ALARM: Active LeArning of Rowhammer Mitigations

A dynamic oxide semiconductor random access memory (DOSRAM) array that achieves reduction in storage capacitance (Cs) and decrease in refresh rate has been fabricated by using a c-axis aligned crystalline oxide semiconductor (CAAC-OS) transistor (L = 60 nm) with an extremely low off-state current. We have confirmed that this array, composed of cells that include a CAAC-OS transistor with W/L = 40 nm/60 nm using InGaZnO and a 3.9 fF storage capacitor, operates with write and read times of 5 ns. Therefore, DOSRAM can ensure sufficient Cs while maintaining operation speed comparable to that of dynamic random access memory (DRAM). We have found that the read signal voltage of DOSRAM is changed by approximately 30 mV after 1 h at 85 °C. Thus, DOSRAM is a promising replacement for DRAM.

Dynamic random access memory (DRAM) is one key component in modern electronic systems. In this paper, we propose a software-hardware-cooperated built-in self-test (SHC-BIST) scheme for the channel-based DRAMs. The testing of DRAMs consists of two major phases: DRAM initialization and DRAM array testing. Typically, the DRAM initialization process is short and executed in the beginning of the DRAM array testing. Thus, it is inefficient to realize it using the dedicated BIST hardware. On the other hand, it is not time efficient if we use the processor (software) to execute the DRAM array testing. Therefore, the SHC-BIST scheme uses a programmable BIST circuit to execute the DRAM array testing and takes advantage of the processor to execute the DRAM initialization and control the programmable BIST circuit such that the test time and hardware cost can be minimized. We verify the SHC-BIST scheme using a system with a LEON3 processor and a multi-channel DRAM.

The larger volume of capacitor and higher leakage current of transistor have become the inherent disadvantages for the traditional one transistor (1T)-one capacitor (1C) dynamic random access memory (DRAM). Recently, the tunneling FET (TFET) is applied in DRAM cell due to the low off-state current and high switching ratio. The dual-gate TFET (DG-TFET) DRAM cell with the capacitorless structure has the superior performance-higher retention time (RT) and weak temperature dependence. But the performance of TFET DRAM cell is sensitive to programming condition. In this paper, the guideline of programming optimization is discussed in detail by using simulation tool—Silvaco Atlas. Both the writing and reading operations of DG-TFET DRAM depend on the band-to-band tunneling (BTBT). During the writing operation, the holes coming from BTBT governed by Gate2 are stored in potential well under Gate2. A small negative voltage is applied at Gate2 to retain holes for a long time during holding “1”. The BTBT governed by Gate1 mainly influences the reading current. Using the optimized programming condition, the DG-TFET DRAM obtains the higher current ratio of reading “1” to reading “0” (107) and RT of more than 2 s. The higher RT reduces the refresh rate and dynamic power consumption of DRAM.

Dynamic random access memory (DRAM) is facing the challenge of technology scaling. The de-creasing feature size makes it harder to make DRAM cells which can keep the current data-holding time. When DRAM cells cannot hold data for a long time, DRAM chips need a more frequent refreshing operation. There-fore, in the near future, time and energy cost on DRAM refreshing will be no longer trivial. In this paper, we propose DRAM Error Correction Pointer (ECP), an error-correction-manner framework, to reduce DRAM re-freshes without data loss. We exploit the non-uniform feature of DRAM cells with respect to the data retention time. Compared with the conventional refreshing mechanisms, which refresh DRAM chips by the retention time of the leakiest cells, we refresh the chips much fewer times, and treat the not-in-time refreshed cells as fault elements. We use the structure of ECP as a fault tolerant element. By recording the data which are supposed to be written into the leaky cells in our DRAM-ECP structures, DRAM-ECP can significantly decrease refreshing frequency. When these data are to be read out, DRAM-ECP retrieves the data stored in ECPs and covers them to the corresponding position in the data row. Our experiments show that DRAM-ECP can reduce over 70% refreshing operations than the current refreshing mechanism and also get significant energy saving.

In this paper, the dynamic random access memory (DRAM) cell technology is introduced and the important technological breakthroughs are reviewed. The criteria of DRAM memory cell design is discussed and the key fabrication technologies of 6F2 memory cell and stack capacitor DRAM cell are summarized. The technological evolution of array access transistor is also reviewed. The transistors with U-shaped transistor or FinFET and the fabrication process flow of 6F2 DRAM chip were discussed. Based upon the technical requirements for DRAM cell, the possible device technologies for the next generation DRAM cell was summarized. It is predicted that (1) U-shape channel transistor will be the mainstream technology for the future DRAM cell beyond 20 nm; (2) low k material will be required for decreasing the bitline parasitic capacitance; (3) sense-amplifier with better signal-noise margin will be required to ease the requirement of high aspect-ratio storage capacitance; (4) low power DRAM design will draw more attention, rather than increasing the storage capacity of DRAM.

Journaling techniques play an important role in addressing the reliability issue of filesystems caused by the volatile dynamic random access memory (DRAM)-based buffer cache. However, journaling techniques introduce a large number of extra storage writes, which greatly degrades system performance, especially for mobile devices. Emerging nonvolatile memory (NVM) technologies bring a new perspective of solving the write amplification issue caused by journaling. By adopting NVM as the buffer cache, the committed data can be maintained in NVM before being written back to the storage, thus, eliminating the journaling overhead. However, simply utilizing NVM as the buffer cache suffers from the limited lifetime and the relatively longer write latency of NVM. In this paper, we present a hybrid buffer cache architecture, named UniBuffer, by combing NVM with dynamic random access memory (DRAM) to reduce the journaling overhead and overcome the inherent constraints of NVM. In UniBuffer, we first propose a journaling-aware page management (JAPM) policy to smartly allocate data to DRAM and NVM pages. JAPM puts infrequently updated data in NVM to reduce the journaling overhead and frequently updated data in DRAM to improve the write performance and lifetime of the hybrid buffer cache. In addition, since data in one journaling transaction may be dispersed in NVM and DRAM simultaneously, different committing policies are required for different storage media, respectively. In order to guarantee the atomicity of the transaction execution in the hybrid cache architecture, a partial in-place commit (PIPC) journaling scheme is proposed to coordinate different committing patterns for NVM and DRAM. We have implemented the proposed techniques on Linux 3.14.52 and measured the performance with representative I/O-intensive benchmarks. The experimental results show that our scheme effectively improves the I/O performance compared with the ext4 filesystem and prolongs the lifetime of the hybrid buffer cache compared with the union of buffer cache and journaling (UBJ) scheme.

As one of the cornerstones of computing, dynamic random-access memory (DRAM) is prevalent across digital systems. Over the years, researchers have proposed modifications to DRAM macros or explored alternative uses of existing DRAM chips to extend the functionality of this ubiquitous media. This work expands on the latter, providing new insights and demonstrating new functionalities in unmodified, commodity DRAM. FracDRAM is the first work to show how fractional values can be stored in off-the-shelf DRAM. We propose two primitive operations built with specially timed DRAM command sequences, to either store fractional values to the entire DRAM row or to masked bits in a row. Utilizing fractional values, this work enables more modules to perform the in-memory majority operation, increases the stability of the existing in-memory majority operation, and builds a state-of-the-art DRAM-based PUF with unmodified DRAM. In total, 582 DDR3 chips from seven major vendors are evaluated and characterized under different environments in this work. FracDRAM breaks through the conventional binary abstraction of DRAM logic, and brings new functions to the existing DRAM macro.

Dynamic random access memory (DRAM) is used as the main memory in every personal computer, due to its high density, high speed and efficient memory function. The ever-shrinking dimensions of DRAM cells with increasing packing density made the cell's capacitor size to be smaller. For successful operation of DRAM, a large cell capacitance (~ 25 fF) and low leakage current (10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-7</sup> A/cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> or 1 fA/cell) are required. In a traditional Si-based capacitor, the target cell capacitance has been achieved by increasing the surface area of the capacitor. More recently, innovations have been made by development of the component materials. A metal electrode, TiN or Ru, and a dielectric material with a moderate-k value (k is the relative dielectric constant), such as HfO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> (k ~ 25) and ZrO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> (k ~ 40), are being explored in giga-bit scale DRAMs. The minimum achievable t <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ox</sub> is ~ 0.7 nm for ZrO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> which is being used currently in DRAM industry. However, the technology road map for memory devices states that t <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ox</sub> of less than 0.45 nm is necessary for the DRAMs with a design rule of <; 20 nm. Perovskite-based dielectric films such as SrTiO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> (STO) and (Ba, Sr)TiO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> were reported to exhibit k values of several hundreds. However, growth of these films showed very slow growth rate and much more complicated processes than growth of binary oxide with the atomic layer deposition (ALD) technique which is a method of choice for the growth of the dielectric films and electrodes in microelectronic devices. Therefore, material and process innovations are necessary for next generation DRAM capacitors.

Dynamic Random Access Memory (DRAM) is widely used for data storage and, when a computer system is in operation, the DRAM can contain sensitive information such as passwords and cryptographic keys. Therefore, the DRAM is a prime target for hardware-based cryptanalytic attacks. These attacks can be performed in the supply chain to capture default key mechanisms enabling a later cyber attack or predisposition the system to remote effects. Two prominent attack classes against memory are the Cold Boot attack which recovers the data from the DRAM even after a supposed power-down and Rowhammer attack which violates memory integrity by influencing the stored bits to flip. In this paper, we propose an on-chip technique that obfuscates the memory addresses and data and provides a fast detect-response to defend against these hardware-based security attacks on DRAM. We advance the prior hardware security research by making two contributions. First, the key material is detected and erased before the Cold Boot attacker can extract the memory data. Second, our solution is on-chip and does not require nor depend on additional hardware or software which are open to additional supply chain attack vectors. We analyze the efficacy of our scheme through circuit simulation and compare the results to the previous mitigation approaches based on DRAM write operations. Our simulation and analysis results show that purging key information used for address and data randomization can be achieved much faster and with lower power than with typical DRAM write techniques used for sanitizing memory content. We demonstrate through circuit simulation of the key register design a technique that clears key information within 2.4ns which is faster by more than two orders magnitude compared to typical DRAM write operations for 180nm technology, and with a power consumption of 0.15 picoWatts.

This retrospective paper describes the RowHammer problem in dynamic random access memory (DRAM), which was initially introduced by Kim et al. at the ISCA 2014 Conference. RowHammer is a prime (and perhaps the first) example of how a circuit-level failure mechanism can cause a practical and widespread system security vulnerability. It is the phenomenon that repeatedly accessing a row in a modern DRAM chip causes bit flips in physically adjacent rows at consistently predictable bit locations. RowHammer is caused by a hardware failure mechanism called DRAM disturbance errors , which is a manifestation of circuit-level cell-to-cell interference in a scaled memory technology. Researchers from Google Project Zero demonstrated in 2015 that this hardware failure mechanism can be effectively exploited by user-level programs to gain kernel privileges on real systems. Many other follow-up works demonstrated other practical attacks exploiting RowHammer. In this paper, we comprehensively survey the scientific literature on RowHammer-based attacks as well as mitigation techniques to prevent RowHammer. We also discuss what other related vulnerabilities may be lurking in DRAM and other types of memories, e.g., NAND flash memory or phase change memory, that can potentially threaten the foundations of secure systems, as the memory technologies scale to higher densities. We conclude by describing and advocating a principled approach to memory reliability and security research that can enable us to better anticipate and prevent such vulnerabilities.

Refresh operations consume substantial energy and bandwidth in high-density dynamic random-access memory (DRAM) memory. The trend of increasing refresh overhead limits the scalability of DRAM memory that refreshes all cells at the same rate, because the refresh rate setting depends on the worst-case weak cell manufactured in unstable process technology. To cope with this issue, fine-grained refresh (FGR) is proposed to eliminate the unnecessary refresh operations caused by minor weak cells. Even JEDEC's DDR4 DRAM specification announces the support of FGR, which is likely to evolve and become a standard in future DRAM. Unfortunately, according to our key observation, the effectiveness of FGR is greatly confined by the procedure of refresh-oblivious device integration because all memory devices within a module have to be controlled and refreshed in a lockstep way after the step of assembly. In this paper, we are the first to propose a holistic FGR-oriented DRAM optimization framework, retention-aware DRAM assembly and repair (RADAR), to enhance the effectiveness of FGR in DRAM modules. RADAR includes two novel techniques applicable at the stage of DRAM assembly. The first one is retention-aware device clustering that integrates the “compatible” devices to achieve low refresh rate through a preassembly testing and retention-aware matching method. The second technique, Microfix, exploits the hierarchical DRAM array structure and its redundancy to fix critical weak DRAM rows through fine-grained row and subarray remapping. With this optimization architecture, RADAR, the refresh overhead of DRAM dual in-line memory modules can be dramatically reduced as implied in the experiments.

As the end of Moore’s law approaches, chiplet integration technology (or chiplet technology) has emerged to revolutionize future semiconductor chip design. Chiplet technology provides unique advantages over 3-D-stacking technology, including a more cost-efficient and thermal-friendly integration of heterogeneous technologies. Although chiplet technologies have already begun to be used by the latest commercial chips, they have not been explored for commodity dynamic random access memory (DRAM) design yet. Harnessing its advantages for DRAM for the first time, this article evaluates the feasibility of chiplet-based DRAM architecture, considering various physical and electrical constraints imposed by a standard chiplet interface [i.e., universal chiplet interconnect express (UCIe)]. We further explore the DIMM architectures that simplify module packaging and assembly, leading to reductions in total die size and overall costs. The comprehensive cross-level analysis (i.e., device, circuit, chip, and system levels) shows that chiplet-based DRAM reduces <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">t_RCD</monospace> + <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">t_CAS</monospace>, latency-critical DRAM timing parameters, by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1.32\times $ </tex-math></inline-formula>–<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1.39\times $ </tex-math></inline-formula>, at the same energy consumption. In addition, a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1.39\times $ </tex-math></inline-formula>–<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2.28\times $ </tex-math></inline-formula> improvement in <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">t_RRD</monospace> is obtained. The reduced DRAM timing parameters improve the overall system performance by up to 8.8%–24.7% (geomean 3.4%–8.4%) in real-life benchmarks. The chiplet-based heterogeneous integration achieves a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1.27\times $ </tex-math></inline-formula> higher chip-level yield compared with the monolithic chip, along with up to 10% reduction in overall cost compared with traditional DIMMs at emerging process technologies.

A multi-layer stacked Dynamic Random Access Memory (DRAM) platform is introduced to address the memory wall issue. This platform features high-density vertical interconnects established between DRAM units for high-capacity memory and logic units for computation, utilizing Wafer-on-Wafer (WoW) hybrid bonding and mini Through-Silicon Via (TSV) technologies. This 3DIC architecture includes commercial DRAM, logic, and 3DIC manufacturing processes. Their design documents typically come from different foundries, presenting challenges for signal integrity design and analysis. This paper establishes a lumped circuit based on 3DIC physical structure and calculates all values of the lumped elements in the circuit model with the transmission line model. A Cross-Process Signal Integrity Analysis (CPSIA) method is introduced, which integrates three different manufacturing processes by modeling vertical stacking cells and connecting DRAM and logic netlists in one simulation environment. In combination with the dedicated buffer driving method, the CPSIA method is used to analyze 3DIC impacts. Simulation results show that the timing uncertainty introduced by 3DIC crosstalk ranges from 31 ps to 62 ps. This analysis result explains the stable slight variation in the maximum frequency observed in vertically stacked memory arrays from different DRAM layers in the physical testing results, demonstrating the effectiveness of this CPSIA method.

On-chip dynamic random access memory (DRAM) cache has been recently employed in the memory hierarchy to mitigate the widening latency gap between high-speed cores and off-chip memory. Two important parameters are the DRAM cache miss rate (D$-MR) and the DRAM cache hit latency (D$-HL), as they strongly influence the performance. These parameters depend upon the DRAM set mapping policy. Recently proposed DRAM set mapping policies are predominantly optimized for either D$-MR or D$-HL. We propose novel DRAM set mapping policies that simultaneously reduce D$-MR (via high associativity) and D$-HL (via improved row buffer hit rates). To further improve the D$-HL, we propose a small and low latency DRAM Tag cache (DTC) structure that can quickly determine whether an access to the DRAM cache will be a hit or a miss. The performance of the proposed DTC depends upon the DTC hit rate. To increase it, we present a novel DTC insertion policy that also increases the DTC hit rate. We investigate the latency and miss rate tradeoffs when designing a DRAM cache hierarchy and analyze the effects of different policies on the overall performance. We evaluate our policies on a wide variety of workloads and compare its performance with three recent proposals for on-chip DRAM caches. For a 16-core system, our set mapping policy along with our DTC and its adaptive DTC insertion policy improve the harmonic mean instruction per cycle throughput by 25.4%, 15.5%, and 7.3% compared to state-of-the-art, while requiring 55% less storage overhead for DRAM cache hit/miss prediction.

The traditional dynamic random-access memory (DRAM) storage medium can be integrated on chips via modern emerging 3D-stacking technology to architect a DRAM shared cache in multicore systems. Compared with static random-access memory (SRAM), DRAM is larger but slower. In the existing research, a lot of work has been devoted to improving the workload performance using SRAM and stacked DRAM together in shared cache systems, ranging from SRAM structure improvement to optimizing cache tags and data access. However, little attention has been paid to designing a shared cache scheduling scheme for multiprogrammed workloads with different memory footprints in multicore systems. Motivated by this, we propose a hybrid shared cache scheduling scheme that allows a multicore system to utilize SRAM and 3D-stacked DRAM efficiently, thus achieving better workload performance. This scheduling scheme employs (1) a cache monitor, which is used to collect cache statistics; (2) a cache evaluator, which is used to evaluate the cache information during the process of programs being executed; and (3) a cache switcher, which is used to self-adaptively choose SRAM or DRAM shared cache modules. A cache data migration policy is naturally developed to guarantee that the scheduling scheme works correctly. Extensive experiments are conducted to evaluate the workload performance of our proposed scheme. The experimental results showed that our method can improve the multiprogrammed workload performance by up to 25% compared with state-of-the-art methods (including conventional and DRAM cache systems).