Learn extra at:
Ahead-looking: As AI workloads reshape computing, AMD is exploring a devoted neural processing unit to enrich or exchange GPUs in AI PCs. This transfer displays rising business momentum towards specialised accelerators that promise sooner efficiency and better vitality effectivity – key elements as PC makers race to ship smarter, leaner machines.
AMD is exploring whether or not PCs may benefit from a brand new type of accelerator: a discrete neural processing unit. The corporate has lengthy relied on GPUs for demanding workloads, however the rise of AI-specific {hardware} opens the door to one thing extra environment friendly and specialised.
Rahul Tikoo, head of AMD’s shopper CPU enterprise, instructed CRN that the chipmaker is in early talks with prospects about what such a chip would possibly appear to be and the place it might match.
“We’re speaking to prospects about use circumstances and potential alternatives for a devoted accelerator chip that’s not a GPU however could possibly be a neural processing unit,” Tikoo stated throughout a briefing earlier than AMD’s Advancing AI occasion final month.
The concept arrives as PC makers like Lenovo, Dell Applied sciences, and HP search methods to dump AI processing from conventional CPUs and GPUs. Dell has already taken that step with its new Professional Max Plus laptop computer, which contains a Qualcomm AI 100 inference card – touted as the primary enterprise-grade discrete NPU for PCs.
Tikoo declined to disclose when AMD would possibly launch such a chip, stressing future plans stay underneath an NDA. Nonetheless, he steered the corporate has the items in place to maneuver rapidly if it decides to proceed, making the leap to a discrete NPU believable.
AMD’s efforts to embed AI capabilities into Ryzen processors might present the muse. The corporate has used AI engine expertise from its Xilinx acquisition as the premise for NPU blocks in its newest chips – a transfer that would scale into stand-alone merchandise.
Christopher Cyr, CTO of Sterling Computer systems, stated the expertise roadmap is already clear.
“If this specific NPU tile creates 50 TOPS [trillion operations per second], tack on two of them, make it 100 TOPS,” Cyr stated.
He emphasised that any discrete NPU from AMD should ship significant efficiency positive factors with out consuming the type of energy or producing the warmth typical of a stand-alone GPU. Effectivity is essential for PC makers striving to take care of skinny designs and lengthy battery life whereas including AI functionality. With out these vitality financial savings, a discrete NPU dangers turning into simply one other cumbersome, heat-producing part relatively than a real different to immediately’s GPU-driven options.
Additionally learn: Opinion: The rapidly evolving world of AI PCs
Cyr cited AMD’s Gaia open-source undertaking, designed to run massive language fashions domestically on Ryzen-based Home windows PCs, as proof that the corporate is laying the groundwork for a broader AI push.
“They’re making actually good inroads in direction of leveraging that complete ecosystem,” he famous.
Whereas GPUs have been the default accelerator for years – and Nvidia want to keep it that way – NPUs are reshaping the panorama. Intel, AMD, and Qualcomm have built-in NPUs into their newest processors. Nonetheless, there may be rising momentum for discrete variations that ship increased efficiency with out the warmth and energy draw of GPUs.
Among the first makes an attempt got here from Intel, which equipped a 2023 Floor Laptop computer with a Movidius VPU earlier than its Core Extremely chips had onboard NPUs. Dell’s newest workstation takes issues additional with a Qualcomm card pushing 450 TOPS in a 75-watt envelope. Startups like Encharge AI are coming into the fray too, promising NPU add-ons with GPU-level compute capability at a fraction of the associated fee and energy consumption.
AMD’s discrete NPU would broaden its product lineup past CPUs, GPUs, and built-in accelerators. This addition would supply OEMs a brand new choice to combine AI capabilities into PCs, doubtlessly offering a leaner and extra energy-efficient different to immediately’s GPU-heavy setups.