Intel

Thousands of Intel’s employees connect to the corporate Wi-Fi network every day. When connectivity issues occur, both productivity and user experience (UX) suffer. Intel IT makes every effort to optimize the network’s performance. Still, until recently, we had little visibility into client behavior through traditional network monitoring solutions because they report issues only from the network infrastructure perspective. At the same time, endpoint IT tools are limited to operating system data.

Based on its existing market presence with PC Wi-Fi products, Intel’s Client Computing product group developed Intel Connectivity Analytics technology. The product group collaborated with Cisco—a well-known enterprise Wi-Fi network infrastructure supplier—and Intel IT to develop compelling use cases and solutions that utilize Intel Connectivity Analytics. Intel IT provided product feedback and practical applications of the technology in our enterprise environment and helped optimize the use cases over Intel’s network infrastructure. Our input helped to better define the data and analytics needed to achieve the desired business outcomes, such as faster troubleshooting, mean time to repair (MTTR), reduced network total cost of ownership, and a better UX.

Intel IT now uses Intel Connectivity Analytics—delivered through the Cisco Catalyst Center (previously Cisco DNA Center) and cloud dashboard—to improve the management of Intel’s Wi-Fi network. We are also working with the overall ecosystem to expand the use cases for Intel Connectivity Analytics and further enhance AI for IT Operations (AIOps). We have reduced some client-side troubleshooting from upwards of 15 minutes to 10–15 seconds. Similarly, finding the root cause for ubiquitous network issues—which could take days—now often takes seconds as well.

We encourage other IT departments to consider deploying IT tools powered by Intel Connectivity Analytics for Wi-Fi, which is built into Intel Wi-Fi adapters and requires no software installation or maintenance. It can be utilized by Cisco and other Intel Connectivity Analytics Program members.

In addition, we are now working with the Intel Client Computing product group to develop an additional Intel Connectivity Analytics offering that shares data through a PC agent to the cloud and expands the available connectivity analytics beyond Wi-Fi to include Thunderbolt technology, Bluetooth, Ethernet, and more.

Increasing Electronic Design Automation (EDA) performance and throughput is critical to Intel’s silicon Design engineers.

Silicon chip Design engineers at Intel face ongoing challenges: integrating more features into ever-shrinking silicon chips, bringing products to market faster, and keeping Design engineering and manufacturing costs low. Design engineers run more than 273 million compute-intensive batch jobs every week. Each job takes from a few seconds to several days to complete.

As design complexity increases, so do the requirements for compute capacity, so refreshing servers and workstations with higher-performing systems is cost-effective and offers a competitive advantage by enabling faster chip design. Refreshing older servers also enables us to realize data center cost savings. By taking advantage of the performance and power-efficiency improvements in new server generations, we can increase computing capacity within the same data center footprint, helping to avoid expensive data center construction and reduce operational costs due to reduced power consumption.

To meet Design engineers’ computing capacity requirements, Intel IT conducts ongoing throughput performance tests using real-world Intel silicon Design workloads. These tests measure EDA workload throughput and help us analyze the performance improvements—and in turn, business benefits offered by newer generations of Intel® processors.

We recently tested two-socket servers based on the Intel® Xeon® Platinum 8400 and 8500 processor Series, along with the Gold 6400 processor Series. The test included operating single- and multi-threaded EDA applications running Intel silicon Design workloads for more than four days. Select results include the following:

• Higher frequency for per-core performance. For critical-path EDA workloads, selecting a high-frequency CPU like the Intel Xeon Gold 6444Y processor (32 cores per server) can deliver up to 1.14x higher per-core performance compared to lower-frequency, higher-core-count CPUs in the same generation of processors.

• Higher core counts for throughput. For volume validation runs, selecting a higher-core-count CPU at optimal frequency like the Intel Xeon Platinum 8462Y+ processor (64 cores per server) can deliver up to 1.75x higher Register Transfer Level (RTL) Simulation throughput per server when compared to a lower-core-count CPU (32 cores per server) in the same generation of processors. The Intel Xeon Platinum 8462Y+ processor (64 cores per server) completed workloads up to 2.17x faster than a previous-generation Intel Xeon Gold 6346 processor-based server, which has only 32 cores. Compared to a 2nd Gen Intel Xeon Gold 6246R processor (32 cores per server), the server with the newer processor outperformed the older processor by up to 2.40x in throughput.

• Additional benefits from 5th generation processors. At the same Thermal Design Power (TDP) of 350W, the Intel Xeon Platinum 8580 processor completed workloads up to 1.27x faster than a previous-generation Intel Xeon Platinum 8468 processor-based server.

Based on our performance assessment and our refresh cycle, we are deploying servers based on the 4th and 5th Gen Intel Xeon Scalable processor family in our data centers. By doing so, we have significantly increased EDA throughput performance to improve the overall EDA design cycles and optimize time to market of Intel chips.

Learn how Intel’s manufacturing engineers are using natural language processing (NLP) to streamline failure mode and effects analysis (FMEA).

Intel Manufacturing Automation has developed an innovative methodology for performing FMEA in manufacturing by using artificial intelligence (AI) techniques to analyze users’ emotional tone—positive, negative, or neutral—about the manufacturing equipment.

Failure mode and effects analysis (FMEA) is a critical process in manufacturing that is used to identify potential failures, assess their impact, and prioritize preventive actions. The FMEA process involves breaking down the system into its individual components; analyzing each component for potential failure modes; determining the effects of these failures; and assigning a risk priority number based on severity, occurrence, and detectability.

Traditionally, FMEA involves time-consuming manual extraction and analysis of large text data from tool logs and other sources, leading to weeks of engineering effort per analysis. This approach must be repeated across large fleets of tools by the engineers who support these tools.

Our new approach uses natural language processing (NLP) and sentiment analysis (SA) to reduce the labor required for FMEA from weeks to seconds. When we compared the traditional FMEA approach to our SA-based system, the software discovered everything the engineers found with their manual system approach—plus even more that they missed. Our system performed FMEA on six months’ worth of data in under one minute, saving weeks of engineering time.

Our SA analysis extracts keywords from comments, notes, charts, and quality systems data to find words with negative connotations about a tool, such as “abort” or “fail.” We’ve customized the analysis for domain-specific language, such as words and phrases that are specific to the semiconductor fab environment (e.g., “defect” and “excursion”). We also implemented custom replacement keywords (“ABORT” vs. “ABT” vs. “ABRT”) to accommodate various abbreviations and spelling errors commonly found in tool logs and other data sources.

The system analyzes sentence structure and filters out brackets for HTML and other special characters used in programming languages, allowing for a wide variety of inputs. While Intel’s manufacturing logs are predominantly in English, the libraries can be extended to handle multilingual input.

Integration with our in-house factory data analytics platform, Data on the Spot (DOTS), further democratizes FMEA results by enabling users to easily access this data and use it to identify root causes from the original sources. The system is now deployed across all Intel semiconductor factories, with a focus on front-end manufacturing.

The Intel® architecture-based components of our new FMEA system enable us to deploy new features rapidly. The FMEA system is powered by Intel® Xeon® processors, which provide the computational power and performance needed for real-time analysis of large datasets. The system uses high-speed SSDs and advanced memory configurations to ensure rapid data access and processing. Fast Intel® Optane™ persistent memory is employed to enhance caching capabilities and accelerate data retrieval.

This transformative approach promises to dramatically streamline the FMEA process, freeing up engineers’ time to focus on developing innovative solutions to further enhance Intel’s manufacturing tools and processes.

“Why is Intel IT modernizing Windows client management? Because a large part of Intel IT’s job is managing client devices—175,000 end-user and shared PCs for 124,000 employees. We need to consider many factors. Does a PC have the right drivers and security patches? How do we get new hires provisioned quickly? How do we ensure end users have access to the corporate resources they need, while still protecting resources from unauthorized access?

Creating efficient client management processes is crucial to maintaining IT efficiency as well as bolstering a positive user experience (UX). That is why we continue our journey toward modern, cloud-native client management with cloud-first capabilities.

Over the last few years, we have migrated both existing devices and new devices to a modern client stack composed of cloud-based components such as Microsoft Intune, Entra ID, Autopilot, and Windows Update for Business with Delivery Optimization. Together, these components support seamless client provisioning that improves the UX for end users as well as substantially reduces IT effort associated with client management.

Benefits accruing from the move to the cloud are plentiful. A few examples include:

We still have additional plans for continuing our modern client journey. However, we—and our users—are already reaping huge rewards, such as the following:

This white paper shares our client management strategy, our roadmap, and our key learnings. We hope this story encourages other IT departments to pursue the benefits of cloud-based client management and makes their journey a little easier.”

Intel IT’s data center strategy is to apply breakthrough technologies, solutions, and processes to accelerate Intel’s business. We also run Intel data center services like a factory, e?ecting change in a disciplined manner. Our approach enables us to optimally meet Intel’s business requirements while providing our internal customers with e?ective data center infrastructure capabilities and innovative business services.

Building on previous investments and techniques, our data center strategy has generated savings exceeding USD 9.6 billion from 2010 to 2023. We are continually improvising our data center strategy to further our data center transformation. We will accomplish this by using disruptive server, storage, network, infrastructure software, and data center facility technologies. These can lead to unprecedented quality-of-service levels and a reduction in total cost of ownership (TCO) for business applications. And they will enable us to continue to improve IT operational efficiency and be environmentally responsible.

Transformational elements of our data center strategy include the following:

Some of our most notable achievements include:

Our data center transformation strategy is critical for Intel IT to stay competitive. We are committed to providing a foundation for continuous innovation that will improve the quality, velocity, and efficiency of Intel IT’s business services.

Intel Factory Pathfinder delivers advanced simulation/scheduling capabilities for manufacturing.

How efficiently is your factory operating? Are you able to provide accurate delivery dates to customers and consistently meet those dates? Are you maximizing the utilization of your equipment and raw materials to keep your factory running optimally and cost effectively?

If not, Intel Factory Pathfinder was developed just for you. Factory Pathfinder can help you quickly identify and eliminate bottlenecks and constraints in your factory and equipment before they happen.

With the surge in the growth and adoption of Generative AI (GenAI) tools, Intel has seen hundreds of employees and teams begin using and developing tools based on commercial large language models (LLMs).

Recognizing the immense potential of these tools to enhance efficiency and innovation—as well as concerns around AI data security, ethical use, and accuracy of responses—Intel IT formed a working group to understand common usage patterns, coordinate knowledge sharing across teams, and establish guidelines for safe usage.

This proactive approach led to the development of a new platform, aimed at democratizing Intel’s use of GenAI by empowering employees at all levels of technical skill to use these tools to improve their day-to-day productivity and unlock new efficiencies in Intel’s business processes.

Our initiative is designed to facilitate the use of GenAI without the need to repeatedly rebuild common components, thereby reducing security risks and speeding time to value. The rapid deployment of this platform has already demonstrated tangible value. Although the platform is currently in pilot, early users have reported notable increases in productivity. We estimate that approximately 75% of Intel employees will eventually use the GenAI platform.”

Intel is evolving quickly, and Intel IT is a key driver in that evolution. As the architects of Intel’s IT landscape, we are the strategic, trusted technology partner for Intel’s business. Our focus is on innovation, AI, and optimization as well as the IT experience of our workforce, our end users, and Intel’s customers.

The 21st edition of the IT Annual Performance Report highlights the transformative progress we made in 2023 and how IT is providing the essential technology and resources that will spearhead Intel’s transformation and continued growth in 2024.

Please explore the report for more on our accomplishments and plans ahead.

Intel IT migrated enterprise data analytics to the cloud, enabling faster turnaround of business requests and increased operational efficiency.

Digital twins are revolutionizing how we model, simulate, and optimize everything—from product designs to real-world systems and processes across virtually every industry.

For our manufacturing process, we developed Intel Operations Recon to model, simulate, and optimize our manufacturing operations, improve yields accelerate problem resolution and training, increase uptime, and more. And now we’re making Intel Operations Recon available to all kinds of industries that can benefit from it. And the software can be customized to model, simulate,

Intel Operations Recon enables you to see your world in three modes:

Intel Operations Recon benefits also extend beyond efficiency. You can also use it to improve safety and customer satisfaction, reduce costs and risks, contribute to your sustainability initiatives, and more.

In this video, we provide an example of how Intel Operations Recon could be applied to the airline industry.

If are you ready to unlock unprecedented levels of visibility, insights, and efficiency in your operations quickly and easily with Intel Recon, reach out to [email protected] to get started.