Spin-transfer torque magnetic random access memory (STT-MRAM) is a promising alternative to existing memory technologies. However, STT-MRAM faces reliability challenges, primarily due to stochastic switching, process variation, and manufacturing defects. These reliability challenges become even worse due to interconnect parasitic resistive-capacitive effects, potentially compromising the reliability of memory cells located far from the write driver. This can severely impair the manu-facturing yield and large-scale industrial adoption. Toaddressthis, we propose an interconnect-aware error correction coding (InterA-ECC), which provides non-uniform error correction to a different zone of the memory subarray. The proposed InterA-ECC strategy selectively applies robust error-correction code (ECC) to specific rows within the subarray rather than uniformly across all rows, reducing ECC parity bits while enhancing bit error rate resiliency in the most vulnerable memory zone.

Spin-transfer torque magnetic random access memory (STT-MRAM) has emerged as a promising alternative to conventional CMOS memory technologies for on-chip cache replacement. Due to its superior access speeds, high endurance, and scalability, it is being extensively considered a promising candidate for last-level cache replacement. This technology has reached considerable industrial maturity, with several foundries now offering this emerging technology. Despite its advantages, STT-MRAM faces reliability challenges, primarily due to its asymmetric error characteristics during write and read operations, where the likelihood of a bit transitioning from$1\rightarrow 0$differs from that of$0\rightarrow 1$. Conventional Error Correcting Codes (ECCs) do not account for such asymmetry between these bit-flip types and fall short of providing balanced error correction. This article introduces an efficient asymmetric and adaptive error correction in STT-MRAM based on the Hamming weight of data bits that operates with negligible overhead alongside a standard ECC framework. Our simulation findings indicate that the proposed technique offers substantial enhancement in reliability, measured by a cache word/block error rate, tested across the last level cache data for various SPEC CPU2017 benchmarks. This enhancement in reliability is achieved without inserting excessive memory and hardware overhead, and without impacting system performance, presenting a compelling case for enhancing the operational reliability of STT-MRAM.

Spin-transfer torque magnetic random access memory (STT-MRAM) is a promising alternative to existing CMOS memory technologies due to its non-volatility, fast read access, and scalability potential. This has reached the level of industrial maturity as several foundries now offer this technology. However, it is sensitive to various failure mechanisms, such as manufacturing defects in both CMOS and magnetic layers, temperature variation, repetitive writes, and oxide breakdown, which can cause early cell failure leading to hard errors. This can severely impair the manufacturing yield and its large-scale industrial adoption. To ensure high manufacturing yield and infield reliability, we propose a new block error correction pointer (BECP) as a hard error correction technique for STT-MRAM. The proposed method divides large word lengths into smaller sub-blocks and assigns a specific base value per sub-block to determine the offset location of the hard error. This allows storing only the offset value instead of the absolute address of the hard error for each sub-block. The results depict that the proposed method is storage efficient and has low decoding complexity compared to the existing state-of-the-art methods. We incorporate experimental measurement data obtained from manufactured STT-MRAM chips at different die locations to get the hard error distribution. The proposed method aligns well with our specific STT-MRAM error distribution measurements.

Guaranteeing high-quality test solutions for Spin-Transfer Torque Magnetic RAM (STT-MRAM) is a must to speed up its high-volume production. A high test quality requires maximizing the fault coverage. Detecting permanent faults is relatively simple compared to intermittent faults; the latter are faults (caused by non-environmental conditions) that appear and disappear as a function of time, and are therefore hard to detect. Testing for such faults in STT-MRAMs is even worse considering the Magnetic Tunneling Junction inherent property ‘intrinsic switching stochasticity’, which results in inevitable random write errors. This paper presents a novel Design-for-Testability (DFT) scheme for detecting intermittent faults in STT-MRAMs; it is based on monitoring the write current. The strength of the write current is inversely correlated to the write error rate; when the write current is smaller than the specification, the device is considered faulty. A reduction in the write current can be caused by any defect in the write path of the memory (e.g., interconnects and contacts). Simulation results based on industrial design show that applying DFT yields a superior coverage of intermittent faults compared to functional test methods, such as march tests.

The Spin-Transfer Torque Magnetic Random Access Memory (STT-MRAM) is on its way to commercialization. However, the development of high-quality test solutions for STT-MRAMs poses challenges due to the specific working mechanism of the core element of the STT-MRAM bit cells, i.e., the magnetic tunnel junction (MTJ), which involves both a magnetic field and spin-transfer torque. This property can introduce defects unique to MTJs which may escape from test programs that consist solely of functional write and read operations, like march tests. Hence, it is important to develop test solutions that go beyond conventional march tests. This paper explores the effect of applying an external magnetic field (Hext) on the test quality and test time of STT-MRAMs, which could be achieved by integrating one or more magnets in the Automated Test Equipment (ATE) setup. A framework for these so-called Hext-assisted tests is presented and implemented for all known conventional and unique defects. The paper demonstrates that the Hext-assisted tests offer superior coverage and/or lower test time compared to regular functional tests, like march tests. The effectiveness of these tests are validated through silicon measurements.

Spin-Transfer Torque Magnetic RAMs (STT-MRAMs) are on their way to commercialization. However, obtaining high-quality test and diagnosis solutions for STT-MRAMs is challenging due to the existence of unique defects in Magnetic Tunneling Junctions (MTJs). Recently, the Device-Aware Test (DA-Test) method has been put forward as an effective approach mainly for detecting unique defecting STT-MRAMs. In this study, we propose a further advancement based on the DA-Test framework, introducing the Device-Aware Diagnosis (DA-Diagnosis) method. This method comprises two steps: a) defining distinctive features of each unique defect by characterization and physical analysis of defective MTJs, and b) utilizing march algorithms to extract distinctive features. The effectiveness of the proposed approach is validated in an industrial setting with real devices and data measurement.

STT-MRAM has long been a promising non-volatile memory solution for the embedded application space owing to its attractive characteristics such as non-volatility, low leakage, high endurance, and scalability. However, the operating requirements for high-performance computing (HPC) and low power (LP) applications involve different challenges. This paper addresses different aspects of STT-MRAM; it will cover state-of-the-art, some new results and future challenges related to technology, design and test. While STT-MRAM devices have shown encouraging performance metrics at device-level, a key challenge has been achieving backend-of-line (BEOL) CMOS compatibility, while retaining the benefits of low power operation. Scaling demands to improve data densities have placed additional challenges in terms of addressing the impact of process-induced damage on device performance at CD < 100 nm. In addition, the paper discusses the design of reliable read mechanism considering the variability effects. Moreover, the failure of traditional fault modeling and test approaches in model STT-MRAM unique defects for appropriate test solutions is demonstrated in this paper based on silicon data.

Understanding defects in magnetic tunnel junctions (MTJs) and their faulty behaviors are paramount for developing high-quality test solutions for STT-MRAM. This article applies the advanced device-aware test to intermediate (IM) state defects in MTJ devices based on silicon measurements and circuit simulations. An IM state manifests itself as an abnormal third resistive state, which differs from the two bi-stable states of MTJ. We performed silicon measurements on MTJ devices with diameter ranging from 60 nm to 120 nm; the results show that the occurrence probability of IM state strongly depends on the switching direction, device size, and bias voltage. We demonstrate that the conventional resistor-based fault modeling and test approach fails to appropriately model and test such a defect. Therefore, device-aware test is applied. We first physically model the defect and incorporate it into a Verilog-A MTJ compact model and calibrate it with silicon data. Thereafter, this model is used for a systematic fault analysis based on circuit simulations to obtain accurate and realistic faults in a pre-defined fault space. Our simulation results show that an IM state defect leads to intermittent write transition faults. Finally, we propose and implement a device-aware test solution to detect the IM state defect.

The popularity of perpendicular magnetic tunnel junction (pMTJ)-based spin-transfer torque magnetic random access memories (STT-MRAMs) is growing very fast. The performance of such memories is very sensitive to magnetic fields, including both internal and external ones. This article presents a magnetic-field-aware compact model of pMTJ, named the MFA-magnetic tunnel junction (MTJ) model, for magnetic/electrical co-simulation of MTJ/CMOS circuits. Magnetic measurement data of MTJ devices, with diameters ranging from 35 to 175 nm, are used to calibrate an in-house magnetic coupling model. This model is subsequently integrated into our developed compact pMTJ model, which is implemented in Verilog-A. The superiority of the proposed MFA-MTJ model for device/circuit co-design of STT-MRAM is demonstrated by simulating a single pMTJ as well as STT-MRAM full circuits. The design space is explored under PVT variations and various configurations of magnetic fields.

Understanding the defects in magnetic tunnel junctions (MTJs) and their faulty behaviors are paramount for developing high-quality tests for STT-MRAM. This paper characterizes and models intermediate (IM) state defects in MTJs; IM state manifests itself as an abnormal third resistive state, apart from the two bi-stable states of MTJ. We performed silicon measurements on MTJ devices with diameter ranging from 60 nm to 120 nm; the results reveal that the occurrence probability of IM state strongly depends on the switching direction, device size, and applied bias voltage. To test such defect, appropriate fault models are needed. Therefore, we use the advanced device-aware modeling approach, where we first physically model the defect and incorporate it into a Verilog-A MTJ compact model and calibrate it with silicon data. Thereafter, we use a systematic fault analysis to accurately validate a theoretically predefined fault space and derive realistic fault models. Our simulation results show that the IM state defect causes intermittent write transition faults. This paper also demonstrates that the conventional resistor-based fault modeling and test approach fails in appropriately modeling IM defects, and hence incapable of detecting such defects.

STT-MRAM is one of the most promising emerging non-volatile memory technologies. As its mass production and deployment in industry is around the corner, high-quality yet cost-efficient manufacturing test solutions are crucial to ensure the required quality of products being shipped to end customers. This paper focuses on STT-MRAM testing, covering three abstraction levels: manufacturing defects, fault models, and test solutions. We first survey STT-MRAM manufacturing defect space and apply the conventional resistor-based test approach to develop test solutions. We then demonstrate with silicon measurements that this approach fails to appropriately model and test defects in STT-MRAM devices: magnetic tunnel junctions (MTJs), although it is qualified for interconnect/contact defects. Therefore, we propose a new test approach: device-aware test (DAT) to specifically target device-internal defects. We apply DAT to three key types of MTJ defects: pinhole, synthetic anti-ferromagnet flip, and intermediate state defects. After developing accurate defect models and calibrating them with silicon data, we perform comprehensive fault analyses based on SPICE circuit simulations to derive accurate and realistic fault models. Some STT-MRAM unique faults are identified, including both permanent faults and intermittent faults. Based on the obtained fault models, high-quality test solutions are proposed. Additionally, this paper also proposes a magnetic coupling model and a magnetic-field-aware compact MTJ model for fast and robust STT-MRAM designs.

As a unique mechanism for MRAMs, magnetic coupling needs to be accounted for when designing memory arrays. This paper models both intra- and inter-cell magnetic coupling analytically for STT-MRAMs and investigates their impact on the write performance and retention of MTJ devices, which are the data-storing elements of STT-MRAMs. We present magnetic measurement data of MTJ devices with diameters ranging from 35 nm to 175 nm, which we use to calibrate our intra-cell magnetic coupling model. Subsequently, we extrapolate this model to study inter-cell magnetic coupling in memory arrays. We propose the inter-cell magnetic coupling factor Ψ to indicate coupling strength. Our simulation results show that Ψ≈2% maximizes the array density under the constraint that the magnetic coupling has negligible impact on the device's performance. Higher array densities show significant variations in average switching time, especially at low switching voltages, caused by inter-cell magnetic coupling, and dependent on the data pattern in the cell's neighborhood. We also observe a marginal degradation of the data retention time under the influence of inter-cell magnetic coupling.

Understanding the manufacturing defects in magnetic tunnel junctions (MTJs), which are the data-storing elements in STT-MRAMs, and their resultant faulty behaviors are crucial for developing high-quality test solutions. This paper introduces a new type of MTJ defect: synthetic anti-ferromagnet flip (SAFF) defect, wherein the magnetization in both the hard layer and reference layer of MTJ devices undergoes an unintended flip to the opposite direction. Both magnetic and electrical measurement data of SAFF defect in fabricated MTJ devices is presented; it shows that such a defect reverses the polarity of stray field at the free layer of MTJ, while it has no electrical impact on the single isolated device. The paper also demonstrates that using the conventional fault modeling and test approach fails to appropriately model and test such a defect. Therefore device-aware fault modeling and test approach is used. It first physically models the defect and incorporate it into a Verilog-A MTJ compact model, which is afterwards calibrated with silicon data. The model is thereafter used for fault analysis and modeling within an STT-MRAM array; simulation results show that a SAFF defect may lead to an intermittent Passive Neighborhood Pattern Sensitive Fault (PNPSF1i) when all neighboring cells are in logic `1' state. Finally, test solutions for such fault are discussed.

The STT-MRAM manufacturing process involves not only traditional CMOS process steps, but also the integration of magnetic tunnel junction (MTJ) devices, the data-storing elements. This paper demonstrates a paradigm shift in fault modeling for STT-MRAMs by performing defect modeling and fault analysis for MTJ pinhole defects which are seen as a key type of STT-MRAM manufacturing defects. A Verilog-A compact model for defect-free MTJ devices is built and calibrated with electrical measurements on actual MTJ wafers. MTJs with a pinhole defect are extensively characterized, both during manufacturing test (t=0) and in the field (t>0), and the data is used to extend our defect-free MTJ compact model to include parameterized pinhole defects. The model is then used to perform single-cell static fault analysis and this shows not only what kind of faults can occur in an STT-MRAM, but also that the conventional fault modeling approach based on linear resistors cannot catch such behavior.

This paper proposes a new test approach that goes beyond cell-aware test, i.e., device-aware test. The approach consists of three steps: defect modeling, fault modeling, and test/DfT development. The defect modeling does not assume that a defect in a device (or a cell) can be modeled electrically as a linear resistor (as the traditional approach suggests), but it rather incorporates the impact of the physical defect on the technology parameters of the device and thereafter on its electrical parameters. Once the defective electrical model is defined, a systematic fault analysis (based on fault simulation) is performed to derive appropriate fault models and subsequently test solutions. The approach is demonstrated using two memory technologies: resistive random access memory (RRAM) and spin-transfer torque magnetic random access memory (STT-MRAM). The results show that the proposed approach is able to sensitize faults for defects that are not detected with the traditional approach, meaning that the latter cannot lead to high-quality test solutions as required for a defective part per billion (DPPB) level. The new approach clearly sets up a turning point in testing for at least the considered two emerging memory technologies.

Spin-transfer-torque magnetic RAM (STT-MRAM) is one of the most promising emerging memory technologies. As various manufacturing vendors make significant efforts to push it to the market, appropriate STT-MRAM testing is of great importance. In this paper, we demonstrate that conventional STT-MRAM defect modeling, which is based on linear resistors, is too pessimistic in representing the real nature of physical defects. It may result in incorrect fault models, which in turn can lead to low-quality test solutions. In addition, we propose a generic defect modeling methodology which captures the nonlinear behavior of STT-MRAM defects accurately; a defect is modeled by adjusting the affected STT-MRAM technology parameters. The methodology is illustrated by two examples, namely a pinhole defect and a sidewall redeposition defect, which are simulated for accurate fault modeling. In case of a pinhole defect, the STT-MRAM suffers from a fast transition between magnetic tunnel junction (MTJ) states with increased write current, making the MTJ more vulnerable to breakdown. However, with the conventional linear resistor as defect model the memory shows a slow transition or even a transition failure. Similarly, a sidewall redeposition defect causes a fast transition without current elevation, which is not observed when using the conventional approach.

STT-MRAM (Spin Transfer Torque Magnetic Random Access Memory) has attracted considerable attention of late since it is the most promising logic compatible nonvolatile memory that is suitable for advanced logic nodes (N28 and beyond) in terms of endurance, speed and power. Embedded STT-MRAM has thus been proposed as a candidate for emerging low standby-power connectivity systems such IoT (Internet-of-Things) and wearables. We utilize the high performance CoFeB based perpendicular MTJ (pMTJ) device to realize a low power and highly dense STT-MRAM array for such systems. This study is carried out on the TSMC 28nm technology node and includes a complete cross-layer design and analysis framework ranging from device modeling to circuit design, layout and system implementation. The process variations and temperature (PT) impact on the MTJ for the STT-MRAM design (and correspondingly the total energy consumption and performance of the system) is also analyzed. We report a ∼85% reduction in the energy consumption compared to the baseline SRAM based system for near negligible performance penalty (<5%).