Intel

IT Best Practices: Improving big data platform efficiency is an ongoing effort for Intel IT. In initial testing, Granulate reduced both memory and CPU utilization in our production environment in our production environment via a light-weight agent, with no code changes or developer resources.

As Intel manufactures hundreds of millions of complex products every year,

Intel IT collects and stores terabytes of manufacturing data to support continual engineering data analysis. As the volume, velocity and complexity of the data increases, it is imperative that we maintain this decision support system at the lowest possible cost. Additionally, we need to be able to assess the cost for future scaling needs. Therefore, we decided to evaluate the scalability, performance and cost of several Intel architecture-based massively parallel processing (MPP) relational database management systems (RDBMS). We found that industry- standard benchmarks did not closely resemble our manufacturing data and did not measure the metrics that were important to us. Therefore, we created a custom MPP RDBMS benchmark that helped us choose a cost-optimized solution.

We used this custom benchmark to complete a comprehensive technical proof of concept (PoC) with several industry-leading MPP RDBMS vendors whose products run on Intel architecture. We are confident that this benchmark enabled us to choose the best Intel Xeon processor-based MPP RDBMS solution while keeping manufacturing data management costs under control. Also, based on the evaluation results, the vendors we worked with have improved their products, strengthening the entire industry ecosystem. And, with the release of the 4th Gen Intel Xeon Scalable processors and associated accelerators, we’re expecting that RDBMS vendors will make their products even more cost competitive. By sharing our benchmark methodology, we hope to help other companies to understand their data better and select a data management system that meets their needs.

Intel IT runs Intel data center services like a factory, affecting change in a disciplined manner and applying breakthrough technologies, solutions, and processes. This enables us to optimally meet Intel’s business requirements while providing our internal customers with effective data center infrastructure capabilities and innovative business services. Building on previous investments and techniques, our data center strategy has generated savings exceeding USD 7.5 billion from 2010 to 2022.

We are constantly enhancing our data center strategy to continue our data center transformation. Using disruptive server, storage, network, infrastructure software and data center facility technologies can lead to unprecedented quality-of-service (QoS) levels and reduction in total cost of ownership (TCO) for business applications. They also enable us to continue to improve IT operational efficiency and be environmentally responsible.

Transformer models are the powerful neural networks that have become the standard for delivering advanced performance behind these innovations. But there is a challenge: Training these deep learning models at scale and doing inference on them requires a large amount of computing power. This can make the process time-consuming, complex, and costly.

Today we will talk about all kinds of issues around accessible, production level AI solutions. We also talk about ethical questions around AI usage and why open, democratized AI solutions are important.

Learn more:

Hugging Face Hub

Fast Inference on Large Language Models: BLOOMZ on Habana Gaudi2 Accelerator

Accelerating Stable Diffusion Inference on Intel CPUs

Transformer Performance with Intel & Hugging Face Webinar

Intel Explainable AI Tools

Intel Distribution of OpenVINO Toolkit

Intel AI Analytics Toolkit (AI Kit)

Guests:

The SafeHouse Initiative was organized to provide education and awareness to businesses who are inundated with technical concepts, jargon and terms around the concepts of Business Continuity and Cyber Security. We understand that customers want to focus on their business rather than becoming Cyber Security or Disaster Recovery/Business Continuity technology experts.

Follow Jake on Twitter at: twitter.com/jakesmithintel

The SafeHouse Initiative was organized to provide education and awareness to businesses who are inundated with technical concepts, jargon and terms around the concepts of Business Continuity and Cyber Security. We understand that customers want to focus on their business rather than becoming Cyber Security or Disaster Recovery/Business Continuity technology experts.

Follow Jake on Twitter at: twitter.com/jakesmithintel

The SafeHouse Initiative was organized to provide education and awareness to businesses who are inundated with technical concepts, jargon and terms around the concepts of Business Continuity and Cyber Security. We understand that customers want to focus on their business rather than becoming Cyber Security or Disaster Recovery/Business Continuity technology experts.

Follow Jake on Twitter at:

As the world moves towards more specialized hardware like GPUs, Google TPUs, Habana Gaudi (HPU), FPGAs, etc, enabling developers to run their code on the most efficient hardware can be challenging. Intel oneAPI and xPUs are at the vanguard of this shift and Digital Cortex is leading the way forward with its comprehensive set of products built on these emerging technologies. By providing unprecedented access to compute across varying architectures and platforms, Digital Cortex is helping developers unlock new levels of performance while simplifying development processes.

We talk to Digital Cortex CEO Charlie Wardell to learn how Digital Cortex is building on top of the oneAPI vision to bring a marketplace of compute kernels to their platform that can run anywhere. Charlie also shares his thoughts on entrepreneurship and what made him make the leap from working in a company to founding a company.

Learn more:

oneAPI

Intel oneAPI toolkits

Guest:

IT Best Practices: Empowering clients with the tools for self-service from the initial acquisition of hardware, through the lifecycle of their devices, and full circle through device refresh helps IT maintain budgets and forecast future client device needs. Leveraging telemetry is key to improving interactive employee experiences by equipping IT with insights that provide better service, device, and product configurations, resulting in overall improved employee satisfaction.

Intel IT is committed to maximizing client productivity and giving employees access to support without picking up a phone or visiting a service desk. To help achieve this they monitor all managed devices in the Intel IT ecosystem and define this as Client Health. The driving questions behind Client Health are how to quantify captured client data, how to analyze the data, and what to do with that data to deliver excellence in IT support. The answers to these questions help deliver a stable, responsive platform with the right hardware aligned to an employee’s needs.

Over the last couple of decades, the world of computer graphics has been growing at an amazing rate.  From animated movies to video games, consumers have reaped the benefits of these technological advances.  One of the latest algorithmic advances in rendering is path guiding.  Learn about path guiding and how you can take advantage of this cool technology using Chaos V-Ray and the Intel Path Guiding Library (OpenPGL)

Learn more:

Intel Open Path Guiding Library (OpenPGL) Github

Paper: Importance driven path tracing using the photon map.

Paper: Practical Path Guiding for Efficient Light-Transport Simulation (a.k.a. Practical Path Guiding)

Paper: Path Guiding in Production

See also:

Guests: