6 research outputs found

    Design of Address Decoder and Sense Amplifier for SRAM

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    Address decoder and sense amplifier is important component of SRAM memory. Selection of storage cell and read operation is depends on decoder and sense amplifier respectively. Hence, performance of SRAM is depends on these components. This work survey the address decoder and sense amplifier for SRAM memory, concentrating on delay optimization and power efficient circuit techniques. We have concentrated on optimal decoder structure with least number of transistors to reduce area of SRAM In static decoders we have stared with simple AND gate decoder and its result is examined. These simple decoder are neither area efficient nor faster one because AND/OR gate are not natural gates, they are made up from combination of NAND/NOR and NOT gate. Decoder having only NOR/NAND gate are area efficient and fast too. Therefore universal decoding having NAND-NOR alternate stages scheme is taken and examined. Universal decoding scheme are having some serious issue like different path delay which may results in false decoding as well as extra power dissipation. To overcome from this issue Novel Address decoding scheme is implemented and their result is compared with simple AND decoder and Universal decoder. Novel address decoder circuit is presented and analyzed. Novel address decoder using NAND-NOR alternate stages with pre-decoder and replica inverter chain circuit is implemented successfully. Current mirror sense-amp and latched type sense amplifier is also implemented for SRAM. These two amplifiers are the basic one and having tremendous advantage due to their small size. They are fast enough and can be fit below the SRAM cell. We have implemented and tested 1Kb; 8 bit; 1.25GHz SRAM memory in Cadence by using UMC 90nm technology, for that decoder and sense amplifier is deployed

    Reliability in the face of variability in nanometer embedded memories

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    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

    myCACTI: A new cache design tool for pipelined nanometer caches

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    TThe presence of caches in microprocessors has always been one of the most important techniques in bridging the memory wall, or the speed gap between the microprocessor and main memory. This importance is continuously increasing especially as we enter the regime of nanometer process technologies (i.e. 90nm and below), as industry has favored investing a larger and larger fraction of a chip.s transistor budget to improving the on-chip cache. This is the case in practice, as it has proven to be an efficient way to utilize the increasing number of transistors available with each succeeding technology. Consequently, it becomes even more important to have cache design tools that give accurate representations of designs that exist in actual microprocessors. The prevalent cache design tools that are the most widely used in academe are CACTI [Wilton1996] and eCACTI [Mamidipaka2004], and these have proven to be very useful tools not just for cache designers, but also for computer architects. This dissertation will show that both CACTI and eCACTI still contain major limitations and even flaws in their design, making them unsuitable for use in very-deep submicron and nanometer caches, especially pipelined designs. These limitations and flaws will be discussed in detail. This dissertation then introduces a new tool, called myCACTI, that addresses all these limitations and, in addition, introduces major enhancements to the simulation framework. This dissertation then demonstrates the use of myCACTI in the cache design process. Detailed design space explorations are done on multiple cache configurations to produce pareto optimal curves of the caches to show optimal implementations. Detailed studies are also performed to characterize the delay and power dissipation of different cache configurations and implementations. Finally, future directions to the development of myCACTI are identified to show possible ways that the tool can be improved in such a way as to allow even more different kinds of studies to be performed

    Low Power Memory/Memristor Devices and Systems

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    This reprint focusses on achieving low-power computation using memristive devices. The topic was designed as a convenient reference point: it contains a mix of techniques starting from the fundamental manufacturing of memristive devices all the way to applications such as physically unclonable functions, and also covers perspectives on, e.g., in-memory computing, which is inextricably linked with emerging memory devices such as memristors. Finally, the reprint contains a few articles representing how other communities (from typical CMOS design to photonics) are fighting on their own fronts in the quest towards low-power computation, as a comparison with the memristor literature. We hope that readers will enjoy discovering the articles within
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