560 research outputs found

    Tagged repair techniques for defect tolerance in hybrid nano/CMOS architecture

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    We propose two new repair techniques for hybrid nano/CMOS computing architecture with lookup table based Boolean logic. Our proposed techniques use tagging mechanism to provide high level of defect tolerance and we present theoretical equations to predict the repair capability including an estimate of the repair cost. The repair techniques are efficient in utilization of spare units and capable of targeting upto 20% defect rates, which is higher than recently reported repair techniques

    The Efficacy of Programming Energy Controlled Switching in Resistive Random Access Memory (RRAM)

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    Current state-of-the-art memory technologies such as FLASH, Static Random Access Memory (SRAM) and Dynamic RAM (DRAM) are based on charge storage. The semiconductor industry has relied on cell miniaturization to increase the performance and density of memory technology, while simultaneously decreasing the cost per bit. However, this approach is not sustainable because the charge-storage mechanism is reaching a fundamental scaling limit. Although stack engineering and 3D integration solutions can delay this limit, alternate strategies based on non-charge storage mechanisms for memory have been introduced and are being actively pursued. Resistive Random Access Memory (RRAM) has emerged as one of the leading candidates for future high density non-volatile memory. The superior scalability of RRAMs is based on the highly localized active switching region and filamentary conductive path. Coupled with its simple structure and compatibility with complementary metal oxide semiconductor (CMOS) processes; RRAM cells have demonstrated switching performance comparable to volatile memory technologies such as DRAMs and SRAMs. However, there are two serious barriers to RRAM commercialization. The first is the variability of the resistance state which is associated with the inherent randomness of the resistive switching mechanism. The second is the filamentary nature of the conductive path which makes it susceptible to noise. In this experimental thesis, a novel program-verify (P-V) technique was developed with the objective to specifically address the programming errors and to provide solutions to the most challenging issues associated with these intrinsic failures in current RRAM technology. The technique, called Compliance-free Ultra-short Smart Pulse Programming (CUSPP), utilizes sub-nanosecond pulses in a compliance-free setup to minimize the programming energy delivered per pulse. In order to demonstrate CUSPP, a custom-built picosecond pulse generator and feedback control circuit was designed. We achieved high (108 cycles) endurance with state verification for each cycle and established high-speed performance, such as 100 ps write/erase speed and 500 kHz cycling rate of HfO2-based RRAM cells. We also investigate switching failure and the short-term instability of the RRAM using CUSPP

    Application of advanced on-board processing concepts to future satellite communications systems: Bibliography

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    Abstracts are presented of a literature survey of reports concerning the application of signal processing concepts. Approximately 300 references are included

    SPICE²: A Spatial, Parallel Architecture for Accelerating the Spice Circuit Simulator

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    Spatial processing of sparse, irregular floating-point computation using a single FPGA enables up to an order of magnitude speedup (mean 2.8X speedup) over a conventional microprocessor for the SPICE circuit simulator. We deliver this speedup using a hybrid parallel architecture that spatially implements the heterogeneous forms of parallelism available in SPICE. We decompose SPICE into its three constituent phases: Model-Evaluation, Sparse Matrix-Solve, and Iteration Control and parallelize each phase independently. We exploit data-parallel device evaluations in the Model-Evaluation phase, sparse dataflow parallelism in the Sparse Matrix-Solve phase and compose the complete design in streaming fashion. We name our parallel architecture SPICE²: Spatial Processors Interconnected for Concurrent Execution for accelerating the SPICE circuit simulator. We program the parallel architecture with a high-level, domain-specific framework that identifies, exposes and exploits parallelism available in the SPICE circuit simulator. This design is optimized with an auto-tuner that can scale the design to use larger FPGA capacities without expert intervention and can even target other parallel architectures with the assistance of automated code-generation. This FPGA architecture is able to outperform conventional processors due to a combination of factors including high utilization of statically-scheduled resources, low-overhead dataflow scheduling of fine-grained tasks, and overlapped processing of the control algorithms. We demonstrate that we can independently accelerate Model-Evaluation by a mean factor of 6.5X(1.4--23X) across a range of non-linear device models and Matrix-Solve by 2.4X(0.6--13X) across various benchmark matrices while delivering a mean combined speedup of 2.8X(0.2--11X) for the two together when comparing a Xilinx Virtex-6 LX760 (40nm) with an Intel Core i7 965 (45nm). With our high-level framework, we can also accelerate Single-Precision Model-Evaluation on NVIDIA GPUs, ATI GPUs, IBM Cell, and Sun Niagara 2 architectures. We expect approaches based on exploiting spatial parallelism to become important as frequency scaling slows down and modern processing architectures turn to parallelism (\eg multi-core, GPUs) due to constraints of power consumption. This thesis shows how to express, exploit and optimize spatial parallelism for an important class of problems that are challenging to parallelize.</p

    Development and characterisation of Monolithic Active Pixel Sensor prototypes for the upgrade of the ALICE Inner Tracking System

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    ALICE (A Large Ion Collider Experiment) is dedicated to the study and characterisation of the Quark-­‐Gluon Plasma (QGP), exploiting the unique potential of ultrarelativistic heavy-­‐ion collisions at the CERN Large Hadron Collider (LHC). The increase of the LHC luminosity leading up to about 50 kHz Pb-­‐Pb interaction rate after the second long shutdown (in 2018-­‐2019) will offer the possibility to perform high precision measurements of rare probes over a wide range of momenta. These measurements are statistically limited or not even possible with the present experimental set up. For this reason, an upgrade strategy for several ALICE detectors is being pursued. In particular, it is foreseen to replace the Inner Tracking System (ITS) by a new detector which will significantly improve the tracking and vertexing capabilities of ALICE in the upgrade scenario. The new ITS will have a barrel geometry consisting of seven layers of Monolithic Active Pixel Sensors (MAPS) with high granularity, which will fulfil the material budget, readout and radiation hardness requirements for the upgrade. Intensive R&D has been carried out in the last four years on MAPS in the framework of the ALICE ITS upgrade. Various small scale sensors have been designed in the TowerJazz 0.18 um imaging sensor technology to study noise, charge collection efficiency and signal-­‐to-­‐noise ratio. This work presents the main characterization results obtained from the measurements performed on two small scale prototypes (MIMOSA-­‐32 and MIMOSA-­‐32ter) with X-­‐ray sources and beams of particles. The architecture of an innovative full scale MAPS prototype (Alice Pixel Detector, ALPIDE) is also presented that is based on an AC-­‐sensitive front end and on a hit-­‐ driven readout. The first results on the ALPIDE prototype showed that the sensor is fully functional and that it provides performance in terms of readout time, power density and noise much better than the state of the art MAPS based on the rolling shutter readout, which makes this type of sensors very attractive for employment in the new ALICE ITS

    Quantum and spin-based tunneling devices for memory systems

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    Rapid developments in information technology, such as internet, portable computing, and wireless communication, create a huge demand for fast and reliable ways to store and process information. Thus far, this need has been paralleled with the revolution in solid-state memory technologies. Memory devices, such as SRAM, DRAM, and flash, have been widely used in most electronic products. The primary strategy to keep up the trend is miniaturization. CMOS devices have been scaled down beyond sub-45 nm, the size of only a few atomic layers. Scaling, however, will soon reach the physical limitation of the material and cease to yield the desired enhancement in device performance. In this thesis, an alternative method to scaling is proposed and successfully realized. The proposed scheme integrates quantum devices, Si/SiGe resonant interband tunnel diodes (RITD), with classical CMOS devices forming a microsystem of disparate devices to achieve higher performance as well as higher density. The device/circuit designs, layouts and masks involving 12 levels were fabricated utilizing a process that incorporates nearly a hundred processing steps. Utilizing unique characteristics of each component, a low-power tunneling-based static random access memory (TSRAM) has been demonstrated. The TSRAM cells exhibit bistability operation with a power supply voltage as low as 0.37 V. Various TSRAM cells were also constructed and their latching mechanisms have been extensively investigated. In addition, the operation margins of TSRAM cells are evaluated based on different device structures and temperature variation from room temperature up to 200oC. The versatility of TSRAM is extended beyond the binary system. Using multi-peak Si/SiGe RITD, various multi-valued TSRAM (MV-TSRAM) configurations that can store more than two logic levels per cell are demonstrated. By this virtue, memory density can be substantially increased. Using two novel methods via ambipolar operation and utilization of enable/disable transistors, a six-valued MV-TSRAM cell are demonstrated. A revolutionary novel concept of integrating of Si/SiGe RITD with spin tunnel devices, magnetic tunnel junctions (MTJ), has been developed. This hybrid approach adds non-volatility and multi-valued memory potential as demonstrated by theoretical predictions and simulations. The challenges of physically fabricating these devices have been identified. These include process compatibility and device design. A test bed approach of fabricating RITD-MTJ structures has been developed. In conclusion, this body of work has created a sound foundation for new research frontiers in four different major areas: integrated TSRAM system, MV-TSRAM system, MTJ/RITD-based nonvolatile MRAM, and RITD/CMOS logic circuits

    AES-EPO study program, volume II Final study report

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    Packaging, machine organization, error detection, and fabrication and test in determining solution to long-term and time-critical reliability of Apollo command module guidance-control compute

    Nanoscale Memristive Devices for Memory and Logic Applications.

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    As the building block of semiconductor electronics, field effect transistor (FET), approaches the sub 100 nm regime, a number of fundamental and practical issues start to emerge such as short channel effects that prevent the FET from operating properly and sub-threshold slope non-scaling that leads to increased power dissipation. In terms of nonvolatile memory, it is generally believed that transistor based Flash memory will approach the end of scaling within about a decade. As a result, novel, non-FET based devices and architectures will likely be needed to satisfy the growing demands for high performance memory and logic electronics applications. In this thesis, we present studies on nanoscale resistance switching devices (memristive devices). The device shows excellent resistance switching properties such as fast switching time ( 10^6), good data retention (> 6 years) and programming endurance (> 10^5). The studies suggest that the nonvolatile resistance switching in a nanoscale a-Si resistive switch is caused by the formation of a single conductive filament within 10 nm range near the bottom electrode. New functionalities, such as multi-bit switching with partially formed filaments, can be obtained by controlling the resistance switching process through current programming. As digital memory devices, the devices are ideally suited in the crossbar architecture which offers ultra-high density and intrinsic defect tolerance capability. As an example, a high-density (2 Gbits/cm^2) 1kb crossbar memory was demonstrated with excellent uniformity, high yield (> 92%) and ON/OFF ratio (> 10^3), proving its promising aspects for memory and reconfigurable logic applications. Furthermore, we demonstrated that properly designed devices can exhibit controlled analog switching behavior and function as flux controlled memristor devices. The analog memristors can be used in biology-inspired neuromorphic circuits in which signal processing efficiency orders of magnitude higher than conventional digital computer systems can be reached. As a prototype illustration, we showed Spike Timing Dependent Plasticity (STDP), one of the key learning rules in biological system, can be realized by CMOS neurons and nanoscale memristor synapses.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/75835/1/josung_1.pd
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