Process Variation Aware DRAM (Dynamic Random Access Memory) Design Using Block-Based Adaptive Body Biasing Algorithm

Large dense structures like DRAMs (Dynamic Random Access Memory) are particularly susceptible to process variation, which can lead to variable latencies in different memory arrays. However, very little work exists on variation studies in DRAMs. This is due to the fact that DRAMs were traditionally placed off-chip and their latency changes due to process variation did not impact the overall processor performance. However, emerging technology trends like three-dimensional integration, use of sophisticated memory controllers, and continued scaling of technology node, substantially reduce DRAM access latency. Hence, future technology nodes will see widespread adoption of embedded DRAMs. This makes process variation a critical upcoming challenge in DRAMs that must be addressed in current and forthcoming technology generations. In this paper, techniques for modeling the effect of random, as well as spatial variation, in large DRAM array structures are presented. Sensitivity-based gate level process variation models combined with statistical timing analysis are used to estimate the impact of process variation on the DRAM performance and leakage power. A simulated annealing-based Vth assignment algorithm using adaptive body biasing is proposed in this thesis to improve the yield of DRAM structures. By applying the algorithm on a 1GB DRAM array, an average of 14.66% improvement in the DRAM yield is obtained

Dynamic fine-grain body biasing of caches with latency and leakage 3T1D-based monitors

In this paper, we propose a dynamically tunable fine-grain body biasing mechanism to reduce active & standby leakage power in caches under process variations.Preprin

Robust low-power digital circuit design in nano-CMOS technologies

Device scaling has resulted in large scale integrated, high performance, low-power, and low cost systems. However the move towards sub-100 nm technology nodes has increased variability in device characteristics due to large process variations. Variability has severe implications on digital circuit design by causing timing uncertainties in combinational circuits, degrading yield and reliability of memory elements, and increasing power density due to slow scaling of supply voltage. Conventional design methods add large pessimistic safety margins to mitigate increased variability, however, they incur large power and performance loss as the combination of worst cases occurs very rarely. In-situ monitoring of timing failures provides an opportunity to dynamically tune safety margins in proportion to on-chip variability that can significantly minimize power and performance losses. We demonstrated by simulations two delay sensor designs to detect timing failures in advance that can be coupled with different compensation techniques such as voltage scaling, body biasing, or frequency scaling to avoid actual timing failures. Our simulation results using 45 nm and 32 nm technology BSIM4 models indicate significant reduction in total power consumption under temperature and statistical variations. Future work involves using dual sensing to avoid useless voltage scaling that incurs a speed loss. SRAM cache is the first victim of increased process variations that requires handcrafted design to meet area, power, and performance requirements. We have proposed novel 6 transistors (6T), 7 transistors (7T), and 8 transistors (8T)-SRAM cells that enable variability tolerant and low-power SRAM cache designs. Increased sense-amplifier offset voltage due to device mismatch arising from high variability increases delay and power consumption of SRAM design. We have proposed two novel design techniques to reduce offset voltage dependent delays providing a high speed low-power SRAM design. Increasing leakage currents in nano-CMOS technologies pose a major challenge to a low-power reliable design. We have investigated novel segmented supply voltage architecture to reduce leakage power of the SRAM caches since they occupy bulk of the total chip area and power. Future work involves developing leakage reduction methods for the combination logic designs including SRAM peripherals

Design of robust spin-transfer torque magnetic random access memories for ultralow power high performance on-chip cache applications

Spin-transfer torque magnetic random access memories (STT-MRAMs) based on magnetic tunnel junction (MTJ) has become the leading candidate for future universal memory technology due to its potential for low power, non-volatile, high speed and extremely good endurance. However, conflicting read and write requirements exist in STT-MRAM technology because the current path during read and write operations are the same. Read and write failures of STT-MRAMs are degraded further under process variations. The focus of this dissertation is to optimize the yield of STT- MRAMs under process variations by employing device-circuit-architecture co-design techniques. A devices-to-systems simulation framework was developed to evaluate the effectiveness of the techniques proposed in this dissertation. An optimization methodology for minimizing the failure probability of 1T-1MTJ STT-MRAM bit-cell by proper selection of bit-cell configuration and access transistor sizing is also proposed. A failure mitigation technique using assistsin 1T-1MTJ STT-MRAM bit-cells is also proposed and discussed. Assist techniques proposed in this dissertation to mitigate write failures either increase the amount of current available to switch the MTJ during write or decrease the required current to switch the MTJ. These techniques achieve significant reduction in bit-cell area and write power with minimal impact on bit-cell failure probability and read power. However, the proposed write assist techniques may be less effective in scaled STT-MRAM bit-cells. Furthermore, read failures need to be overcome and hence, read assist techniques are required. It has been experimentally demonstrated that a class of materials called multiferroics can enable manipulation of magnetization using electric fields via magnetoelectric effects. A read assist technique using an MTJ structure incorporating multiferroic materials is proposed and analyzed. It was found that it is very difficult to overcome the fundamental design issues with 1T-1MTJ STT-MRAM due to the two-terminal nature of the MTJ. Hence, multi-terminal MTJ structures consisting of complementary polarized pinned layers are proposed. Analysis of the proposed MTJ structures shows significant improvement in bit-cell failures. Finally, this dissertation explores two system-level applications enabled by STT-MRAMs, and shows that device-circuit-architecture co-design of STT-MRAMs is required to fully exploit its benefits

Temperature Variation Operation of Mixed-VT 3T GC-eDRAM for Low Power Applications in 2Kbit Memory Array

Embedded memories were once utilized to transfer information between the CPU and the main memory. The cache storage in most traditional computers was static-random-access-memory (SRAM). Other memory technologies, such as embedded dynamic random-access memory (eDRAM) and spin-transfer-torque random-access memory (STT-RAM), have also been used to store cache data. The SRAM, on the other hand, has a low density and severe leakage issues, and the STT-RAM has high latency and energy consumption when writing. The gain-cell eDRAM (GC-eDRAM), which has a higher density, lower leakage, logic compatibility, and is appropriate for two-port operations, is an attractive option. To speed up data retrieval from the main memory, future processors will require larger and faster-embedded memories. Area overhead, power overhead, and speed performance are all issues with the existing architecture. A unique mixed-V_T 3T GC-eDRAM architecture is suggested in this paper to improve data retention times (DRT) and performance for better energy efficiency in embedded memories. The GC-eDRAM is simulated using a standard complementary-metal-oxide-semiconductor (CMOS) with a 130nm technology node transistor. The performance of a 2kbit mixed-V_T 3T GC-eDRAM array were evaluated through corner process simulations. Each memory block is designed and simulated using Mentor Graphics Software. The array, which is based on the suggested bit-cell, has been successfully operated at 400Mhz under a 1V supply and takes up almost 60-75% less space than 6T SRAM using the same technology. When compared to the existing 6T and 4T ULP SRAMs (others' work), the retention power of the proposed GC-eDRAM is around 80-90% lower

Reliability in the face of variability in nanometer embedded memories

In this thesis, we have investigated the impact of parametric variations on the behaviour of one performance-critical processor structure - embedded memories. As variations manifest as a spread in power and performance, as a first step, we propose a novel modeling methodology that helps evaluate the impact of circuit-level optimizations on architecture-level design choices. Choices made at the design-stage ensure conflicting requirements from higher-levels are decoupled. We then complement such design-time optimizations with a runtime mechanism that takes advantage of adaptive body-biasing to lower power whilst improving performance in the presence of variability. Our proposal uses a novel fully-digital variation tracking hardware using embedded DRAM (eDRAM) cells to monitor run-time changes in cache latency and leakage. A special fine-grain body-bias generator uses the measurements to generate an optimal body-bias that is needed to meet the required yield targets. A novel variation-tolerant and soft-error hardened eDRAM cell is also proposed as an alternate candidate for replacing existing SRAM-based designs in latency critical memory structures. In the ultra low-power domain where reliable operation is limited by the minimum voltage of operation (Vddmin), we analyse the impact of failures on cache functional margin and functional yield. Towards this end, we have developed a fully automated tool (INFORMER) capable of estimating memory-wide metrics such as power, performance and yield accurately and rapidly. Using the developed tool, we then evaluate the #effectiveness of a new class of hybrid techniques in improving cache yield through failure prevention and correction. Having a holistic perspective of memory-wide metrics helps us arrive at design-choices optimized simultaneously for multiple metrics needed for maintaining lifetime requirements

Low Power SoC Design

The design of Low Power Systems-on-Chips (SoC) in very deep submicron technologies becomes a very complex task that has to bridge very high level system description with low-level considerations due to technology defaults and variations and increasing system and circuit complexity. This paper describes the major low-level issues, such as dynamic and static power consumption, temperature, technology variations, interconnect, DFM, reliability and yield, and their impact on high-level design, such as the design of multi-Vdd, fault-tolerant, redundant or adaptive chip architectures. Some very low power System-on-Chip (SoC) will be presented in three domains: wireless sensor networks, vision sensors and mobile TV

Embracing Low-Power Systems with Improvement in Security and Energy-Efficiency

As the economies around the world are aligning more towards usage of computing systems, the global energy demand for computing is increasing rapidly. Additionally, the boom in AI based applications and services has already invited the pervasion of specialized computing hardware architectures for AI (accelerators). A big chunk of research in the industry and academia is being focused on providing energy efficiency to all kinds of power hungry computing architectures. This dissertation adds to these efforts. Aggressive voltage underscaling of chips is one the effective low power paradigms of providing energy efficiency. This dissertation identifies and deals with the reliability and performance problems associated with this paradigm and innovates novel energy efficient approaches. Specifically, the properties of a low power security primitive have been improved and, higher performance has been unlocked in an AI accelerator (Google TPU) in an aggressively voltage underscaled environment. And, novel power saving opportunities have been unlocked by characterizing the usage pattern of a baseline TPU with rigorous mathematical analysis

SEU sensitivity and modeling using picosecond pulsed laser stimulation of a D Flip-Flop in 40 nm CMOS technology

International audience—This paper presents the design of a CMOS 40 nm D Flip-Flop cell and reports the laser fault sensitivity mapping both with experiments and simulation results. Theses studies are driven by the need to propose a simulation methodology based on laser/silicon interactions with a complex integrated circuit. In the security field, it is therefore mandatory to understand the behavior of sensitive devices like D Flip-Flops to laser stimulation. In previous works, Roscian et al., Sarafianos et al., Lacruche et al. or Courbon et al. studied the relations between the layout of cells, its different laser-sensitive areas and their associated fault model using laser pulse duration in the nanosecond range. In this paper, we report similar experiments carried out using a shorter laser pulse duration (30 ps instead of 50 ns). We also propose an upgrade of the simulation model they used to take into account laser pulse durations in the picosecond range on a logic gate composed of a large number of transistors for a recent CMOS technology (40 nm)