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. @en

Designers typically add design margins to memories to compensate for their aging. As the aging impact increases with technology scaling, bigger margins become necessary. However, this negatively impacts area, yield, performance, and power consumption. Alternatively, mitigation schemes can be used to reduce the impact of aging. This paper proposes a hardware-based mitigation scheme for the memory's address decoder logic. The scheme is based on adapting the decoder's workload during idle cycles by stressing the short paths and putting long paths into relaxation. Thanks to the adapted workload, the impact of aging on the address decoder is reduced, resulting in a more reliable memory. To validate the benefit of the mitigation scheme, the decoder's degradation of the L1 data and instruction caches for an ARM v8-a processor is analyzed. The experimental results show that the proposed mitigation scheme reduces the degradation of the decoder's timing margin with up to 4.1x at negligible area and no more than 3% power overhead.@en

Integrated circuits typically contain design margins to compensate for aging. As aging impact increases with technology scaling, bigger margins are necessary to achieve the desired reliability. However, these increased margins lead to a reduced performance and lower yield. Alternatively, mitigation schemes can be deployed to reduce the aging. This paper proposes a software-based method to mitigate the aging of the memory's address decoder logic due to Bias Temperature Instability. The method is based on periodically applying a rejuvenation application on top of a user application. The goal of the rejuvenation application is to recover aged transistors of the critical paths of the address decoder. The experimental results show that the proposed method significantly reduces aging in cases when applications consist of memory access patterns that result in an unbalanced stress in the address decoder logic. In particular, it reduces the degradation of the address decoder's setup delay by up to 43% with an execution overhead of only 1%.@en

Designers typically add design margins to compensate for chip aging. However, this leads to yield loss (in case of overestimation) or low reliability (in case of underestimation). This paper analyzes the impact of aging on a complete high-performance industrial 14-nm FinFET SRAM. It investigates the impact on the memory’s parametric (i.e., its delay) and functional (i.e., correct functionality) metrics. Moreover, it examines which components are the main contributors to the degradation of the memory’s reliability and how it is impacted by workload and environmental conditions, i.e., temperature and voltage fluctuations. This paper not only investigates the impact of the memory’s components individually, which is typically the case in prior work, but it also studies the contribution of components’ interaction to the overall memory aging. The results show that the timing circuit, address decoder, and the output latches and buffers are the main contributors to the memory’s parametric degradation, while the cell, sense amplifier, and address decoder are the main contributors to its functional degradation. Moreover, the results show that it is crucial to consider the impact of the interaction of components on the aging; individual analysis leads to overly pessimistic results and even wrong conclusions in certain cases.@en

Designers typically add design margins to compensate for chip aging. However, this leads to yield loss (in case of overestimation) or low reliability (in case of underestimation). This paper analyzes the impact of aging on a complete high-performance industrial 14-nm FinFET SRAM. It investigates the impact on the memory’s parametric (i.e., its delay) and functional (i.e., correct functionality) metrics. Moreover, it examines which components are the main contributors to the degradation of the memory’s reliability and how it is impacted by workload and environmental conditions, i.e., temperature and voltage fluctuations. This paper not only investigates the impact of the memory’s components individually, which is typically the case in prior work, but it also studies the contribution of components’ interaction to the overall memory aging. The results show that the timing circuit, address decoder, and the output latches and buffers are the main contributors to the memory’s parametric degradation, while the cell, sense amplifier, and address decoder are the main contributors to its functional degradation. Moreover, the results show that it is crucial to consider the impact of the interaction of components on the aging; individual analysis leads to overly pessimistic results and even wrong conclusions in certain cases.@en

Designers typically add design margins to compensate for chip aging. However, this leads to yield loss (in case of overestimation) or low reliability (in case of underestimation). This paper analyzes the impact of aging on a complete high-performance industrial 14-nm FinFET SRAM. It investigates the impact on the memory’s parametric (i.e., its delay) and functional (i.e., correct functionality) metrics. Moreover, it examines which components are the main contributors to the degradation of the memory’s reliability and how it is impacted by workload and environmental conditions, i.e., temperature and voltage fluctuations. This paper not only investigates the impact of the memory’s components individually, which is typically the case in prior work, but it also studies the contribution of components’ interaction to the overall memory aging. The results show that the timing circuit, address decoder, and the output latches and buffers are the main contributors to the memory’s parametric degradation, while the cell, sense amplifier, and address decoder are the main contributors to its functional degradation. Moreover, the results show that it is crucial to consider the impact of the interaction of components on the aging; individual analysis leads to overly pessimistic results and even wrong conclusions in certain cases.@en

Designers typically add design margins to compensate for chip aging. However, this leads to yield loss (in case of overestimation) or low reliability (in case of underestimation). This paper analyzes the impact of aging on a complete high-performance industrial 14-nm FinFET SRAM. It investigates the impact on the memory’s parametric (i.e., its delay) and functional (i.e., correct functionality) metrics. Moreover, it examines which components are the main contributors to the degradation of the memory’s reliability and how it is impacted by workload and environmental conditions, i.e., temperature and voltage fluctuations. This paper not only investigates the impact of the memory’s components individually, which is typically the case in prior work, but it also studies the contribution of components’ interaction to the overall memory aging. The results show that the timing circuit, address decoder, and the output latches and buffers are the main contributors to the memory’s parametric degradation, while the cell, sense amplifier, and address decoder are the main contributors to its functional degradation. Moreover, the results show that it is crucial to consider the impact of the interaction of components on the aging; individual analysis leads to overly pessimistic results and even wrong conclusions in certain cases.@en

Designers typically add design margins to compensate for chip aging. However, this leads to yield loss (in case of overestimation) or low reliability (in case of underestimation). This paper analyzes the impact of aging on a complete high-performance industrial 14-nm FinFET SRAM. It investigates the impact on the memory’s parametric (i.e., its delay) and functional (i.e., correct functionality) metrics. Moreover, it examines which components are the main contributors to the degradation of the memory’s reliability and how it is impacted by workload and environmental conditions, i.e., temperature and voltage fluctuations. This paper not only investigates the impact of the memory’s components individually, which is typically the case in prior work, but it also studies the contribution of components’ interaction to the overall memory aging. The results show that the timing circuit, address decoder, and the output latches and buffers are the main contributors to the memory’s parametric degradation, while the cell, sense amplifier, and address decoder are the main contributors to its functional degradation. Moreover, the results show that it is crucial to consider the impact of the interaction of components on the aging; individual analysis leads to overly pessimistic results and even wrong conclusions in certain cases.@en

This paper presents an accurate technique to extensively analyze the impact of time-zero (i.e., global and local variation) and time-dependent (i.e., voltage, temperature, workload, and aging) variation on the offset voltage specification of a memory sense amplifier design using 45 nm predictive technology model (PTM) high performance library. The results show that increasing the supply voltage both for time-zero and time-dependent reduces the offset voltage specification marginally, irrespective of the process corners. In contrast, the offset voltage specification is very sensitive to the temperature and the workload, i.e., the applied voltage patterns. The results also show that a balanced workload results in a significantly lower offset voltage specification. The above results can be used to estimate the required offset voltage accurately for a given lifetime, and operational conditions such as workload, temperature, and voltage; hence, enable the designer to take appropriate measures for a high quality, robust, optimal and reliable design.@en

This paper presents an accurate technique to extensively analyze the impact of time-zero (i.e., global and local variation) and time-dependent (i.e., voltage, temperature, workload, and aging) variation on the offset voltage specification of a memory sense amplifier design using 45 nm predictive technology model (PTM) high performance library. The results show that increasing the supply voltage both for time-zero and time-dependent reduces the offset voltage specification marginally, irrespective of the process corners. In contrast, the offset voltage specification is very sensitive to the temperature and the workload, i.e., the applied voltage patterns. The results also show that a balanced workload results in a significantly lower offset voltage specification. The above results can be used to estimate the required offset voltage accurately for a given lifetime, and operational conditions such as workload, temperature, and voltage; hence, enable the designer to take appropriate measures for a high quality, robust, optimal and reliable design.@en

This paper presents an accurate technique to extensively analyze the impact of time-zero (i.e., global and local variation) and time-dependent (i.e., voltage, temperature, workload, and aging) variation on the offset voltage specification of a memory sense amplifier design using 45 nm predictive technology model (PTM) high performance library. The results show that increasing the supply voltage both for time-zero and time-dependent reduces the offset voltage specification marginally, irrespective of the process corners. In contrast, the offset voltage specification is very sensitive to the temperature and the workload, i.e., the applied voltage patterns. The results also show that a balanced workload results in a significantly lower offset voltage specification. The above results can be used to estimate the required offset voltage accurately for a given lifetime, and operational conditions such as workload, temperature, and voltage; hence, enable the designer to take appropriate measures for a high quality, robust, optimal and reliable design.@en

To compensate for time-zero (due to process variation) and time-dependent (due to e.g. Bias Temperature Instability (BTI)) variability, designers usually add design margins. Due to technology scaling, these variabilities become worse, leading to the need for bigger design margins. Typically, only worst-case scenarios are considered, which will not present the actual workload of the targeted application. Alternatively, mitigation schemes can be used to counteract the variability. This paper presents a run-time design-for-reliability scheme for memory Sense Amplifiers (SAs); SAs are an integral part of any memory system and are very critical for high performance. The proposed scheme mitigates the impact of time-dependent variability due to aging by using an on-line control circuit to create a balanced workload. The simulation results show that the proposed scheme can reduce the most critical figures-of-merit, namely the offset voltage shift and the sensing delay of the SA with up to ~40% and ~10%, respectively, depending on the stress conditions (temperature, voltage, workload).@en

To compensate for time-zero (due to process variation) and time-dependent (due to e.g. Bias Temperature Instability (BTI)) variability, designers usually add design margins. Due to technology scaling, these variabilities become worse, leading to the need for bigger design margins. Typically, only worst-case scenarios are considered, which will not present the actual workload of the targeted application. Alternatively, mitigation schemes can be used to counteract the variability. This paper presents a run-time design-for-reliability scheme for memory Sense Amplifiers (SAs); SAs are an integral part of any memory system and are very critical for high performance. The proposed scheme mitigates the impact of time-dependent variability due to aging by using an on-line control circuit to create a balanced workload. The simulation results show that the proposed scheme can reduce the most critical figures-of-merit, namely the offset voltage shift and the sensing delay of the SA with up to ~40% and ~10%, respectively, depending on the stress conditions (temperature, voltage, workload).@en

To compensate for time-zero (due to process variation) and time-dependent (due to e.g. Bias Temperature Instability (BTI)) variability, designers usually add design margins. Due to technology scaling, these variabilities become worse, leading to the need for bigger design margins. Typically, only worst-case scenarios are considered, which will not present the actual workload of the targeted application. Alternatively, mitigation schemes can be used to counteract the variability. This paper presents a run-time design-for-reliability scheme for memory Sense Amplifiers (SAs); SAs are an integral part of any memory system and are very critical for high performance. The proposed scheme mitigates the impact of time-dependent variability due to aging by using an on-line control circuit to create a balanced workload. The simulation results show that the proposed scheme can reduce the most critical figures-of-merit, namely the offset voltage shift and the sensing delay of the SA with up to ~40% and ~10%, respectively, depending on the stress conditions (temperature, voltage, workload).@en

Nowadays, typical (memory) designers add design margins to compensate for uncertainties, however, this may be overestimated leading to yield loss, or underestimated leading to reduced reliability designs. Accurate quantification of all uncertainties is therefore critical to provide high quality and optimal designs. These uncertainties are caused by zero-time variability (due to process variability), and by run-time variability(due to environmental variabilities such as voltage and temperature, or due to temporal variability such as aging). This paper uses an accurate methodology to predict the impact of both zero-and run-time variability on the offset voltage of sense amplifiers while considering different workloads and PVT variations for a pre-defined failure rate. The results show a marginal impact of environmental run-time variability on the offset specification when considering zero-time variability only, while this becomes significant (up to 2X) when incorporating aging run-time variability. The results can be used to quantify whether the required offset voltage is met or not for the targeted lifetime, hence, enable the designer to take appropriate measures for an efficient and optimized design, depending on the targeted application lifetime.@en

Nowadays, typical (memory) designers add design margins to compensate for uncertainties, however, this may be overestimated leading to yield loss, or underestimated leading to reduced reliability designs. Accurate quantification of all uncertainties is therefore critical to provide high quality and optimal designs. These uncertainties are caused by zero-time variability (due to process variability), and by run-time variability(due to environmental variabilities such as voltage and temperature, or due to temporal variability such as aging). This paper uses an accurate methodology to predict the impact of both zero-and run-time variability on the offset voltage of sense amplifiers while considering different workloads and PVT variations for a pre-defined failure rate. The results show a marginal impact of environmental run-time variability on the offset specification when considering zero-time variability only, while this becomes significant (up to 2X) when incorporating aging run-time variability. The results can be used to quantify whether the required offset voltage is met or not for the targeted lifetime, hence, enable the designer to take appropriate measures for an efficient and optimized design, depending on the targeted application lifetime.@en

Nowadays, typical (memory) designers add design margins to compensate for uncertainties, however, this may be overestimated leading to yield loss, or underestimated leading to reduced reliability designs. Accurate quantification of all uncertainties is therefore critical to provide high quality and optimal designs. These uncertainties are caused by zero-time variability (due to process variability), and by run-time variability(due to environmental variabilities such as voltage and temperature, or due to temporal variability such as aging). This paper uses an accurate methodology to predict the impact of both zero-and run-time variability on the offset voltage of sense amplifiers while considering different workloads and PVT variations for a pre-defined failure rate. The results show a marginal impact of environmental run-time variability on the offset specification when considering zero-time variability only, while this becomes significant (up to 2X) when incorporating aging run-time variability. The results can be used to quantify whether the required offset voltage is met or not for the targeted lifetime, hence, enable the designer to take appropriate measures for an efficient and optimized design, depending on the targeted application lifetime.@en

Nowadays, typical (memory) designers add design margins to compensate for uncertainties, however, this may be overestimated leading to yield loss, or underestimated leading to reduced reliability designs. Accurate quantification of all uncertainties is therefore critical to provide high quality and optimal designs. These uncertainties are caused by zero-time variability (due to process variability), and by run-time variability(due to environmental variabilities such as voltage and temperature, or due to temporal variability such as aging). This paper uses an accurate methodology to predict the impact of both zero-and run-time variability on the offset voltage of sense amplifiers while considering different workloads and PVT variations for a pre-defined failure rate. The results show a marginal impact of environmental run-time variability on the offset specification when considering zero-time variability only, while this becomes significant (up to 2X) when incorporating aging run-time variability. The results can be used to quantify whether the required offset voltage is met or not for the targeted lifetime, hence, enable the designer to take appropriate measures for an efficient and optimized design, depending on the targeted application lifetime.@en

Nowadays, typical (memory) designers add design margins to compensate for uncertainties, however, this may be overestimated leading to yield loss, or underestimated leading to reduced reliability designs. Accurate quantification of all uncertainties is therefore critical to provide high quality and optimal designs. These uncertainties are caused by zero-time variability (due to process variability), and by run-time variability(due to environmental variabilities such as voltage and temperature, or due to temporal variability such as aging). This paper uses an accurate methodology to predict the impact of both zero-and run-time variability on the offset voltage of sense amplifiers while considering different workloads and PVT variations for a pre-defined failure rate. The results show a marginal impact of environmental run-time variability on the offset specification when considering zero-time variability only, while this becomes significant (up to 2X) when incorporating aging run-time variability. The results can be used to quantify whether the required offset voltage is met or not for the targeted lifetime, hence, enable the designer to take appropriate measures for an efficient and optimized design, depending on the targeted application lifetime.@en

Nowadays, typical (memory) designers add design margins to compensate for uncertainties, however, this may be overestimated leading to yield loss, or underestimated leading to reduced reliability designs. Accurate quantification of all uncertainties is therefore critical to provide high quality and optimal designs. These uncertainties are caused by zero-time variability (due to process variability), and by run-time variability(due to environmental variabilities such as voltage and temperature, or due to temporal variability such as aging). This paper uses an accurate methodology to predict the impact of both zero-and run-time variability on the offset voltage of sense amplifiers while considering different workloads and PVT variations for a pre-defined failure rate. The results show a marginal impact of environmental run-time variability on the offset specification when considering zero-time variability only, while this becomes significant (up to 2X) when incorporating aging run-time variability. The results can be used to quantify whether the required offset voltage is met or not for the targeted lifetime, hence, enable the designer to take appropriate measures for an efficient and optimized design, depending on the targeted application lifetime.@en