Managing power, heat, and complexity for reliability and performance.
By John Ferguson and Sheltha Nolke
For design teams adopting 3D-IC architectures, the relentless pursuit of performance and reliability brings a familiar, yet increasingly complex, set of challenges: how do we manage power, dissipate heat and navigate the intricate dance of physics within these stacked architectures? While 3D-ICs offer significant advantages in size, performance, power efficiency and cost, they also introduce a new level of complexity. Successfully navigating these challenges, particularly concerning power management, thermal dissipation and the intricate interplay of various physical phenomena, requires a sophisticated approach, leveraging automated multiphysics analysis, enhanced collaboration and a shift-left methodology.
The transition from traditional 2D system-on-chip (SoC) architectures to heterogeneous integration and full 3D stacking has fundamentally altered the design landscape. While 2D design largely relied on well-established process design kits (PDKs) for predictable outcomes, 3D-ICs introduce novel materials, massive data volumes and complex interaction effects. Designers can no longer abstract away mechanical, thermal and power phenomena; these are now central to achieving reliable designs.
Consider the fundamental relationship between power and heat: power consumption directly generates heat. This heat, in turn, can cause wires to distort and alter transistor behavior. These changes cascade through the design, necessitating updated power estimates and fresh timing analyses. Stacking multiple dies, chiplets and components into compact packages further amplifies this complexity. Figure 1 illustrates thermal hotspots in a 3D stack.
Fig. 1: Stress hotspots in a 3D stack involve thermal, electrical and mechanical effects.
The familiar concept of a “known good die” evolves into a “known good stack,” where a single failure can compromise the reliability of the entire system. This “multiphysics” interaction means that various physical phenomena impact both the physical and electrical aspects of a design. Without careful consideration, these effects can lead to catastrophic yield issues or, worse, reliability problems in the field. These include traditional concerns like electromigration (EM), electrical parasitics (PEX), voltage drop (IR) and electrostatic discharge (ESD), now compounded by newer thermal and mechanical interactions.
While these individual issues are generally well understood, traditional SoC design and verification approaches are often inadequate at the 3D-IC level. This is due to the introduction of new materials that behave differently from the traditional silicon, glass and copper combinations found in 2D-ICs. Compounding the problem, these effects cannot be considered in isolation; a change in one impacts the others, creating a complex web of interdependencies.
Beyond the technical intricacies, successful 3D-IC projects hinge on close cooperation across diverse teams—including chip designers, package engineers, foundry partners and outsourced semiconductor assembly and test (OSAT) companies. While protecting critical intellectual property and process data is paramount, establishing a common language and interoperable design flows is equally vital. Tighter integration allows cross-functional teams to identify and address risks early in the design cycle, preventing costly fixes at sign-off. Figure 2 illustrates the web of connections in a 3D-IC design and verification process.
Fig. 2: The interconnected nature of various analyses required for successful 3D-IC design includes thermal, thermo-mechanical stress, power, physical implementation, verification, timing and circuit analysis, all centered around 3D-IC assembly specifications.
Historically, multiphysics analysis often relied on simplified package-level models, frequently treating dies as homogenous units or “bricks.” However, recent research demonstrates that power, thermal and mechanical stress can significantly disrupt expected die-level behavior. This highlights the critical need to involve die designers in discussions about multiphysics criteria from the very outset. The greatest flexibility for making placement and material decisions exists early in the design cycle, underscoring the importance of a shift-left mindset.
Shift-left is an industry-wide philosophy that advocates for pushing analysis and decision-making to the earliest feasible point in the design process. For 3D-ICs, this means conducting “what-if” studies, simulating power and thermal stress and optimizing placement long before late-stage surprises threaten time-to-market. Modern tools like Calibre 3DStress enable multiphysics analysis from the earliest stages of chiplet, package and device definition. This shift-left analysis allows teams to catch issues and refine placement or materials when changes are easy and less costly.
Fig. 3: A shift-left approach runs multiphysics simulations starting at the conceptual phase.
Siemens Digital Industries Software (Siemens EDA) addresses these requirements through integrated flow automation. The Calibre solution combines detailed GDSII-level analysis—extracting wire, oxide and transistor data—with Simcenter Flotherm for thermal simulation. This approach eliminates the need for every designer to be a thermal or mechanical expert. Instead, automated flows deliver push-button results that highlight hotspots, stress regions and timing impacts within familiar layouts and tools. These automated multiphysics workflows are built for scale and efficiency, allowing designers to access deep insight with push-button simplicity within established tool environments and flows, without disrupting current workflows or slowing down design.
These workflows help IC designers understand the impacts across packaging, chiplets and system levels without requiring them to become multiphysics specialists. Early insight provides teams with greater flexibility and confidence in device placement, alignment and material selection, ultimately preventing failure modes or degraded circuit behavior. Furthermore, by combining detailed GDSII-level understanding with Simcenter Flotherm, these workflows account for genuine process temperatures, material stacks and assembly steps, offering results that accurately reflect actual device behavior.
As design challenges multiply, so do the demands on toolchains. Designers must still perform traditional 2D verification—including place-and-route, timing checks, design rule checking (DRC) and layout-vs-schematic (LVS)—in addition to new analyses for the assembled package.
The first generation of Calibre 3D tools focused on sign-off verification and mapping of multilayer, multi-process chiplets from different foundries. Layer mapping, interface detection and understanding physical connections are critical for avoiding errors in three-dimensional space. Expanded standards, such as IEEE’s 3Dblox initiative, now enable even more robust and integrated flows, supporting DRC, LVS, PERC analysis, thermal simulation and stress checks. The overarching goal is clear: provide visibility across every layer and component, facilitating the smooth propagation of simulation results from the die level to the substrate and board.
Comprehensive models now capture not just global effects like warpage and thermal hotspots, but also device-level influences, such as stress regions that might shift transistor performance or impact timing closure. This means that modeling extends beyond just physical deformations to directly impact device-level timing. Moreover, expanded standards and integrated flows allow results to propagate from die-level analysis all the way to package and board simulation, delivering consistent data and context to every stakeholder and significantly aiding team collaboration. This iterative process is crucial because all that heat, EM, IR and mechanical distortion will impact the parasitics and even the electrical behavior of individual transistors. The electrical integrity initially identified is no longer correct, necessitating continuous iteration between all interacting physical phenomena to achieve accurate accounting of the final electrical behavior.
Looking ahead, sign-off criteria for 3D-ICs will increasingly rely on multi-domain expertise—mechanical, thermal, power and timing—all codified within accessible, automated flows. The comprehensive digital twin concept allows teams to propagate die-level simulation results throughout the design, supporting rigorous multiphysics validation and enhancing reliability.
To address the steep learning curves associated with these advanced technologies, Siemens EDA is investing in AI and agentic additions to its platforms. These innovations aim to help users ramp up quickly. Machine learning methods are being explored for smarter analysis, faster cycles and improved usability, allowing designers to focus on innovation rather than grappling with complexity. Figure 4 illustrates the Siemens EDA 3D-IC multiphysics workflow.
Fig. 4: Siemens EDA holistic 3D-IC multiphysics workflow showing design, verification, manufacturing and multiphysics engines.
Emerging approaches to 3D-IC design include photonics for efficient signal delivery, glass and ceramic materials for improved thermal buffering and even chip-level liquid cooling. Each new development underscores the industry’s relentless pursuit of higher performance and greater efficiency, with automated, integrated flows serving as the essential backbone for future design success. This continuous iterative process, starting from early floor planning (or “multi-level planning” as it might be better termed for 3D-ICs), ensures that even with less initial data, designers can make informed decisions. As the design matures and more precise material properties and power maps become available, further adjustments can be made, such as inserting copper pillars to reduce thermal impacts or modifying dummy fill to improve mechanical stress. This proactive, iterative approach is key to achieving high-yield, reliable 3D-IC designs with optimal electrical behavior.
Shetha Nolke is a senior product engineer at Siemens Digital Industries Software.
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