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

Review on suitable eDRAM configurations for next nano-metric electronics era

We summarize most of our studies focused on the main reliability issues that can threat the gain-cells eDRAM behavior when it is simulated at the nano-metric device range has been collected in this review. So, to outperform their memory cell counterparts, we explored different technological proposals and operational regimes where it can be located. The best memory cell performance is observed for the 3T1D-eDRAM cell when it is based on FinFET devices. Both device variability and SEU appear as key reliability issues for memory cells at sub-22nm technology node.Peer ReviewedPostprint (author's final draft

Review and Classification of Gain Cell eDRAM Implementations

With the increasing requirement of a high-density, high-performance, low power alternative to traditional SRAM, Gain Cell (GC) embedded DRAMs have gained a renewed interest in recent years. Several industrial and academic publications have presented GC memory implementations for various target applications, including high-performance processor caches, wireless communication memories, and biomedical system storage. In this paper, we review and compare the recent publications, examining the design requirements and the implementation techniques that lead to achievement of the required design metrics of these applications

Technology Implications for Large Last-Level Caches

Large last-level cache (L3C) is efficient for bridging the performance and power gap between processor and memory. Several memory technologies, including SRAM, STT-RAM (MRAM), and embedded DRAM (eDRAM), have been used or considered as the technology to implement L3Cs. However, each of them has inherent weaknesses: SRAM is relatively low density and dissipates high leakage; STT-RAM has long write latency and requires high write energy; eDRAM requires refresh. As future processors are expected to have larger last-level caches, the objective of this dissertation is to study the tradeoffs associated with using each of these technologies to implement L3Cs. In order to make useful comparisons between L3Cs built with SRAM, STT-RAM, and eDRAM, we consider and implement several levels of details. First, to obtain unbiased cache performance and power properties (i.e., read/write access latency, read/write access energy, leakage power, refresh power, area), we prototype caches based on realistic memory and device models. Second, we present simplistic analytical models that enable us to quickly examine different memory technologies under various scenarios. Third, we review power-optimization techniques for each of the technologies, and propose using a low-cost dead-line prediction scheme for eDRAM-based L3Cs to eliminate unnecessary refreshes. Finally, the highlight of this dissertation is the comparison and analysis of low-leakage SRAM, low write-energy STT-RAM, and refresh-optimized eDRAM. We report system performance, last-level cache energy breakdown, and memory hierarchy energy breakdown, using an augmented full-system simulator with the execution of a range of workloads and input sets. From the insights gained through simulation results, STT-RAM has the highest potential to save energy in future L3C designs. For contemporary processors, SRAM-based L3C results in the fastest system performance, whereas eDRAM consumes the lowest energy

ULTRA ENERGY-EFFICIENT SUB-/NEAR-THRESHOLD COMPUTING: PLATFORM AND METHODOLOGY

Ph.DDOCTOR OF PHILOSOPH

Design techniques for dense embedded memory in advanced CMOS technologies

University of Minnesota Ph.D. dissertation. February 2012. Major: Electrical Engineering. Advisor: Chris H. Kim. 1 computer file (PDF); viii, 116 pages.On-die cache memory is a key component in advanced processors since it can boost micro-architectural level performance at a moderate power penalty. Demand for denser memories only going to increase as the number of cores in a microprocessor goes up with technology scaling. A commensurate increase in the amount of cache memory is needed to fully utilize the larger and more powerful processing units. 6T SRAMs have been the embedded memory of choice for modern microprocessors due to their logic compatibility, high speed, and refresh-free operation. However, the relatively large cell size and conflicting requirements for read and write make aggressive scaling of 6T SRAMs challenging in sub-22 nm. In this dissertation, circuit techniques and simulation methodologies are presented to demonstrate the potential of alternative options such as gain cell eDRAMs and spin-torque-transfer magnetic RAMs (STT-MRAMs) for high density embedded memories.Three unique test chip designs are presented to enhance the retention time and access speed of gain cell eDRAMs. Proposed bit-cells utilize preferential boostings, beneficial couplings, and aggregated cell leakages for expanding signal window between data `1' and `0'. The design space of power-delay product can be further enhanced with various assist schemes that harness the innate properties of gain cell eDRAMs. Experimental results from the test chips demonstrate that the proposed gain cell eDRAMs achieve overall faster system performances and lower static power dissipations than SRAMs in a generic 65 nm low-power (LP) CMOS process. A magnetic tunnel junction (MTJ) scaling scenario and an efficient HSPICE simulation methodology are proposed for exploring the scalability of STT-MRAMs under variation effects from 65 nm to 8 nm. A constant JC0*RA/VDD scaling method is adopted to achieve optimal read and write performances of STT-MRAMs and thermal stabilities for a 10 year retention are achieved by adjusting free layer thicknesses as well as projecting crystalline anisotropy improvements. Studies based on the proposed methodology show that in-plane STT-MRAM will outperform SRAM from 15 nm node, while its perpendicular counterpart requires further innovations in MTJ material properties in order to overcome the poor write performance from 22 nm node

Cache memory design in the FinFET era

The major problem in the future technology scaling is the variations in process parameters that are interpreted as imperfections in the development process. Moreover, devices are more sensitive to the environmental changes of temperature and supply volt- age as well as to ageing. All these influences are manifested in the integrated circuits as increased power consumption, reduced maximal operating frequency and increased number of failures. These effects have been partially overcome with the introduction of the FinFET technology which have solved the problem of variability caused by Random Dopant Fluctuations. However, in the next ten years channel length is projected to shrink to 10nm where the variability source generated by Line Edge Roughness will dominate, and its effects on the threshold voltage variations will become critical. The embedded memories with their cells as the basic building unit are the most prone to these effects due to their the smallest dimensions. Because of that, memories should be designed with particular care in order to make possible further technology scaling. This thesis explores upcoming 10nm FinFETs and the existing issues in the cache memory design with this technology. More- over, it tries to present some original and novel techniques on the different level of design abstraction for mitigating the effects of process and environmental variability. At first original method for simulating variability of Tri-Gate Fin- FETs is presented using conventional HSPICE simulation environment and BSIM-CMG model cards. When that is accomplished, thorough characterisation of traditional SRAM cell circuits (6T and 8T) is performed. Possibility of using Independent Gate FinFETs for increasing cell stability has been explored, also. Gain Cells appeared in the recent past as an attractive alternative for in the cache memory design. This thesis partially explores this idea by presenting and performing detailed circuit analysis of the dynamic 3T gain cell for 10nm FinFETs. At the top of this work, thesis shows one micro-architecture optimisation of high-speed cache when it is implemented by 3T gain cells. We show how the cache coherency states can be used in order to reduce refresh energy of the memory as well as reduce memory ageing.El principal problema de l'escalat la tecnologia són les variacions en els paràmetres de disseny (imperfeccions) durant procés de fabricació. D'altra banda, els dispositius també són més sensibles als canvis ambientals de temperatura, la tensió d'alimentació, així com l'envelliment. Totes aquestes influències es manifesten en els circuits integrats com l'augment de consum d'energia, la reducció de la freqüència d'operació màxima i l'augment del nombre de xips descartats. Aquests efectes s'han superat parcialment amb la introducció de la tecnologia FinFET que ha resolt el problema de la variabilitat causada per les fluctuacions de dopants aleatòries. No obstant això, en els propers deu anys, l'ample del canal es preveu que es reduirà a 10nm, on la font de la variabilitat generada per les rugositats de les línies de material dominarà, i els seu efecte en les variacions de voltatge llindar augmentarà. Les memòries encastades amb les seves cel·les com la unitat bàsica de construcció són les més propenses a sofrir aquests efectes a causa de les seves dimensions més petites. A causa d'això, cal dissenyar les memòries amb una especial cura per tal de fer possible l'escalat de la tecnologia. Aquesta tesi explora la tecnologia de FinFETs de 10nm i els problemes existents en el disseny de memòries amb aquesta tecnologia. A més a més, presentem noves tècniques originals sobre diferents nivells d'abstracció del disseny per a la mitigació dels efectes les variacions tan de procés com ambientals. En primer lloc, presentem un mètode original per a la simulació de la variabilitat de Tri-Gate FinFETs usant entorn de simulació HSPICE convencional i models de tecnologia BSIMCMG. Després, es realitza la caracterització completa dels circuits de cel·les SRAM tradicionals (6T i 8T) conjuntament amb l'ús de Gate-independent FinFETs per augmentar l'estabilitat de la cèl·lula