Iris® Pro graphics P580.

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Designed for dense media transcoding and 3D remote graphics rendering. Three Intel® Xeon® processor E3-1283L v4 with Intel® Advanced Vector Extensions 2 (Intel® AVX2). Up to 96 GB of DDR3 memory.

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Intel® Acceleration for Application Developers

Intel has an extensive developer base in the data center. These developers, who are very familiar with the Intel® Xeon® processor and the Intel® architecture, have access to the broadest portfolio of accelerators – from built-in acceleration in Intel® Xeon® processors to the Intel® Iris® Pro graphics processor. Intel is making workload optimization with Intel® Xeon® CPU and acceleration easier to use.

A key challenge for application developers is time to market. Intel is enabling Intel® architecture users, traditional OS developers, open language users, and other ecosystem developers with tools built around industry standards. Unlike other solutions, developers using the Intel® acceleration portfolio can use the tool, SDK, or OS they are comfortable with, without learning a new language. A developer may leverage his experience with the Intel® architecture and determine the best accelerator for their workload or application. Developers can create their application solution from a new system with the Intel® Xeon® Scalable processor or retrofit an existing Intel® Xeon® CPU system with Intel and partner accelerator cards.

Intel® Acceleration News

New Solutions to Enable FPGA Acceleration in the Data Center

Monday, October 2, 2017

Intel has announced the first in a family of Intel® Programmable Acceleration Cards, the Intel® Programmable Acceleration Card (Intel® PAC) with the Intel® Arria® 10 GX FPGA (A10GX). This is the first FPGA-based acceleration platform to support the Acceleration Stack for Intel® Xeon® CPU with FPGAs. In the near future, Intel will also offer Intel® Xeon® processors with Integrated FPGA for a high-bandwidth, cache-coherent, low-latency solution. 

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Acceleration Stack for Intel® Xeon® CPU with FPGAs – Enhanced Performance, Simplified

Monday, September 4, 2017

Intel has announced a new set of software tools to make FPGA programming accessible to mainstream developers. The Acceleration Stack for Intel® Xeon® CPU with FPGAs makes it easier to develop and deploy Intel FPGAs for workload optimization in the data center. As part of this announcement, Intel has released the Open Programmable Acceleration Engine (OPAE) on Github to foster an open ecosystem and encourage the use of FPGA acceleration in the data center. 

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