Intel Looks to Muscle Its Way to AI Dominance
Back in the day, Intel used its size, engineering muscle, and sizeable financial resources to run roughshod over smaller competitors and seize dominant shares of the client and server processor markets.
However, a few years of missed deadlines and questionable strategic decisions, shifts in computing, and increased competition from a resurgent AMD, Nvidia, and an array of AI-focused startups took the sheen off Intel’s armor, making the one-time giant look vulnerable.
Returning to the company in early 2021 as CEO, Pat Gelsinger promised to put Intel back on the right track, creating an ambitious product roadmap, ramping its manufacturing capabilities, and putting a greater emphasis on developers with a software-first approach, personified by his hiring of Greg Lavender, the former VMware executive who took over as senior vice president, CTO, and general manager of the company’s Software and Advanced Technology Group.
The chip-making giant — along with much of the rest of the IT industry — soon turned much of its efforts to AI and machine learning field, a fast-growing space that only accelerated with the rapid adoption of generative AI and large-language models after the release in late last year of OpenAI’s ChatGPT chatbot.
All that was on display at Intel’s two-day Innovation 2023 developer conference in San Jose, California, last week, with Gelsinger, Lavender, and other executives positioning the company as the only player with the silicon and open ecosystem chops to address the needs of AI developers.
“This developer community is the catalyst for driving the transformation and deep technical innovations that we’re doing to create fundamental change across industries with Intel hardware and software,” Lavender said in his day-two keynote. “There’s no other field seeing such deep, rapid innovation than the field of artificial intelligence right now, especially around generative AI and large-language models.”
He added that “the key to leveling the playing field across all AI developers is a strategy that is built on open systems and open ecosystems.”
Central to much of this is Intel’s Developer Cloud, which was first introduced at last year’s show and is now generally available. Through the Developer Cloud, AI programmers will get access to an array of Intel’s chips and applications, including early access to upcoming technologies.
Infrastructure Lays the AI Groundwork
In his own keynote the day before, Gelsinger gave a detailed rundown about those systems and the Intel chips that will power many of them and will form the computing foundation for AI developers.
“AI is representing a generational shift in how computing is used and giving rise to the ‘Siliconomy,’” the CEO said. “But inside of that, a simple rule: developers rule. You run the global economy. … [AI development] requires a range of different capabilities, next-generation CPUs, NPUs [neural processing units], GPUs, chiplets, new interconnects, and specialized accelerators, and our commitment to you is to give you the coolest hardware and software ASAP. And we will do that.”
He said this promise of four processor nodes in five years is still on track, proving that Intel can once again deliver quality products on time. It’s an achievement that can’t be taken lightly, according to Patrick Moorhead, chief analyst at Moor Insights and Strategies, writing on X (nee Twitter), “This is the most important metric I track on the degree of Intel’s future success.”
“Design and software [are] vital, of course, but without five nodes in four years … the company never be successful,” Moorhead continued “It’s the first question I ask Pat Gelsinger about, every time we meet. Why do I say that? Without IFS [Intel Foundry Services], Intel won’t be cost or tech-competitive through investment scale, and a successful IFS needs five in four.”
For its Xeon data center chips, Gelsinger said the “Emerald Rapids” processor — a follow-on to the current fourth generation “Sapphire Rapids” processors — will be released Dec. 14, but it was the fifth generation Xeons that generated buzz. It will be the first generation to feature the vendor’s P-core (performance) and E-core (efficient) layouts to address different workloads.
“Granite Rapids” will be the P-core chip, coming out next year and offering as much as three times the performance for AI workloads over Sapphire Rapids. A little earlier in 2024, Intel will roll out “Sierra Forest,” the E-core chip that the company said would come with 144 cores. However, Gelsinger said Intel was able to create a version of the processor with another 144-core chiplet, bringing the total number of cores to 288.
“Clearwater Forest,” another E-core Xeon, will arrive in 2025.
The Coming AI PCs
Intel also will use its upcoming Core Ultra “Meteor Lake” client chips for PCs that will be able to run AI inferencing workloads on the device. The Core Ultra, which will launch December 14, is a chiplet design with a CPU and GPU and that also will include an integrated NPU power-efficient AI accelerator.
Developers and users will be able to work with AI workloads locally, ensuring greater data security and privacy, a growing concern with ChatGPT and similar tools.
The CEO also spoke about the 2023.1 release of its OpenVINO toolkit distribution for AI inferencing for developers on client and edge platforms. It includes pre-trained models that can integrate with generative AI models like Meta’s Llama 2. There also is Project Strata, which will result in an edge-native software platform that will launch next year to enable infrastructure to scale for the intelligent edge and hybrid AI.
Lavender stressed the need for open ecosystems to ensure widespread adoption of AI and said Intel’s open strategy will draw developers away from competitors like Nvidia. He noted that 4,000 of Intel’s Gaudi 2 GPUs and its fifth-generation Xeons will be used in an upcoming massive AI supercomputer from Stability AI.
OpenAPI Leads the Way
He also noted the rapid adoption of Intel’s OneAPI open programming model, seeing an 85% uptake since 2021. In addition, OneAPI — which touches CPUs, GPUs, FPGAs, and accelerators — will be the basis of the Linux Foundation’s Unified Acceleration (UXL) Foundation to create an open standard for accelerator programming. The group’s founders include Intel, Arm, Fujitsu, Google Cloud, and Qualcomm.
Intel is contributing its OneAPI specification to the UXL Foundation.
In addition, the chip maker is working with Red Hat, Canonical, and SUSE to develop Intel-optimized enterprise software distributions optimized for Intel technologies, while CodePlay, a software company Intel bought last year, is rolling out multiplatform plug-ins in OneAPI for GPUs from Nvidia, AMD, and Intel. Using the OneAPI plug-in for Nvidia will enable developers to run the Khronos Groups SYCL programming models on the vendor’s GPUs, Lavender said.
“This is a major milestone for the OneAPI ecosystem and the developer community, creating a viable migration path from [Nvidia’s] CUDA and other proprietary programming models to SYCL and OneAPI, enabling AI programming everywhere,” he said.
“The CUDA ecosystem is being disrupted due to the generative AI revolution and the importance of higher-level programming extractions using frameworks such as OpenAI’s Triton, Google’s Jax, Modular AI’s Mojo, and Julia for scientific computing. More is coming. The rapid rate of innovation of AI technologies is creating new disruptions to the status quo, freeing the developer from proprietary lock-in. This is important to the future of everyone and getting AI adopted everywhere.”