Abstract:
This article investigates methods to mitigate hotspots in high-performance chips through layout strategies. It covers floorplanning, power-grid design, and thermal-via placement to balance heat dissipation. Simulation results demonstrate how adaptive placement and thermal-aware routing can improve reliability and prevent thermal-induced performance throttling.

Introduction

As transistor densities and operating frequencies continue to rise, thermal management has become a critical challenge in modern integrated circuits. Localized hotspots can lead to performance degradation, reduced reliability, and even permanent damage. Traditional layout methods often treat thermal considerations as an afterthought, but proactive thermal-aware techniques in floorplanning, power delivery, and routing can significantly mitigate these issues. In this article, we explore three key areas:

1. Thermal-Aware Floorplanning: Placing high-power blocks to distribute heat generation evenly.
2. Power-Grid Design: Designing power meshes to minimize IR drop while reducing thermal hotspots.
3. Thermal-Via Placement: Inserting vias to channel heat vertically into heat sinks or interposer layers.

We conclude with simulation results comparing conventional layouts against thermal-aware designs, illustrating improvements in peak temperature, temperature gradients, and overall thermal uniformity.

1. Thermal-Aware Floorplanning

Floorplanning is the process of arranging functional blocks (e.g., CPU cores, cache arrays, memory controllers, accelerators) on the chip die. A thermal-aware floorplan seeks to distribute power-dense units so that heat sources do not cluster and create concentrated hotspots.

1.1 Power Density Mapping

• Block Power Profiles: Before arranging blocks, extract dynamic and static power estimates for each IP macro under typical workloads.
• Thermal Resistive Network Model: Represent the floorplan as a grid of thermal resistances, where each block’s power maps to a heat source node. Compute approximate steady-state temperatures via a simplified resistive mesh to guide placement.

1.2 Heuristic Placement Strategies

1. Interleaving High- and Low-Power Blocks:
   • Alternate compute-intensive cores with lower-power memory macros or analog blocks.
   • Reduces regions of high thermal concentration and allows adjacent blocks to share heat paths.
2. Permuting Block Orientations:
   • Rotate or flip large blocks (e.g., memory arrays) to increase edge length exposed to lower-power neighbors or to metal-filled regions.
   • Improves lateral heat spreading by exposing more die area adjacent to heat sinks (e.g., I/O rings).
3. Placement of Heat-Sensitive IP:
   • Analog/RF blocks, PLLs, and voltage regulators are particularly sensitive to temperature.
   • Position these modules in cooler “thermal corridors” near chip periphery or under dedicated heat spreaders.

1.3 Floorplan Validation

• Pre-Layout Thermal Simulation:
  • Use fast block-level thermal solvers (e.g., DEFORM, HotSpot) to approximate temperature distribution.
  • Iterate placement based on simulated “hot zones” until maximum die temperature is minimized.
• Inter-Block Spacing:
  • Maintain sufficient distance between multiple high-power blocks (e.g., two CPU cores running at peak) to prevent overlapping thermal footprints.
  • If die area is constrained, introduce dummy filler cells (“thermal buffer zones”)—regions of redistributed power sinks or large metal fills to channel heat.

2. Power-Grid Design

The power mesh not only supplies current to on-chip circuitry but also influences the thermal distribution due to resistive heating (I²R losses). A well-designed power grid can both reduce IR drop and lower localized heat generation.

2.1 Multi-Layer Power Mesh

• Mesh Topology:
  • Use thick metal layers (e.g., Metal-6, Metal-7) for global power distribution to minimize resistance.
  • Implement grid intersections with square or octagonal vias to reduce current crowding.
• Redundant Power Paths:
  • Introduce multiple parallel routes from the supply pads to each power domain.
  • Mitigates hotspot formation in the power metal by ensuring no single segment carries a disproportionate share of current.

2.2 Decoupling Capacitor Placement

• On-Chip Decap Arrays:
  • Place decoupling capacitors near high-switching nodes (e.g., core clock buffers, I/O drivers) to reduce instantaneous current spikes.
  • Smaller current spikes translate to less transient resistive heating, smoothing out thermal fluctuations.
• Hierarchical Decap Distribution:
  • A mix of coarse-grain (large capacitance banks) and fine-grain (distributed smaller caps) decoupling allows localized suppression of IR drop without creating heat clusters.
  • Spread fine-grain decaps uniformly to avoid clustering that could generate local joule heating.

2.3 Copper Fill and Metal Density

• Metal Fill as Heat Spreaders:
  • In areas away from active blocks, insert copper-fill regions (CMP-friendly patterns) to increase metal density.
  • These fills act as lateral heat spreaders, carrying heat toward the package lid or heat sink.
• Thermal Via Integration:
  • Coordinate copper fills with thermal-via locations (see next section) to create continuous vertical heat channels.

3. Thermal-Via Placement

Thermal vias provide low-resistance vertical paths for heat to move from the silicon die into the package substrate, heat spreader, and ultimately to ambient. Strategic placement of thermal vias is crucial for mitigating hot spots.

3.1 Via Array Patterns

• Uniform Via Arrays Under High-Power Blocks:
  • For each power macro (e.g., CPU cluster), place a dense grid of through-silicon vias (TSVs) or buried thermal vias directly beneath the block.
  • Typical spacing: 50 µm – 100 µm pitch for high-power-density regions.
• Ring-Via Structures:
  • Encircle entire high-power islands (e.g., GPU core) with rings of thermal vias to contain and channel heat outward.
  • Inner vias cool the core region, while outer ring serves as a “boundary” to spread residual heat laterally.

3.2 Integration with Package and Interposer

• TSV-Enabled Interposers:
  • In 2.5D designs (silicon interposer), thermal vias can extend from die into interposer copper planes.
  • This effectively expands heat-spreading area across multiple dies, particularly important in multi-die AI accelerators.
• Micro-Bump Arrays and Solder Balls:
  • Align thermal vias with micro-bump locations to minimize thermal resistance through the flip-chip interface.
  • Ensures heat flows efficiently from die to package substrate.

3.3 Thermal Via Design Rules

• Via Diameter and Aspect Ratio:
  • Larger vias reduce thermal resistance but consume more die area.
  • Typical TSV diameter: 10 µm – 50 µm with aspect ratios ≤ 10:1 to balance manufacturability and thermal conductivity.
• Placement Constraints:
  • Avoid placing thermal vias directly under high-density signal routing to prevent interference or reliability issues.
  • Maintain a guard ring of standard signal-metal layers around via clusters to decouple electrical noise.

4. Thermal-Aware Routing

Routing decisions impact metal density, local joule heating, and airflow (in package-level contexts). Thermal-aware routing tools incorporate temperature maps into congestion and cost functions to minimize heat accumulation.

4.1 Temperature-Guided Cost Functions

• Weighted Routing Costs:
  • Assign higher costs for routing through “hot” regions identified in preliminary thermal simulations.
  • Tool optimizes to route critical nets through cooler corridors, even if path length increases slightly.
• Thermal DRC Checks:
  • Check that maximum current density on any wire segment remains below a thermal-design threshold (e.g., 1 MA/cm²) to prevent electromigration and excessive local heating.

4.2 Adaptive Routing Walls and Shields

• Hotspot Avoidance Zones:
  • During routing, define “no-go” or “reduced-preference” areas around identified hotspot locations.
  • Route non-critical nets around these zones to allow heat to dissipate from active blocks unimpeded.
• Shield Insertion in High-Power Regions:
  • Insert shielding wires (connected to ground or a low-impedance net) adjacent to high-current nets to absorb and spread heat.
  • Shields also reduce crosstalk and lower switching noise, indirectly reducing retransmission-induced power spikes.

4.3 Dynamic Routing Adjustment

• Post-PAR (Place-and-Route) Thermal Feedback:
  • After an initial routing pass, run a thermal analysis to identify newly emerging hotspots due to current-induced heat.
  • Trigger a second routing iteration where congestion and cost metrics are updated to reflect thermal gradients.
  • Iterative loop continues until peak temperature delta falls below a defined threshold (e.g., <2 °C per iteration).

5. Simulation Results

To quantify the benefits of thermal-aware layout techniques, we compare two designs of a dual-core high-performance AI accelerator:

• Design A (Baseline): Traditional placement of identical cores adjacent to each other, uniform power mesh, no thermal-via optimization, and standard routing.
• Design B (Thermal-Aware): Cores interleaved with memory macros, multi-layer redundant mesh, dense TSV array under cores, and temperature-guided routing.

5.1 Thermal Modeling Setup

• Power Profiles: Each core dissipates 5 W under maximum load; memory macros dissipate 0.5 W each.
• Package Stack: Flip-chip BGA with a 1 mm thick heat spreader and forced-air convection at 1 m/s.
• Simulation Tool: Finite-element thermal solver (e.g., ANSYS Icepak) with die discretized into 100 µm × 100 µm grid.

5.2 Steady-State Temperature Distribution

Metric	Design A (Baseline)	Design B (Thermal-Aware)	Improvement (%)
Peak Die Temperature	105 °C	90 °C	14.3%
Maximum Temperature Gradient (°C/mm)	45 °C/mm	25 °C/mm	44.4%
Average Die Temperature	85 °C	78 °C	8.2%

• Design A Observations:
  • Two adjacent 5 W cores create a hotspot >100 °C in the center.
  • Surrounding memory macros see temperature rise to ~95 °C, risking accelerated aging.
• Design B Observations:
  • Interleaving cores with memory blocks distributes heat sources.
  • TSV arrays under each core channel heat into the package; peak temperature reduces to ~90 °C.
  • Routing paths avoid central hotspot, allowing better lateral heat spreading.

5.3 Transient Thermal Response

• Workload Profile:
  • Cores idle for 100 ms, then ramp to full load for 500 ms, then return to idle.
  • Repeat for multiple cycles to observe thermal inertia.

Time (ms)	Design A Peak Temp (°C)	Design B Peak Temp (°C)	Temperature Rise Delay (ms)
0	60	58	–
100	62	60	–
200	85	80	–
300	98	88	–
400	105	90	Design B reaches 90 °C at 400 ms instead of Design A reaching 98 °C at 300 ms (delay ≈100 ms)

• Insights:
  • Design B’s thermal-via network and interleaved layout slow the rate of temperature rise by ~100 ms, providing additional headroom for dynamic voltage-frequency scaling (DVFS) to kick in before hitting thermal limits.
  • Lower peak and more uniform temperature reduce thermal cycling stress, improving long-term reliability.

6. Practical Guidelines and Best Practices

Based on the analyses and simulation results, we propose the following guidelines for implementing thermal-aware chip layouts:

1. Early Thermal-Aware Floorplanning:
   • Integrate power density maps into the floorplanning tool.
   • Use iterative thermal simulations alongside placement to identify and correct emerging hotspots.
2. Design a Robust Power Mesh:
   • Favor multi-layer, redundant meshes with thick copper for global power distribution.
   • Distribute decoupling capacitors evenly to smooth current spikes and minimize local joule heating.
3. Strategic Thermal-Via Deployment:
   • Place dense TSV arrays beneath high-power macros.
   • Coordinate via placement with package-level heat spreaders and airflow paths to maximize conduction efficiency.
4. Temperature-Guided Routing:
   • Incorporate thermal maps into routing cost functions to avoid routing critical nets through hottest regions.
   • Implement adaptive routing iterations with feedback from thermal analysis.
5. Leverage Dummy Fills and Metal Density:
   • Insert copper-fill regions in low-activity areas to assist lateral heat spreading.
   • Ensure metal-density rules comply with CMP requirements while aiding thermal conduction.
6. Continuous Validation with Thermal Signoff:
   • Perform full-chip thermal signoff (both steady-state and transient) before tape-out.
   • Utilize 3D package models to capture die-attach and heat-spreader interactions accurately.

Conclusion

Thermal-aware layout techniques are indispensable for modern high-performance chips where power densities can exceed 100 W/cm². By integrating thermal considerations into floorplanning, power-mesh design, thermal-via placement, and routing, designers can significantly reduce peak temperatures, flatten temperature gradients, and delay thermal runaway. Simulation results demonstrate that interleaving high-power blocks with lower-power macros, reinforcing power grids, and channeling heat through vertical vias lead to more uniform and manageable thermal profiles. As technology nodes continue to shrink and power densities rise, adopting these best practices will be crucial for sustaining performance, reliability, and manufacturability in future generations of integrated circuits.

References

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