As AI moves from a specialized workload into mainstream infrastructure, backend test is undergoing a quiet but decisive shift. The questions customers ask of test are changing, and so is the role test plays in the broader manufacturing flow.
For decades, the industry operated with a simple guiding question: do we have a “Known Good Die (KGD)” defined?
From wafer sort through final test, automated test equipment (ATE) has answered that question effectively, serving as the backbone of silicon validation and ensuring structural integrity, parametric compliance, and functional correctness. But AI systems are exposing the limits of that model.
The Limits of “Known Good Die”
Modern compute devices, like GPUs, AI accelerators, and heterogeneous HPC modules, are no longer operating in controlled environments. They are deployed into systems running sustained, high-power workloads, often at the edge of thermal and electrical limits.
Passing ATE no longer guarantees success in the field. That shift introduces a more relevant question: will the device perform reliably, in the system it was designed for, under real-world conditions at scale?
Figure 1: Comparison of ATE vs SLT. Source: Teradyne.
Why System-Level Test Matters Now
System-Level Test (SLT) complements ATE, not replaces it. Where ATE provides precision and speed, SLT provides context. It introduces real workloads, system interaction, and environmental stress, exposing failure modes that are otherwise invisible at the chip or package level, including:
- Power delivery instability
- Thermal-induced degradation
- Interconnect weaknesses across HBM, TSVs, and advanced packaging
- Firmware and software integration issues
- Early-life (infant mortality) failures
These are no longer corner cases. In AI infrastructure, they are increasingly first-order failure mechanisms.
Figure 2: Where each SLT-exposed failure mode shows up in the stack. Source: Teradyne.
Packaging Complexity Forces a System View
The industry’s move toward advanced packaging, like 2.5D, 3D, and HBM-based architectures, has fundamentally altered device behavior. These devices are more thermally dense, more interconnect-heavy, more sensitive to process variation, and more dependent on system-level integration. ATE, by design, abstracts away much of this complexity. SLT forces it back into view.
SLT as a Complement, Not a Replacement
The evolution toward SLT reflects a broader shift in how Known Good Die is defined. Silicon correctness remains necessary, but it is no longer sufficient. In the AI era, reliability must be validated at the system level, under realistic operating conditions. SLT provides that missing layer of validation, bridging the gap between passing test and surviving deployment.
This is exactly where Teradyne’s Titan HP platform delivers value. Titan HP is purpose-built for system-level test, giving manufacturers a practical way to validate AI accelerators and HPC devices under the same sustained power, thermal, and workload stress they’ll face in the field, before those devices ever reach a customer’s data center.
Figure 3: The cost of a missed defect rises sharply the later it is caught. Source: Teradyne.
That matters because the cost of a miss is no longer a failed test; it’s downtime, warranty exposure, and eroded trust once a device is deployed at scale. By surfacing power delivery instability, thermal-driven degradation, and interconnect weaknesses early, Titan HP helps manufacturers move from hoping a device will hold up to knowing it will. For an industry racing to scale AI infrastructure without sacrificing reliability, that confidence is what separates a chip that passes test from a system that performs when it counts.
Figure 4: Titan HP SLT System. Source: Teradyne.
Test as a Continuous Feedback Mechanism
System-level test is no longer a niche step reserved for selected products. As AI infrastructure scales, SLT is becoming a foundational element of the backend test strategy.
The question is no longer just whether a device passes test, but whether it performs reliably over time, in the systems that matter most. SLT is how the industry is beginning to answer that question.
Melvin Lee is the Director of Factory Applications for System Level Test at Teradyne, where he is responsible for growing the team’s engagements with many of the industry’s leading semiconductor companies. Melvin brings over 25 years of experience in the semiconductor industry, with a strong track record of building and leading global applications and yield engineering organizations. Most recently, he served as Director of Worldwide Field Applications at Onto Innovation, where he led global teams across the U.S. and Asia; prior to that, Melvin held multiple leadership roles at GlobalFoundries. Melvin holds a Bachelor of Engineering in Mechanical Engineering, Second Class Honours, from Curtin University of Technology.