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Electromigration (EM) is still the most important reliability concern for VLSI systems, especially at the nanometer regime. EM immortality check is an important step for full-chip EM signoff analysis. In this paper, we propose a new electromigration (EM) immortality check method for multi-segment interconnect considering the impacts of Joule heating induced temperature gradient. Temperature gradients from metal Joule heating, called thermal migration, can be a significant force for the metal atomic migrations, and these impacts get more significant as technology scales down. Compared to existing methods, the new method can consider the spatial temperature gradient due to Joule heating for multi-segment wires for the first time. We derive the analytic solution for the resulting steady-state EM-thermal migration stress distribution problem. Then we develop the new temperature-aware voltage-based EM immortality check method considering the multi-segment temperature migration effects, which carries all the benefits of the recently proposed voltage-based EM immortality method for multi-segment interconnects. Numerical results on an IBM power grid and self synthesized power delivery networks show that the proposed temperature-aware EM immortality check method is much more accurate than recently proposed state of the art EM immortality method.
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Long-term reliability management for multitasking GPGPUs
This paper proposes long-term reliability management for spatial multitasking GPU architectures. Specifically, we focus on electromigration (EM)-induced long-term failure of the GPU's power delivery network. A distributed power delivery network model at functional unit granularity is developed and used for our EM analysis of GPU architectures. We use a recently proposed physics-based EM reliability model and consider the EM-induced time-to-failure at the GPU system level as a reliability resource. For GPU scheduling, we mainly focus on spatial multitasking, which allows GPU computing resources to be partitioned among multiple applications. We find that the existing reliability-agnostic thread block scheduler for spatial multitasking is effective in achieving high GPU utilization, but poor reliability. We develop and implement a long-term reliability-aware thread block scheduler in GPGPU-Sim, and compare it against existing reliability-agnostic scheduler. We evaluate several use cases of spatial multitasking and find that our proposed scheduler achieves up to 30\% improvement in long-term reliability.
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- Award ID(s):
- 1854276
- PAR ID:
- 10148005
- Date Published:
- Journal Name:
- International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design (SMACD’19)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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