11 research outputs found
System-Scenario Methodology to Design a Highly Reliable Radiation-Hardened Memory for Space Applications
Cache memory circuits are one of the concerns of computing systems, especially in terms of power consumption, reliability, and high performance. Voltage-scaling techniques can be used to reduce the total power consumption of the caches. However, aggressive voltage scaling significantly increases the probability of memory failure, especially in environments with high radiation levels, such as space. It is, therefore, important to deploy techniques to deal with reliability issues along with voltage scaling. In this chapter, we present a system-scenario methodology for radiation-hardened memory design to keep the reliability during voltage scaling. Although any SRAM array can benefit from the design, we frame our study on the recently proposed radiation-hardened cell, Nwise, which provides high level of tolerance against single event and multi event upsets in memories. To reduce the power consumption while upholding reliability, we leverage the system-scenario-based design methodology to optimize the energy consumption in applications, where system requirements vary dynamically at run time. We demonstrate the use of the methodology with a use case related to satellite systems and solar activity. Our simulations show that we achieve up to 49.3% power consumption saving compared to using a cache design with a fixed nominal power supply level
Highly Reliable Quadruple-Node Upset-Tolerant D-Latch
This work was supported in part by the Spanish MCIN/AEI /10.13039/501100011033/ FEDER under Grant PID2020-117344RB-I00, and
in part by the Regional Government under Grant P20_00265 and Grant P20_00633.As CMOS technology scaling pushes towards the reduction of the length of transistors,
electronic circuits face numerous reliability issues, and in particular nodes of D-latches at nano-scale confront
multiple-node upset errors due to their operation in harsh radiative environments. In this manuscript, a new
high reliable D-latch which can tolerate quadruple-node upsets is presented. The design is based on a low-cost
single event double-upset tolerant (LSEDUT) cell and a clock-gating triple-level soft-error interceptive
module (CG-SIM). Due to its LSEDUT base, it can tolerate two upsets, but the combination of two LSEDUTs
and the triple-level CG-SIM provides the proposed D-latch with remarkable quadruple-node upsets (QNU)
tolerance. Applying LSEDUTs for designing a QNU-tolerant D-latch improves considerably its features;
in particular, this approach enhances its reliability against process variations, such as threshold voltage and
(W/L) transistor variability, compared to previous QNU-tolerant D-latches and double-node-upset tolerant
latches. Furthermore, the proposed D-latch not only tolerates QNUs, but it also features a clear advantage
in comparison with the previous clock gating-based quadruple-node-upset-tolerant (QNUTL-CG) D-latch:
it can mask single event transients. Speci c gures of merit endorse the gains introduced by the new design:
compared with the QNUTL-CG D-latch, the improvements of the maximum standard deviations of the gate
delay, induced by threshold voltage and (W/L) transistors variability of the proposed D-latch, are 13.8%
and 5.7%, respectively. Also, the proposed D-latch has 23% lesser maximum standard deviation in power
consumption, resulting from threshold voltage variability, when compared to the QNUTL-CG D-latch.Spanish MCIN/AEI /10.13039/501100011033/ FEDER under Grant PID2020-117344RB-I00Regional Government under Grant P20_00265 and Grant P20_0063
Heterogeneous Reconfigurable Fabrics for In-circuit Training and Evaluation of Neuromorphic Architectures
A heterogeneous device technology reconfigurable logic fabric is proposed which leverages the cooperating advantages of distinct magnetic random access memory (MRAM)-based look-up tables (LUTs) to realize sequential logic circuits, along with conventional SRAM-based LUTs to realize combinational logic paths. The resulting Hybrid Spin/Charge FPGA (HSC-FPGA) using magnetic tunnel junction (MTJ) devices within this topology demonstrates commensurate reductions in area and power consumption over fabrics having LUTs constructed with either individual technology alone. Herein, a hierarchical top-down design approach is used to develop the HSCFPGA starting from the configurable logic block (CLB) and slice structures down to LUT circuits and the corresponding device fabrication paradigms. This facilitates a novel architectural approach to reduce leakage energy, minimize communication occurrence and energy cost by eliminating unnecessary data transfer, and support auto-tuning for resilience. Furthermore, HSC-FPGA enables new advantages of technology co-design which trades off alternative mappings between emerging devices and transistors at runtime by allowing dynamic remapping to adaptively leverage the intrinsic computing features of each device technology. HSC-FPGA offers a platform for fine-grained Logic-In-Memory architectures and runtime adaptive hardware. An orthogonal dimension of fabric heterogeneity is also non-determinism enabled by either low-voltage CMOS or probabilistic emerging devices. It can be realized using probabilistic devices within a reconfigurable network to blend deterministic and probabilistic computational models. Herein, consider the probabilistic spin logic p-bit device as a fabric element comprising a crossbar-structured weighted array. The Programmability of the resistive network interconnecting p-bit devices can be achieved by modifying the resistive states of the array\u27s weighted connections. Thus, the programmable weighted array forms a CLB-scale macro co-processing element with bitstream programmability. This allows field programmability for a wide range of classification problems and recognition tasks to allow fluid mappings of probabilistic and deterministic computing approaches. In particular, a Deep Belief Network (DBN) is implemented in the field using recurrent layers of co-processing elements to form an n x m1 x m2 x ::: x mi weighted array as a configurable hardware circuit with an n-input layer followed by i ≥ 1 hidden layers. As neuromorphic architectures using post-CMOS devices increase in capability and network size, the utility and benefits of reconfigurable fabrics of neuromorphic modules can be anticipated to continue to accelerate
Microarchitectural Low-Power Design Techniques for Embedded Microprocessors
With the omnipresence of embedded processing in all forms of electronics today, there is a strong trend towards wireless, battery-powered, portable embedded systems which have to operate under stringent energy constraints. Consequently, low power consumption and high energy efficiency have emerged as the two key criteria for embedded microprocessor design. In this thesis we present a range of microarchitectural low-power design techniques which enable the increase of performance for embedded microprocessors and/or the reduction of energy consumption, e.g., through voltage scaling. In the context of cryptographic applications, we explore the effectiveness of instruction set extensions (ISEs) for a range of different cryptographic hash functions (SHA-3 candidates) on a 16-bit microcontroller architecture (PIC24). Specifically, we demonstrate the effectiveness of light-weight ISEs based on lookup table integration and microcoded instructions using finite state machines for operand and address generation. On-node processing in autonomous wireless sensor node devices requires deeply embedded cores with extremely low power consumption. To address this need, we present TamaRISC, a custom-designed ISA with a corresponding ultra-low-power microarchitecture implementation. The TamaRISC architecture is employed in conjunction with an ISE and standard cell memories to design a sub-threshold capable processor system targeted at compressed sensing applications. We furthermore employ TamaRISC in a hybrid SIMD/MIMD multi-core architecture targeted at moderate to high processing requirements (> 1 MOPS). A range of different microarchitectural techniques for efficient memory organization are presented. Specifically, we introduce a configurable data memory mapping technique for private and shared access, as well as instruction broadcast together with synchronized code execution based on checkpointing. We then study an inherent suboptimality due to the worst-case design principle in synchronous circuits, and introduce the concept of dynamic timing margins. We show that dynamic timing margins exist in microprocessor circuits, and that these margins are to a large extent state-dependent and that they are correlated to the sequences of instruction types which are executed within the processor pipeline. To perform this analysis we propose a circuit/processor characterization flow and tool called dynamic timing analysis. Moreover, this flow is employed in order to devise a high-level instruction set simulation environment for impact-evaluation of timing errors on application performance. The presented approach improves the state of the art significantly in terms of simulation accuracy through the use of statistical fault injection. The dynamic timing margins in microprocessors are then systematically exploited for throughput improvements or energy reductions via our proposed instruction-based dynamic clock adjustment (DCA) technique. To this end, we introduce a 6-stage 32-bit microprocessor with cycle-by-cycle DCA. Besides a comprehensive design flow and simulation environment for evaluation of the DCA approach, we additionally present a silicon prototype of a DCA-enabled OpenRISC microarchitecture fabricated in 28 nm FD-SOI CMOS. The test chip includes a suitable clock generation unit which allows for cycle-by-cycle DCA over a wide range with fine granularity at frequencies exceeding 1 GHz. Measurement results of speedups and power reductions are provided
Self-healing concepts involving fine-grained redundancy for electronic systems
The start of the digital revolution came through the metal-oxide-semiconductor field-effect transistor (MOSFET) in 1959 followed by massive integration onto a silicon die by means of constant down scaling of individual components. Digital systems for certain applications require fault-tolerance against faults caused by temporary or permanent influence. The most widely used technique is triple module redundancy (TMR) in conjunction with a majority voter, which is regarded as a passive fault mitigation strategy. Design by functional resilience has been applied to circuit structures for increased fault-tolerance and towards self-diagnostic triggered self-healing. The focus of this thesis is therefore to develop new design strategies for fault detection and mitigation within transistor, gate and cell design levels.
The research described in this thesis makes three contributions. The first contribution is based on adding fine-grained transistor level redundancy to logic gates in order to accomplish stuck-at fault-tolerance. The objective is to realise maximum fault-masking for a logic gate with minimal added redundant transistors. In the case of non-maskable stuck-at faults, the gate structure generates an intrinsic indication signal that is suitable for autonomous self-healing functions. As a result, logic circuitry utilising this design is now able to differentiate between gate faults and faults occurring in inter-gate connections. This distinction between fault-types can then be used for triggering selective self-healing responses.
The second contribution is a logic matrix element which applies the three core redundancy concepts of spatial- temporal- and data-redundancy. This logic structure is composed of quad-modular redundant structures and is capable of selective fault-masking and localisation depending of fault-type at the cell level, which is referred to as a spatiotemporal quadded logic cell (QLC) structure. This QLC structure has the capability of cellular self-healing. Through the combination of fault-tolerant and masking logic features the QLC is designed with a fault-behaviour that is equal to existing quadded logic designs using only 33.3% of the equivalent transistor resources. The inherent self-diagnosing feature of QLC is capable of identifying individual faulty cells and can trigger self-healing features.
The final contribution is focused on the conversion of finite state machines (FSM) into memory to achieve better state transition timing, minimal memory utilisation and fault protection compared to common FSM designs. A novel implementation based on content-addressable type memory (CAM) is used to achieve this. The FSM is further enhanced by creating the design out of logic gates of the first contribution by achieving stuck-at fault resilience. Applying cross-data parity checking, the FSM becomes equipped with single bit fault detection and correction
Techniques for Aging, Soft Errors and Temperature to Increase the Reliability of Embedded On-Chip Systems
This thesis investigates the challenge of providing an abstracted, yet sufficiently accurate reliability estimation for embedded on-chip systems. In addition, it also proposes new techniques to increase the reliability of register files within processors against aging effects and soft errors. It also introduces a novel thermal measurement setup that perspicuously captures the infrared images of modern multi-core processors
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MANAGING AND LEVERAGING VARIATIONS AND NOISE IN NANOMETER CMOS
Advanced CMOS technologies have enabled high density designs at the cost of complex fabrication process. Variation in oxide thickness and Random Dopant Fluctuation (RDF) lead to variation in transistor threshold voltage Vth. Current photo-lithography process used for printing decreasing critical dimensions result in variation in transistor channel length and width. A related challenge in nanometer CMOS is that of on-chip random noise. With decreasing threshold voltage and operating voltage; and increasing operating temperature, CMOS devices are more sensitive to random on-chip noise in advanced technologies.
In this thesis, we explore novel circuit techniques to manage the impact of process variation in nanometer CMOS technologies. We also analyze the impact of on-chip noise on CMOS circuits and propose techniques to leverage or manage impact of noise based on the application. True Random Number Generator (TRNG) is an interesting cryptographic primitive that leverages on-chip noise to generate random bits; however, it is highly sensitive to process variation. We explore novel metastability circuits to alleviate the impact of variations and at the same time leverage on-chip noise sources like Random Thermal Noise and Random Telegraph Noise (RTN) to generate high quality random bits. We develop stochastic models for metastability based TRNG circuits to analyze the impact of variation and noise. The stochastic models are used to analyze and compare low power, energy efficient and lightweight post-processing techniques targeted to low power applications like System on Chip (SoC) and RFID. We also propose variation aware circuit calibration techniques to increase reliability. We extended this technique to a more generic application of designing Post-Si Tunable (PST) clock buffers to increase parametric yield in the presence of process variation. Apart from one time variation due to fabrication process, transistors undergo constant change in threshold voltage due to aging/wear-out effects and RTN. Process variation affects conventional sensors and introduces inaccuracies during measurement. We present a lightweight wear-out sensor that is tolerant to process variation and provides a fine grained wear-out sensing. A similar circuit is designed to sense fluctuation in transistor threshold voltage due to RTN. Although thermal noise and RTN are leveraged in applications like TRNG, they affect the stability of sensitive circuits like Static Random Access Memory (SRAM). We analyze the impact of on-chip noise on Bit Error Rate (BER) and post-Si test coverage of SRAM cells
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
Design and analysis of SRAMs for energy harvesting systems
PhD ThesisAt present, the battery is employed as a power source for wide varieties of microelectronic systems ranging from biomedical implants and sensor net-works to portable devices. However, the battery has several limitations and incurs many challenges for the majority of these systems. For instance, the design considerations of implantable devices concern about the battery from two aspects, the toxic materials it contains and its lifetime since replacing the battery means a surgical operation. Another challenge appears in wire-less sensor networks, where hundreds or thousands of nodes are scattered around the monitored environment and the battery of each node should be maintained and replaced regularly, nonetheless, the batteries in these nodes do not all run out at the same time.
Since the introduction of portable systems, the area of low power designs has witnessed extensive research, driven by the industrial needs, towards the aim of extending the lives of batteries. Coincidentally, the continuing innovations in the field of micro-generators made their outputs in the same range of several portable applications. This overlap creates a clear oppor-tunity to develop new generations of electronic systems that can be powered, or at least augmented, by energy harvesters. Such self-powered systems benefit applications where maintaining and replacing batteries are impossi-ble, inconvenient, costly, or hazardous, in addition to decreasing the adverse effects the battery has on the environment.
The main goal of this research study is to investigate energy harvesting aware design techniques for computational logic in order to enable the capa-
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bility of working under non-deterministic energy sources. As a case study, the research concentrates on a vital part of all computational loads, SRAM, which occupies more than 90% of the chip area according to the ITRS re-ports.
Essentially, this research conducted experiments to find out the design met-ric of an SRAM that is the most vulnerable to unpredictable energy sources, which has been confirmed to be the timing. Accordingly, the study proposed a truly self-timed SRAM that is realized based on complete handshaking protocols in the 6T bit-cell regulated by a fully Speed Independent (SI) tim-ing circuitry. The study proved the functionality of the proposed design in real silicon. Finally, the project enhanced other performance metrics of the self-timed SRAM concentrating on the bit-line length and the minimum operational voltage by employing several additional design techniques.Umm Al-Qura University, the Ministry of Higher Education in the Kingdom of Saudi Arabia, and the Saudi Cultural Burea
Robust Design of Variation-Sensitive Digital Circuits
The nano-age has already begun, where typical feature dimensions are smaller than 100nm. The operating frequency is expected to increase up to
12 GHz, and a single chip will contain over 12 billion transistors in 2020, as given by the International Technology Roadmap for Semiconductors
(ITRS) initiative. ITRS also predicts that the scaling of CMOS devices and process technology, as it is known today, will become much more
difficult as the industry advances towards the 16nm technology node and further. This aggressive scaling of CMOS technology has pushed the
devices to their physical limits. Design goals are governed by several factors other than power, performance and area such as process
variations, radiation induced soft errors, and aging degradation mechanisms. These new design challenges have a strong impact on the parametric
yield of nanometer digital circuits and also result in functional yield losses in variation-sensitive digital circuits such as Static Random
Access Memory (SRAM) and flip-flops. Moreover, sub-threshold SRAM and flip-flops circuits, which are aggravated by the strong demand for lower
power consumption, show larger sensitivity to these challenges which reduces their robustness and yield. Accordingly, it is not surprising that
the ITRS considers variability and reliability as the most challenging obstacles for nanometer digital circuits robust design.
Soft errors are considered one of the main reliability and robustness concerns in SRAM arrays in sub-100nm technologies due to low operating
voltage, small node capacitance, and high packing density. The SRAM arrays soft errors immunity is also affected by process variations. We
develop statistical design-oriented soft errors immunity variations models for super-threshold and sub-threshold SRAM cells accounting for
die-to-die variations and within-die variations. This work provides new design insights and highlights the important design knobs that can be
used to reduce the SRAM cells soft errors immunity variations. The developed models are scalable, bias dependent, and only require the
knowledge of easily measurable parameters. This makes them useful in early design exploration, circuit optimization as well as technology
prediction. The derived models are verified using Monte Carlo SPICE simulations, referring to an industrial hardware-calibrated 65nm CMOS
technology.
The demand for higher performance leads to very deep pipelining which means that hundreds of thousands of flip-flops are required to control
the data flow under strict timing constraints. A violation of the timing constraints at a flip-flop can result in latching incorrect data
causing the overall system to malfunction. In addition, the flip-flops power dissipation represents a considerable fraction of the total power
dissipation. Sub-threshold flip-flops are considered the most energy efficient solution for low power applications in which, performance is of
secondary importance. Accordingly, statistical gate sizing is conducted to different flip-flops topologies for timing yield improvement of
super-threshold flip-flops and power yield improvement of sub-threshold flip-flops. Following that, a comparative analysis between these
flip-flops topologies considering the required overhead for yield improvement is performed. This comparative analysis provides useful
recommendations that help flip-flops designers on selecting the best flip-flops topology that satisfies their system specifications while
taking the process variations impact and robustness requirements into account.
Adaptive Body Bias (ABB) allows the tuning of the transistor threshold voltage, Vt, by controlling the transistor body voltage. A forward
body bias reduces Vt, increasing the device speed at the expense of increased leakage power. Alternatively, a reverse body bias increases
Vt, reducing the leakage power but slowing the device. Therefore, the impact of process variations is mitigated by speeding up slow and
less leaky devices or slowing down devices that are fast and highly leaky. Practically, the implementation of the ABB is desirable to bias each
device in a design independently, to mitigate within-die variations. However, supplying so many separate voltages inside a die results in a
large area overhead. On the other hand, using the same body bias for all devices on the same die limits its capability to compensate for
within-die variations. Thus, the granularity level of the ABB scheme is a trade-off between the within-die variations compensation capability
and the associated area overhead. This work introduces new ABB circuits that exhibit lower area overhead by a factor of 143X than that of
previous ABB circuits. In addition, these ABB circuits are resolution free since no digital-to-analog converters or analog-to-digital
converters are required on their implementations. These ABB circuits are adopted to high performance critical paths, emulating a real
microprocessor architecture, for process variations compensation and also adopted to SRAM arrays, for Negative Bias Temperature Instability
(NBTI) aging and process variations compensation. The effectiveness of the new ABB circuits is verified by post layout simulation results and
test chip measurements using triple-well 65nm CMOS technology.
The highly capacitive nodes of wide fan-in dynamic circuits and SRAM bitlines limit the performance of these circuits. In addition, process
variations mitigation by statistical gate sizing increases this capacitance further and fails in achieving the target yield improvement. We
propose new negative capacitance circuits that reduce the overall parasitic capacitance of these highly capacitive nodes. These negative
capacitance circuits are adopted to wide fan-in dynamic circuits for timing yield improvement up to 99.87% and to SRAM arrays for read access
yield improvement up to 100%. The area and power overheads of these new negative capacitance circuits are amortized over the large die area of
the microprocessor and the SRAM array. The effectiveness of the new negative capacitance circuits is verified by post layout simulation results
and test chip measurements using 65nm CMOS technology