Reliability Modeling and Mitigation for Embedded Memories

Innocent Agbo

Research output: ThesisDissertation (TU Delft)

289 Downloads (Pure)

Abstract

Complementary Metallic Oxide Semiconductor (CMOS) technology scaling enhances the performance, transistor density, functionality, and reduces cost and power consumption. However, scaling causes significant reliability challenges both from a manufacturing and operational point of view. Obtaining reliable memories require accurate understanding of the impact of aging (such as Bias temperature instability (BTI)) on individual memory components and how they interact with each other. In this dissertation, two types of challenges are addressed, which are related to BTI aging and partially to mitigation schemes: one related to the aging of sense amplifier and another one to the aging of read path and write path. Analysis of aging impact on different memory sense amplifiers - The analysis of BTI impact on various memory sense amplifier (SA) designs was performed, while taking into account two BTI models (i.e., Atomistic and RD model), different technology nodes (i.e., 90, 65, 45, 32, 22, and 16 nm), and different workloads. First, the analysis and comparison of RD and Atomistic models impact on the SA were performed. The results show that the atomistic trap-based BTI model is more accurate than the RD model. Second, the investigation of BTI impact on the drain-input latch type SA for various technology nodes and supply voltages was performed. The result shows that as technology scales down, the impact of BTI on sensing delay increases, while the sensing voltage decreases, causing less robust and reliable memory sense amplifier. The result also shows that increase in supply voltage compensates the BTI degradation. Third, an accurate technique was proposed and characterized for the integral impact of BTI and voltage temperature variation on the memory standard latch type SA for various technology nodes and workloads. The results show that the degradation is strongly dependent on workload and temperature. Fourth, in addition to the latter, the impact of process variation at timezero was incorporated and analyzed. The results show that the SA sensing delay degradation is more significant at lower nodes and could lead to read failures at lower power supply. This reveals that there must be a tradeoff between performance and reliability. Fifth, an accurate methodology was proposed to quantify the impact of variability on the memory SA offset-voltage for both time-zero and time-dependent variability. The results show that the impact on the offset voltage specification is significant for aging time-dependent variability. Sixth, on top of the latter, the sensitivity of the SA and its failure rate were analyzed for five process corners (i.e., Nominal, Fast-Fast, Fast-Slow, Slow-Fast, and Slow-Slow). The results show that balanced workloads result in a significant low offset voltage specification. Finally, the impact of aging was analyzed and compared, while considering different supply voltages, temperatures, and SA designs. The results show that the High Performance SA degrades faster than other SA types, irrespective of the workload, supply voltage, and temperature. Investigation of read path aging - Adequate techniques was proposed to estimate and mitigate the impact of aging on the read path of a high performance SRAMmemory. The mitigation techniques are based on the re-sizing of the pull-down transistors of the cell’s and the SA’s designs. The results show that the SA mitigation is more effective for the SRAM read path (i.e., SA) than cell mitigation. Investigation of write path aging - The analysis of BTI impact on the SRAM write driver was performed for various supply voltages, temperatures, and technology nodes. The result shows that the impact of BTI increases the write delay and widen its distribution, when the technology scales down.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Delft University of Technology
Supervisors/Advisors
  • Hamdioui, S., Supervisor
Award date18 Jun 2018
Electronic ISBNs978-94-6366-053-2
DOIs
Publication statusPublished - 2018

Keywords

  • Memory reliability
  • Aging
  • Bias temperature instability (BTI)
  • sense amplifier (SA)

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