Power Efficient Data-Aware SRAM Cell for SRAM-Based FPGA Architecture

The design of low-power SRAM cell becomes a necessity in today\u27s FPGAs, because SRAM is a critical component in FPGA design and consumes a large fraction of the total power. The present chapter provides an overview of various factors responsible for power consumption in FPGA and discusses the design techniques of low-power SRAM-based FPGA at system level, device level, and architecture levels. Finally, the chapter proposes a data-aware dynamic SRAM cell to control the power consumption in the cell. Stack effect has been adopted in the design to reduce the leakage current. The various peripheral circuits like address decoder circuit, write/read enable circuits, and sense amplifier have been modified to implement a power-efficient SRAM-based FPGA

A 28-nm 32Kb SRAM For Low-VMIN Applications Using Write and Read Assist Techniques

In this paper new write and read assist techniques, reduced coupling signal negative bitline (RCS-NBL) and low power disturbance noise reduction (LP-DNR) of 6T static random-access memory (SRAM) to improve its minimal supply voltage (VMIN), have been presented. To observe the improvements in VMIN and power consumption of SRAM with the help of proposed assist techniques, a 32 Kb capacity SRAM, with 128 words of 256 bits width, is designed and simulated in 28-nm bulk CMOS technology. New RCS-NBL scheme, shows an improvement in SRAM write VMIN by 295 mV and also reduces overstress on pass transistor (PG) of the selected bitcell by 40 mV. Proposed LP-DNR scheme demonstrates an improvement in SRAM read VMIN by 35 mV and also shows a saving of the power loss in the existing DNR scheme during the read access which occurs due to continuous flow of current from the cross coupled latch to the discharge block path after the bitlines have settled. The static power consumption of this SRAM macro is improved by 48.9 % and 11.7 % while dynamic power by 91.7 % and 8.1 % with the help of proposed write and read assist techniques respectively. Area overheads of these proposed RCS-NBL and LP-DNR assist techniques for this macro are less than 0.79 % and 3.70 % respectively

Robust Circuit Design for Low-Voltage VLSI.

Voltage scaling is an effective way to reduce the overall power consumption, but the major challenges in low voltage operations include performance degradation and reliability issues due to PVT variations. This dissertation discusses three key circuit components that are critical in low-voltage VLSI. Level converters must be a reliable interface between two voltage domains, but the reduced on/off-current ratio makes it extremely difficult to achieve robust conversions at low voltages. Two static designs are proposed: LC2 adopts a novel pulsed-operation and modulates its pull-up strength depending on its state. A 3-sigma robustness is guaranteed using a current margin plot; SLC inherently reduces the contention by diode-insertion. Improvements in performance, power, and robustness are measured from 130nm CMOS test chips. SRAM is a major bottleneck in voltage-scaling due to its inherent ratioed-bitcell design. The proposed 7T SRAM alleviates the area overhead incurred by 8T bitcells and provides robust operation down to 0.32V in 180nm CMOS test chips with 3.35fW/bit leakage. Auto-Shut-Off provides a 6.8x READ energy reduction, and its innate Quasi-Static READ has been demonstrated which shows a much improved READ error rate. A use of PMOS Pass-Gate improves the half-select robustness by directly modulating the device strength through bitline voltage. Clocked sequential elements, flip-flops in short, are ubiquitous in today’s digital systems. The proposed S2CFF is static, single-phase, contention-free, and has the same number of devices as in TGFF. It shows a 40% power reduction as well as robust low-voltage operations in fabricated 45nm SOI test chips. Its simple hold-time path and the 3.4x improvement in 3-sigma hold-time is presented. A new on-chip flip-flop testing harness is also proposed, and measured hold-time variations of flip-flops are presented.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111525/1/yejoong_1.pd

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- II 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

Low-power and high-performance SRAM design in high variability advanced CMOS technology

As process technologies shrink, the size and number of memories on a chip are exponentially increasing. Embedded SRAMs are a critical component in modern digital systems, and they strongly impact the overall power, performance, and area. To promote memory-related research in academia, this dissertation introduces OpenRAM, a flexible, portable and open-source memory compiler and characterization methodology for generating and verifying memory designs across different technologies.In addition, SRAM designs, focusing on improving power consumption, access time and bitcell stability are explored in high variability advanced CMOS technologies. To have a stable read/write operation for SRAM in high variability process nodes, a differential-ended single-port 8T bitcell is proposed that improves the read noise margin, write noise margin and readout bitcell current by 45%, 48% and 21%, respectively, compared to a conventional 6T bitcell. Also, a differential-ended single-port 12T bitcell for subthreshold operation is proposed that solves the half-select disturbance and allows efficient bit-interleaving. 12T bitcell has a leakage control mechanism which helps to reduce the power consumption and provides operation down to 0.3 V. Both 8T and 12T bitcells are analyzed in a 64 kb SRAM array using 32 nm technology. Besides, to further improve the access time and power consumption, two tracking circuits (multi replica bitline delay and reconfigurable replica bitline delay techniques) are proposed to aid the generation of accurate and optimum sense amplifier set time.An error tolerant SRAM architecture suitable for low voltage video application with dynamic power-quality management is also proposed in this dissertation. This memory uses three power supplies to improve the SRAM stability in low voltages. The proposed triple-supply approach achieves 63% improvement in image quality and 69% reduction in power consumption compared to a single-supply 64 kb SRAM array at 0.70 V

Improved Fault Tolerant SRAM Cell Design & Layout in 130nm Technology

Technology scaling of CMOS devices has made the integrated circuits vulnerable to single event radiation effects. Scaling of CMOS Static RAM (SRAM) has led to denser packing architectures by reducing the size and spacing of diffusion nodes. However, this trend has led to the increase in charge collection and sharing effects between devices during an ion strike, making the circuit even more vulnerable to a specific single event effect called the single event multiple-node upset (SEMU). In nanometer technologies, SEMU can easily disrupt the data stored in the memory and can be more hazardous than a single event single-node upset. During the last decade, most of the research efforts were mainly focused on improving the single event single-node upset tolerance of SRAM cells by using novel circuit techniques, but recent studies relating to angular radiation sensitivity has revealed the importance of SEMU and Multi Bit Upset (MBU) tolerance for SRAM cells. The research focuses on improving SEMU tolerance of CMOS SRAM cells by using novel circuit and layout level techniques. A novel SRAM cell circuit & layout technique is proposed to improve the SEMU tolerance of 6T SRAM cells with decreasing feature size, making it an ideal candidate for future technologies. The layout is based on strategically positioning diffusion nodes in such a way as to provide charge cancellation among nodes during SEMU radiation strikes, instead of charge build-up. The new design & layout technique can improve the SEMU tolerance levels by up to 20 times without sacrificing on area overhead and hence is suitable for high density SRAM designs in commercial applications. Finally, laser testing of SRAM based configuration memory of a Xilinx Virtex-5 FPGA is performed to analyze the behavior of SRAM based systems towards radiation strikes

Low-Power Soft-Error-Robust Embedded SRAM

Soft errors are radiation-induced ionization events (induced by energetic particles like alpha particles, cosmic neutron, etc.) that cause transient errors in integrated circuits. The circuit can always recover from such errors as the underlying semiconductor material is not damaged and hence, they are called soft errors. In nanometer technologies, the reduced node capacitance and supply voltage coupled with high packing density and lack of masking mechanisms are primarily responsible for the increased susceptibility of SRAMs towards soft errors. Coupled with these are the process variations (effective length, width, and threshold voltage), which are prominent in scaled-down technologies. Typically, SRAM constitutes up to 90% of the die in microprocessors and SoCs (System-on-Chip). Hence, the soft errors in SRAMs pose a potential threat to the reliable operation of the system. In this work, a soft-error-robust eight-transistor SRAM cell (8T) is proposed to establish a balance between low power consumption and soft error robustness. Using metrics like access time, leakage power, and sensitivity to single event transients (SET), the proposed approach is evaluated. For the purpose of analysis and comparisons the results of 8T cell are compared with a standard 6T SRAM cell and the state-of-the-art soft-error-robust SRAM cells. Based on simulation results in a 65-nm commercial CMOS process, the 8T cell demonstrates higher immunity to SETs along with smaller area and comparable leakage power. A 32-kb array of 8T cells was fabricated in silicon. After functional verification of the test chip, a radiation test was conducted to evaluate the soft error robustness. As SRAM cells are scaled aggressively to increase the overall packing density, the smaller transistors exhibit higher degrees of process variation and mismatch, leading to larger offset voltages. For SRAM sense amplifiers, higher offset voltages lead to an increased likelihood of an incorrect decision. To address this issue, a sense amplifier capable of cancelling the input offset voltage is presented. The simulated and measured results in 180-nm technology show that the sense amplifier is capable of detecting a 4 mV differential input signal under dc and transient conditions. The proposed sense amplifier, when compared with a conventional sense amplifier, has a similar die area and a greatly reduced offset voltage. Additionally, a dual-input sense amplifier architecture is proposed with corroborating silicon results to show that it requires smaller differential input to evaluate correctly.1 yea

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

Exploiting Natural On-chip Redundancy for Energy Efficient Memory and Computing

Power density is currently the primary design constraint across most computing segments and the main performance limiting factor. For years, industry has kept power density constant, while increasing frequency, lowering transistors supply (Vdd) and threshold (Vth) voltages. However, Vth scaling has stopped because leakage current is exponentially related to it. Transistor count and integration density keep doubling every process generation (Moore’s Law), but the power budget caps the amount of hardware that can be active at the same time, leading to dark silicon. With each new generation, there are more resources available, but we cannot fully exploit their performance potential. In the last years, different research trends have explored how to cope with dark silicon and unlock the energy efficiency of the chips, including Near-Threshold voltage Computing (NTC) and approximate computing. NTC aggressively lowers Vdd to values near Vth. This allows a substantial reduction in power, as dynamic power scales quadratically with supply voltage. The resultant power reduction could be used to activate more chip resources and potentially achieve performance improvements. Unfortunately, Vdd scaling is limited by the tight functionality margins of on-chip SRAM transistors. When scaling Vdd down to values near-threshold, manufacture-induced parameter variations affect the functionality of SRAM cells, which eventually become not reliable. A large amount of emerging applications, on the other hand, features an intrinsic error-resilience property, tolerating a certain amount of noise. In this context, approximate computing takes advantage of this observation and exploits the gap between the level of accuracy required by the application and the level of accuracy given by the computation, providing that reducing the accuracy translates into an energy gain. However, deciding which instructions and data and which techniques are best suited for approximation still poses a major challenge. This dissertation contributes in these two directions. First, it proposes a new approach to mitigate the impact of SRAM failures due to parameter variation for effective operation at ultra-low voltages. We identify two levels of natural on-chip redundancy: cache level and content level. The first arises because of the replication of blocks in multi-level cache hierarchies. We exploit this redundancy with a cache management policy that allocates blocks to entries taking into account the nature of the cache entry and the use pattern of the block. This policy obtains performance improvements between 2% and 34%, with respect to block disabling, a technique with similar complexity, incurring no additional storage overhead. The latter (content level redundancy) arises because of the redundancy of data in real world applications. We exploit this redundancy compressing cache blocks to fit them in partially functional cache entries. At the cost of a slight overhead increase, we can obtain performance within 2% of that obtained when the cache is built with fault-free cells, even if more than 90% of the cache entries have at least a faulty cell. Then, we analyze how the intrinsic noise tolerance of emerging applications can be exploited to design an approximate Instruction Set Architecture (ISA). Exploiting the ISA redundancy, we explore a set of techniques to approximate the execution of instructions across a set of emerging applications, pointing out the potential of reducing the complexity of the ISA, and the trade-offs of the approach. In a proof-of-concept implementation, the ISA is shrunk in two dimensions: Breadth (i.e., simplifying instructions) and Depth (i.e., dropping instructions). This proof-of-concept shows that energy can be reduced on average 20.6% at around 14.9% accuracy loss

Design, implementation and testing of SRAM based neutron detectors

Neutrons of thermal and high energies can change the value of a bit stored in a Static Random Access Memory (SRAM) memory chip. The effect is non destructive and linearly dependent on the amount of incoming particles, which makes it exploitable for use as a neutron detector. Detection is done by writing a known pattern to the memory and continuously reading it back checking for wrong values. As the SRAM memory is immune to gamma radiation it is ideal for use in for instance medical linear accelerators for detection of neutron dose to a patient. The intention of this work has been twofold: (1) Testing of different SRAM devices of different bit-sizes, manufacturers, feature sizes and voltages for their sensitivity to neutrons of different energies from thermal to high energies. (2) Design and implement detector hardware, firmware and its accompanying readout system for successful use in irradiation testing. The work has been done in close collaboration with Eivind Larsen, whose main contributions has been related to the nuclear physics aspect of the work in addition to arrangements in regard to beam setup and experimentation. Testing have been done at the Physikalisch-Technische Bundesanstalt (PTB) facility in Braunschweig Germany in a quasi-monochromatic neutron beam of 5:8MeV, 8:5MeV and 14:8MeV, finding a dependence of the sensitivity on the energy. In addition there have been testing conducted in the high energy hadron field at CERF at CERN, finding that by using the results from the other experiments an estimated range of the saturation cross section could be determined. Testing was also conducted at two occasions in the 29MeV proton beam at Oslo Cyclotron Laboratory (OCL) in Oslo Norway, where it was found that the detector could be used as a reference detector for beam monitoring and for beam profile characterization. The cross sections of the detectors were found to be comparable to the 14:8MeV cross section found at PTB. Thermal neutron testing of the devices was done in the thermal neutron field of the nuclear reactor at Institute for Energy Technology (IFE) at Kjeller Norway. All the devices were found to be sensitive to the field. Detector electronics, adapted to the different devices, has been built which can withstand the same radiation as the memory device without malfunctioning. There has been a focus on using Commercial Off The Shelf (COTS) components for reducing the total cost of the detector to about 100-200$US. The use of COTS SRAM memory devices also simplifies the reproducibility and availability of spares. The detector currently uses a two way communication between the detector and iv Abstract the readout computer over two pair of cables reducing the amount of cabling needed for experiments. The detectors can be connected to the communication link in a bus fashion, currently enabling a total of 14 detectors to be tested simultaneously from 100m away, over the same cable. Single Event Latch-up (SEL) and problems with irregular count rate of SRAMs created in the 90nm fabrication node has created problems during testing. Some solutions and techniques to mitigate these in hardware and firmware are presented in this work.Master i FysikkMAMN-PHYSPHYS39