MediaTek Rack-Level Optimization: Data Center XPUs, ASICs & AI Computing

DATA CENTER • AI COMPUTE • ASIC • HYPERSCALE

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MediaTek's Rack-Level Optimization: From Data Center XPUs to ASIC AI workloads are scaling faster than conventional chip architectures can keep up with. As such, training large models, serving inference at high concurrency, and moving data across thousands of compute nodes simultaneously puts pressure on every layer of data center infrastructure management.

The question for hyperscale operators is no longer just which chip to buy, but which partner can build, package, and interconnect a complete compute system around their specific workload. Addressing these scale constraints requires purpose-built hardware.

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DATA CENTER • AI COMPUTE • ASIC • HYPERSCALE

This is where MediaTek comes in, delivering custom ASICs and end-to-end design expertise engineered to maximize performance per watt at every tier of the compute stack. Here is a closer look at how custom ASICs and purpose-built silicon are reshaping data center design from the ground up.

How XPUs are Changing ASICs for Data Centers A CPU handles general-purpose tasks, while a GPU remains focused on graphics before being repurposed for parallel compute. An XPU, by contrast, is purpose-built from the ground up for AI. This is specifically for the tensor operations, matrix math, and sparse computations that dominate model training and inference at scale.

MediaTek designs custom XPUs that are co-optimized with advanced packaging, high-bandwidth memory, and interconnect as a single unified system. As such, data center and hyperscaler customers can either have MediaTek architect their compute requirements entirely, or bring their own AI accelerators, logic IP, and microarchitectures to be integrated into a coherent end-to-end solution.

This flexibility is what separates a genuine ASIC data center partner from a chip vendor.

Process Technology as a Competitive Lever Performance per watt is the defining metric in any hyperscale data center today. With fixed power and grid limits, tiny chip inefficiencies compound massively at rack scale.

MediaTek is at the cutting edge of process technology, with 10-plus tape-outs on N3, 2-plus on N2, and its first A14 test chip set to tape out later this year. The company leads with mobile, leveraging high volume and scale to optimize yield and process-technology co-optimization, then rapidly applies those learnings to large-scale data center designs.

This approach has a measurable consequence: MediaTek reaches advanced nodes for data centers faster than most competitors can. Through Design-Technology Co-Optimization (DTCO), MediaTek works directly with leading fabs at state-of-the-art process nodes to customize and optimize transistors, extracting every last bit of performance the silicon can deliver.

For operators running a hyperscale data center, that efficiency difference translates directly into cost per token.

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DATA CENTER • AI COMPUTE • ASIC • HYPERSCALE

System-Level Packaging Requirements: Hyperscale Data Centers

The physical limits of a single die mean that advanced packaging is now a core part of any serious data center ASIC design. The 2.5D packaging places compute tiles and HBM side-by-side on silicon interposers (<10,000 sq. mm), delivering high performance in a single package.

MediaTek's 3.5D integration introduces vertical die-to-die stacking and more complex integration, minimizing the distances between logic, memory, and I/O, reducing the cost of data movement, with specifications spanning 10,000 to 20,000 sq.mm SI.

Both approaches bring CPUs, XPUs, high-bandwidth memory, high-speed I/O chiplets, and power and thermal structures together with nanometer-level precision. For a data center ASIC operating at scale, shorter internal distances mean lower latency, lower power consumption, and better signal integrity across the entire compute system.

NVLink Fusion and the Full-Stack Partnership When it comes to hyperscale data center deployments, MediaTek operates in the NVIDIA NVLink Fusion ecosystem.

MediaTek • Rack-Level Optimization • 3

DATA CENTER • AI COMPUTE • ASIC • HYPERSCALE

By connecting custom XPUs into NVIDIA's ecosystem via NVLink C2C, MediaTek's architecture extends from the ASIC Compute Tray and NVSwitch Tray at the rack level. This scales out further through InfiniBand and Ethernet, delivering a full-stack data center solution from end to end.

This is a rack-level solution, co-optimized across silicon, packaging, interconnect, and system architecture.

Conclusion Building an ASIC data center accelerator is not just a chip-design problem. It requires a partner that controls the full stack - from process node and DTCO through die design, advanced packaging, memory hierarchy, interconnect, and rack-level co-optimization.

At the same time, this semiconductor company has the expertise to bring all these elements together into a single, cohesive architecture. MediaTek's data center solutions are built for hyperscale performance, with custom XPUs, advanced packaging, and full-stack interconnects designed as one unified AI compute system.

For hyperscalers whose data center infrastructure management depends on getting more performance per watt out of every rack, that end-to-end capability is what makes the difference.

FAQs 1. What is an ASIC data center accelerator?

An Application-Specific Integrated Circuit or ASIC data center accelerator is a customdesigned microchip built exclusively to execute specific compute tasks more efficiently than general-purpose CPUs or GPUs.

2. How does MediaTek approach rack-level optimization?

MediaTek co-designs compute, memory, interconnect, and power delivery, treating the rack as the primary compute unit.

3. What interconnect technologies does MediaTek support for hyperscale data centers?

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DATA CENTER • AI COMPUTE • ASIC • HYPERSCALE

MediaTek connects die-to-die links, SerDes, PCIe, co-packaged optics, and Active Optical Cables for scalable data-center connectivity.

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