From ARIES to MARS

In the rapidly evolving landscape of modern electronics, memory devices and circuits play a pivotal role in determining system performance, energy efficiency, and scalability. Traditional memory technologies, such as Dynamic Random Access Memory (DRAM) and NAND flash, face challenges related to scaling limits, latency, power consumption, and endurance, particularly as demands for faster and more efficient data storage grow. Emerging non-volatile memory (NVM) technologies like Resistive Random Access Memory (ReRAM), Phase-Change Memory (PCM), and Spin-Transfer Torque Magnetic Random Access Memory (STT-MRAM) offer potential solutions to these challenges, but their combination into existing systems poses design and manufacturing hurdles. The primary problem lies in balancing storage performance with power efficiency while ensuring scalability for advanced applications such as artificial intelligence (AI), Internet of Things (IoT), and high-performance computing (HPC). Innovations in circuit design, including advanced error-correction mechanisms, adaptive voltage scaling, and low-power architectures, are critical in enhancing the overall performance of memory systems. This study employs a hybrid approach, combining novel circuit design techniques with the combination of emerging NVM technologies. Simulations were performed to evaluate the performance metrics, including write latency, energy consumption, and endurance. Results show that ReRAM-based memory designs achieved a 35% reduction in write latency and a 50% improvement in energy efficiency compared to traditional DRAM, while PCM demonstrated superior endurance with up to 10^8 write cycles. Furthermore, STT-MRAM circuits showed promise with a 40% reduction in standby power consumption. These advancements in memory circuits and devices highlight the potential for significant improvements in storage performance and efficiency, addressing the growing needs of modern electronic systems and paving the way for future innovations in computing.

Spin-Torque Transfer Magnetic RAM (STT-RAM), one of the emerging nonvolatile memory (NVM) technologies explored as the replacement for SRAM memory architectures, is particularly promising due to the fast access speed, high integration density, and zero standby power consumption. Recently, hybrid deigns with SRAM and STT-RAM buffers for routers in Network-on-Chip (NoC) systems have been widely implemented to maximize the mutually complementary characteristics of different memory technologies, and leverage the efficiency of intra-router latency and system power consumption. With the realization of Processing-in-Memory enabled by STT-RAM, in this paper, we novelly offload the execution from processors to the STT-RAM based on-chip routers to improve the application performance. On top of the hybrid buffer design in routers, we further present system-level approaches, including an ILP model and polynomial-time heuristic algorithms, to fine-tune the application mapping and scheduling on NoCs, with the objectives of improving system performance-energy efficiency. Network overhead caused by flit conflict in conventional communication circumstances can be ideally avoided by computing the contended flits in intermediate routers; meanwhile, the pressure of heavy workload on processors can be relieved by transferring partial operations to routers, such that network latency and system power consumption can be significantly reduced. Experimental results demonstrate that application schedule length and system energy consumption can be reduced by 35.62, 32.87 percent on average, respectively, in extensive evaluation experiments on PARSEC benchmark applications. In particular, the achievements of application performance and energy efficiency, averagely 36.44 and 33.19 percent, for the CNN application AlexNet have verified the practicability and effectiveness of our presented approaches.

Energy optimization for multi-level cell non-volatile memory using state remapping

Using nonvolatile memories in memory hierarchy has been investigated to reduce its energy consumption because nonvolatile memories consume zero leakage power in memory cells. One of the difficulties is, however, that the endurance of most nonvolatile memory technologies is much shorter than the conventional SRAM and DRAM technology. This has limited its usage to only the low levels of a memory hierarchy, e.g., disks, that is far from the CPU.

Spin transfer torque magnetic random access memory (STT-MRAM) is one of the most promising new non-volatile memory technologies. Recently, STT-MRAM has become popular as a DRAM alternative in main memories particularly for tablets and palmtop computers in part due to its non-volatile properties and potential for improved device scalability. However, STT-MRAM is well known for its asymmetric access properties and considerable attention has been applied to the device, circuit, and architecture designs to mitigate its write energy concerns. In this work, we propose a new method to reduce the write energy consumption using a combination of pulse width scaling and error correction coding schemes for STT-MRAM main memories. The introduced methodology works by dynamically adjusting the pulse width based on the compressibility of the written data. We evaluate the efficiency of the proposed method on Android applications. Experimental results show an average improvement of more than 10% in the write energy consumption, in addition to the 46% reduction achieved by compression.

New non-volatile memory (NVM) technologies, e.g., Phase Change Memory (PCM), are emerging with main features such as byte addressability, cheapness and large size, and will be deployed to serve as main memory. For fast processing of big data, block device drivers have been developed for NVM such that traditional file systems (e.g., EXT4) operated on non-volatile main memory. However, the existing block driver blindly caches pages, which incurs unnecessary access delays. To overcome this drawback, this paper develops a novel block device driver, called NVMBD, for byte-addressable non-volatile main memory. It adopts two methods of processing block I/O requests, i.e., traditional block I/O and BMAP. On the one hand, traditional block I/O reads/writes 512B sectors with multiple load/store instructions. On the other hand, BMAP inserts NVM pages into the page cache tree when processing block I/O requests, which removes the page movement between the page cache and the NVM. BMAP involves in the management of page cache, but it is transparent to file systems. BMAP provides file systems with the DAX-like feature, improving the file system performance. Through comprehensive experiments, we demonstrate that the developed block device driver significantly improves the file access performance.

Spin Transfer Torque Magnetic Random Access Memory (STT-MRAM) is an emerging non-volatile memory technology, as a leading candidate to replace conventional on-chip memories due to its various advantages such as high density, non-volatility, scalability, high endurance and CMOS compatibility. However, read and write operations in STT-MRAM are extremely vulnerable to manufacturing variations. In particular, the read operation is becoming more susceptible to failures since the read timing and read-disturb failures have conflicting requirements of read period. To overcome this issue, we propose a technique to reduce the read period without sacrificing the target reliability requirements. The reduced read period, in turn, results in improved read performance and reduced read-disturb rates. The results show that using this technique, the read period can be reduced by 50%, and the read-disturb probability by 51%.

We analyze the augmentation of spin-transfer torque (STT) MRAM with electrically driven selective phase transition of a threshold switch (TS) to enhance the read operation. This paper provides a comprehensive discussion on necessary design considerations for TS augmented (TSA) MRAMs. We deduce constraints for read and write biasing that yields improved read operation of TSA MRAMs. We explain the dependence of read/write performance metrics on read/write biases and the properties (resistance and critical currents for transitions) of the TS. With proper device-circuit optimization, TSA MRAM shows up to 70% larger sense margin, ~27% higher data stability with ~40% less power for read operation compared to STT MRAM (in nominal condition). We evaluate the impact of variation on TSA MRAM through Monte Carlo simulations. We report that even with variation induced spread in the distribution of bit-line voltages, TSA MRAM provides $\sim 1.7\times $ larger voltage differential between parallel and antiparallel states. For the write operation, the TSA MRAM consumes ~10% less average power and demands only ~5% more write time extension than the STT MRAM to achieve the same level of variation tolerance.

Dynamic Random Access Memory (DRAM) has been prevalent over the past few decades as main memory component. The demand of higher memory capacity is increasing continuously, while scaling of DRAM is reaching its boundaries. As we scale DRAM to smaller feature size, difficulties in fabrication, leakage power, and energy consumption become significant. Therefore, memory technologies, which have better scalability feature, will be the future of memory systems. To overcome these limitations, search for a new memory technology is necessary and Phase Change Memory (PCM) is the most promising. PCM is non-volatile memory with better scalability and less leakage power than DRAM. It is a resistance-based memory, which doesn't need to be refreshed. PCM suffers more write latency and less write endurance. The write latency of PCM is higher than its read latency by almost 8 times. A large number of researches have been done on reducing write latency of PCM. This research will focus on studying different approaches and techniques in order to reduce write latency on various aspects. Then, techniques employed to reduce write latency of PCM such as PreSET, Partial-SET, Flip-N-Write, two-stage-write, and two-stage-write-inv are introduced. Conclusively, a performance comparison of each technique is discussed.

Recently, numerous efforts have been made on NVM-based Field Programmable Gate Arrays (FPGAs) because the emerging non-volatile memory (NVM) technologies have the advantages of lower leakage power and higher density than Static Random Access Memory (SRAM) technology. However, the cost and the scale of FPGAs are so high and large that they can’t be applied in the consumer electronics field and Internet of Things (IoT). Due to the small scale and low cost, Programmable Logic Array (PLA) is an ideal option for these fields. However, up to now there are few researches on non-volatile PLA based on emerging NVMs. In this paper, a power-efficient non-volatile PLA based on Phase Change Memory (PCM) is proposed. The proposed non-volatile PLA architecture has been evaluated using the 40 nm Complementary Metal Oxide Semiconductor (CMOS) technology, and the simulation results show the correct functionality of the PLA. After the PLA reads the configuration bits from the non-volatile programmable elements (PEs), the power of the programmable elements can be OFF. Therefore, the standby power of the programmable elements is much smaller than that of the commonly SRAM-based PLAs. The simulation results also show that the total power of nvPLA is reduced by about 53.6% when the supply power of Programmable Element is OFF.

Spin Transfer Torque Magnetic RAM (STT-MRAM) is one of the most promising on-chip technologies, which delivers high density, non-volatility, and near-zero leakage power. However, Spin Transfer Torque Magnetic RAM (STT-MRAM) suffers from three reliability issues, namely, read disturbance, write failure, and retention failure, that present significant challenges to its use as a reliable on-chip memory. All of these three reliability challenges become even more threatening with any increase in STT-MRAM cell temperature. Write operations are regarded as the main source of heat generation and temperature increase in STT-MRAM on-chip memories. This article first presents experiments to show how the heat generated by consecutive writes affects the reliability of an STT-MRAM on-chip cache. Then, it proposes the WiSE framework, an approach to reduce the STT-MRAM-based cache memory temperature and improve its reliability. WiSE utilizes the Reinforcement Learning (Reinforcement Learning (RL)) technique to detect high-density write operation patterns in STT-MRAM cache. To manage the write operations across the STT-MRAM caches, WiSE introduces a new temperature-aware replacement policy. The simulation results show that while WiSE imposes only about 1% performance overhead, it improves retention failure rate, read disturbance rate and write failure rate by 64%, 57%, and 47%, respectively, compared to Least Recently Used (Least Recently Used (LRU)) replacement policy.

The explosive growth in the market of smart mobile phones and other portable electronic devices has attracted the interest of the semiconductor industry in non-volatile memory (NVM) technologies. Phase change memory (PCM), which utilizes the large optical and electrical property contrast between crystalline and amorphous phases of phase change materials to store information, has been considered as a promising candidate for the future NVM device [1]. Recently, Min Zhu et al [2] found that the PCM cell which based on TiSbTe(TST) alloy shows much faster Set operation speed and lower Reset power, compared with Ge2Sb2Te5 with the same size. In the present work, the surface morphology, phase and simulated images of the TST film were obtained using AFM technique. The in-situ annealed TEM morphology analyses were used in combination with the electron-diffraction Radial distribution function (RDF) to investigate the structural evolution from amorphous to the polycrystalline phases [3]. The structural evolution characteristics of the TST films were studied as a function of the annealing temperature. Furthermore, the atomic arrangement and defects of the polycrystalline state were revealed through an advanced Cs-corrected scanning transmission electron microscope (STEM) attached with an energy dispersive X-ray (EDX) spectroscope. In conclusion, our results are valuable for understanding the fast, reversible phase-change process of TST materials and also for designing new memory devices. [1] Wuttig, M. & Yamada, N., Nature Mater. 6 (2007)824–832. [2] M. Zhu et al, Nat. Commun. 5 (2014), 4086. [3] L. Zhang et al, Journal of Alloys and Compounds. 537 (2012) 71–75. B21-P-08 doi:10.1093/jmicro/dfv252

Spin-transfer torque magnetic random access memory (STT-RAM) technology has emerged as a potential replacement of SRAM in cache design, especially for building large-scale and energy-efficient last level caches. Compared with single-level cell (SLC), multi-level cell (MLC) STT-RAM is expected to double cache capacity and increase system performance. However, the two-step read/write access schemes incur considerable energy consumption and performance degradation. In this paper, we propose two techniques using data compression to optimize MLC STT-RAM cache design. The first technique tries to compress a cache line and fit it into only the soft-bit region of the cells, so that reading or writing this cache line takes only one step which is fast and energy-efficient. We introduce a second technique to increase the cache capacity by enabling the left hard-bit region to store another compressed cache line, which can improve the system performance for memory intensive workloads. The experimental results show that, compared with a conventional MLC STT-RAM last level cache design, our overhead minimized technique reduces the dynamic energy consumption by 38.2% on average with the same system performance, and our capacity augmented technique boosts the system performance by 6.1% with 19.2% dynamic energy saving on average, across the evaluated multi-programmed benchmarks.

Due to the leakage power of CMOS-based memory, Nonvolatile magnetic memory is considered a strong candidate to replace the CMOS-based memory. Spin transfer torque magnetic random access memory (STT-MRAM) is one of the most promising candidates, but it still has many shortcomings related to the write operation. Compared to STT-MRAM, spin orbit torque magnetic random access memory (SOT-MRAM) is the next generation of nonvolatile magnetic memory because of its relatively good performance and low power. Although SOT-MRAM has various advantages over STT-MRAM, a significant reduction in write power is required to meet the power level of CMOS-based memory. In this paper, we present a low power SOT-MRAM cell configuration using the dual write operation. By writing on two cells simultaneously, write energy can be reduced depending on data patterns. Compared to the conventional 2T-1MTJ SOT-MRAM, the proposed SOT-MRAM cell with the dual write scheme reduces the write energy by 26.3% on average.

Emerging technologies such as Spin-transfer torque magnetic random-access memory (STT-MRAM) are considered potential candidates for implementing low-power, high density storage systems. The vulnerability of such nonvolatile memory (NVM) based cryptosystems to standard side-channel attacks must be thoroughly assessed before deploying them in practice. In this paper, we outline a generic Correlation Power Analysis (CPA) attack strategy against STT-MRAM based cryptographic designs using a new power model. In our proposed attack methodology, an adversary exploits the power consumption patterns during the write operation of an STT-MRAM based cryptographic implementation to successfully retrieve the secret key. In order to validate our proposed attack technique, we mounted a CPA attack on MICKEY-128 2.0 stream cipher design consisting of STT-MRAM cells with Magnetic Tunnel Junctions (MTJs) as storage elements. The results of the experiments show that the STT-MRAM based implementation of the cipher circuit is susceptible to standard differential power analysis attack strategy provided a suitable hypothetical power model (such as the one proposed in this paper) is selected. In addition, we also investigated the effectiveness of state-of-the-art side-channel attack countermeasures for MRAMs and found that our proposed scheme is able to break such protected implementations as well.