Why Next-Gen AI Architectures Demand Purpose-Built Power Test Systems
Artificial intelligence is most often framed as a story of compute advancements. Faster GPUs, denser accelerators, and advanced process nodes. But behind every AI workload, the most fundamental constraint is power.
(Figure 1: AI Server Market, Source: Grand View Research)
As AI servers scale to meet datacenter demand, power delivery is becoming one of the most critical and complex engineering challenges, with persistent implications for semiconductor test. It’s no longer true that power delivery and measurement are peripheral steps in the test flow. Today they are explicit requirements driven by extreme current levels, fast transients, evolving voltage architectures, and tight efficiency margins.
AI accelerators operate at extremely low voltages while demanding unprecedented current levels. It’s a combination that fundamentally changes how devices behave under load and how they must be measured, stressed, and verified during test. Power-focused test systems are emerging as strategically important infrastructure for fast, scalable validation with parameters such as current handling, efficiency, and transient response now written directly into test requirements. This reflects the reality that power behavior has become a first-order determinant of yield, reliability, and system-level performance.
Inside the AI server stack
Modern AI servers rely on multi‑stage power conversion architectures to efficiently deliver energy from the grid to high‑power accelerators such as GPUs. Power is stepped down through multiple high‑voltage AC‑DC and DC‑DC conversion stages, optimised for efficiency, power density, and reliability. As AI workloads continue to scale, these architectures are evolving toward higher distribution voltages and fewer conversion stages to reduce losses, simplify power delivery networks, and support ever‑increasing rack‑level power demands.
Each stage introduces different classes of power devices, including silicon, silicon carbide, and gallium nitride, each of which has its own unique electrical and thermal characteristics. The final stage (closest to the GPU) is where power density peaks and test requirements become most demanding.
What makes AI power devices different to test
These devices operate in systems that challenge conventional test assumptions. This includes devices such as DrMOS, smart power stages, and increasingly integrated power modules. Near the point of load, smart power stages integrate gate drivers and power devices to minimize parasitic and improve efficiency. A single high-performance GPU could use an order of magnitude more DrMOS than a typical CPU.
As package complexity increases, so does the need for more deliberate test strategies. In the transition from monolithic dies to chiplets, long-established test methods are not always directly transferable because test IP is now distributed across multiple dies and, in some cases, across different design teams or companies. This fragmentation requires a clearer definition of what must be tested at each stage—die, bridge, interposer, substrate, and stack—and which standards or techniques apply to each scope.
For engineers, this convergence of constraints creates a perfect storm. Ultra-low RDS(on) values must be measured accurately while forcing tens of amps of current without overheating the device. At these levels, millivolt-scale measurement errors translate into meaningful power loss and thermal impact. The margin for error is minuscule, and thermal effects can easily distort results if measurements are too slow. At the same time, throughput must be maintained, keeping costs in check. Additional factors like noise, ground shift, and parasitic effects (which become increasingly pronounced at high current levels) can further complicate measurement accuracy. Dense device packaging, multiple parallel contacts, and shared ground paths amplify the challenge, making the test environment itself a potential source of error.
Why RDS(on) test is getting harder
As current increases, RDS(on) measurement becomes more sensitive to temperature. Longer test pulses or slower rise times allow the device to self-heat, skewing results and reducing repeatability. To manage these effects during test, short, high-current pulses are required —long enough to capture meaningful electrical behavior, yet short enough to avoid the self-heating that can distort results.
These factors put new demands on test instrumentation: the ability to source and sustain high current for precise, short durations; wide analog bandwidth to support fast transients; and tight timing control to ensure repeatable results across sites and systems. Without these capabilities, manufacturers risk trading measurement accuracy for throughput or vice versa.
From discrete devices to integrated modules
Power suppliers are also moving toward larger, more integrated power modules that combine many phases into a single package. These devices simplify system design but complicate test flows. For example, many manufacturers now test RDS(on) and related parameters at the smart power stage or device level, again after integration into higher-level modules, and sometimes under extended stress or burn-in conditions to meet rigorous AI qualification requirements.
This multi-insertion test structure considers the cost of failure. Scrapping a fully integrated power module is far more expensive than screening early, even if early test adds complexity.
Implications for test architecture and methodology
These complex, device-level requirements have real consequences for how test systems are architected. For example, high-channel density alone is insufficient if instruments cannot maintain fast transient response and stable regulation under load and across all active channels simultaneously. In high-current scenarios, many traditional platforms reduce effective channel count or pulse duration, thus decreasing throughput and increasing the cost of test. As current levels and site counts increase, serialization and intelligent power multiplexing are becoming essential. Rather than scaling test hardware linearly with power demand, advanced test methodologies rely on fast, deterministic switching to share high-performance resources across multiple sites without sacrificing accuracy. Critically, test methodologies must capture real power behavior while minimizing thermal and electrical artifacts introduced by the test system itself. Elements like pulse width, slew rate, grounding strategy, and measurement timing must be designed into the platform rather than managed ad hoc.
Power-focused test systems as a competitive category
These pressures are reshaping the test landscape. For AI and cloud infrastructure, test operators require systems purpose-built for power semiconductor validation, as opposed to adaptations of general-purpose digital or mixed-signal platforms. In these environments, power delivery and measurement are first-class capabilities, not auxiliary features.
Test systems must support a wider operating envelope: higher voltages upstream, higher currents downstream, and tighter accuracy requirements everywhere in between. This shift is giving rise to a distinct category of power-centric test platforms that complement traditional SoC and digital test systems. These platforms are designed to handle high current, fast transients, and precision measurement as core functions.
How power-focused test systems address AI power challenges
Purpose-built power test systems tackle challenges specific to AI by combining high current delivery, wide regulation bandwidth, and precision measurement within a tightly integrated architecture. In Teradyne’s ETS-800 platform, for example, power instruments such as the SPU-8112 Power VI are designed specifically to support short, high-current pulses with fast transient response.
(Figure 2: SPU-8112, Source: Teradyne)
The SPU-8112 provides true multi-channel density while sustaining high current levels across all channels, enabling parallel test without derating commonly seen in conventional instruments. High regulation bandwidth and fast slew rates allow test pulses to settle quickly, minimizing self-heating during RDS(on) measurement. Characterization is more accurate while throughput improves.
To manage the cost of test at scale, solid-state power multiplexing can be implemented through components such as the SPMB power MUX. This intelligent serialization means high-current resources can be ganged and shared across sites with minimal switching overhead. Measurement integrity is well-maintained, and test systems avoid unnecessary duplication of hardware.
For very high current applications, including large or highly integrated power modules, Teradyne also supports validation using platforms such as UltraFLEXplus, capable of addressing test scenarios involving hundreds or even thousands of amps. This flexibility allows test strategies to evolve alongside device architectures, rather than forcing a one-size-fits-all approach.
Power is now a test requirement, not just a design constraint
As power behavior becomes a determinant of yield, reliability, and system stability, power test requirements are moving earlier and deeper into the test flow. Validation is not confined to final test or system bring-up, but spans wafer-level, package-level, and module-level test stages.
Looking ahead, higher rack density and evolving voltage architectures will continue to raise the bar for power device validation.
(Figure 3:HPC/ AI data centers 800V Opportunity, Source: Teradyne)
AI data centers are already moving toward higher-voltage DC distribution, including emerging 800V DC architectures. While this is poised to improve system-level efficiency, it will also introduce new validation challenges across multiple conversion stages, from high-voltage front-end devices to dense point-of-load power stages near the processor.
AI’s growth depends on more than advanced compute silicon. It depends on reliable, efficient power delivery and on the ability to validate that power at production scale. Accurate high-current measurement, thermal-aware test strategies, and scalable throughput are no longer niche requirements. They are foundational to enabling the next generation of AI infrastructure.
Aik-Moh Ng is a Product Manager for Analog Power Test Products at Teradyne. With over 20 years of experience in the automated test equipment industry, he has been integral in developing marketing strategies, and ensuring clear value propositions and product positioning. Prior to his role as a Product Manager, Aik-Moh held various roles including Field Product Specialist and Senior Engineer. Aik-Moh holds a Bachelor of Science degree in electrical and electronic engineering from the University of Manchester.