High-Density Solid-State Memory Devices and Technologies

This Special Issue aims to examine high-density solid-state memory devices and technologies from various standpoints in an attempt to foster their continuous success in the future. Considering that broadening of the range of applications will likely offer different types of solid-state memories their chance in the spotlight, the Special Issue is not focused on a specific storage solution but rather embraces all the most relevant solid-state memory devices and technologies currently on stage. Even the subjects dealt with in this Special Issue are widespread, ranging from process and design issues/innovations to the experimental and theoretical analysis of the operation and from the performance and reliability of memory devices and arrays to the exploitation of solid-state memories to pursue new computing paradigms

Energy efficient core designs for upcoming process technologies

Energy efficiency has been a first order constraint in the design of micro processors for the last decade. As Moore's law sunsets, new technologies are being actively explored to extend the march in increasing the computational power and efficiency. It is essential for computer architects to understand the opportunities and challenges in utilizing the upcoming process technology trends in order to design the most efficient processors. In this work, we consider three process technology trends and propose core designs that are best suited for each of the technologies. The process technologies are expected to be viable over a span of timelines. We first consider the most popular method currently available to improve the energy efficiency, i.e. by lowering the operating voltage. We make key observations regarding the limiting factors in scaling down the operating voltage for general purpose high performance processors. Later, we propose our novel core design, ScalCore, one that can work in high performance mode at nominal Vdd, and in a very energy-efficient mode at low Vdd. The resulting core design can operate at much lower voltages providing higher parallel performance while consuming lower energy. While lowering Vdd improves the energy efficiency, CMOS devices are fundamentally limited in their low voltage operation. Therefore, we next consider an upcoming device technology -- Tunneling Field-Effect Transistors (TFETs), that is expected to supplement CMOS device technology in the near future. TFETs can attain much higher energy efficiency than CMOS at low voltages. However, their performance saturates at high voltages and, therefore, cannot entirely replace CMOS when high performance is needed. Ideally, we desire a core that is as energy-efficient as TFET and provides as much performance as CMOS. To reach this goal, we characterize the TFET device behavior for core design and judiciously integrate TFET units, CMOS units in a single core. The resulting core, called HetCore, can provide very high energy efficiency while limiting the slowdown when compared to a CMOS core. Finally, we analyze Monolithic 3D (M3D) integration technology that is widely considered to be the only way to integrate more transistors on a chip. We present the first analysis of the architectural implications of using M3D for core design and show how to partition the core across different layers. We also address one of the key challenges in realizing the technology, namely, the top layer performance degradation. We propose a critical path based partitioning for logic stages and asymmetric bit/port partitioning for storage stages. The result is a core that performs nearly as well as a core without any top layer slowdown. When compared to a 2D baseline design, an M3D core not only provides much higher performance, it also reduces the energy consumption at the same time. In summary, this thesis addresses one of the fundamental challenges in computer architecture -- overcoming the fact that CMOS is not scaling anymore. As we increase the computing power on a single chip, our ability to power the entire chip keeps decreasing. This thesis proposes three solutions aimed at solving this problem over different timelines. Across all our solutions, we improve energy efficiency without compromising the performance of the core. As a result, we are able to operate twice as many cores with in the same power budget as regular cores, significantly alleviating the problem of dark silicon

High Peformance and Low Power On-Die Interconnect Fabrics.

Increasing power density with technology scaling has caused stagnation in operating frequency of modern day microprocessors. This has led designers to prefer multicore architectures over complex monolithic processors to keep up with the demand for rising computing throughput. Although processing units are getting smaller and simpler, the dramatic rise of their count on a single die has made the fabric that connects these processing units increasingly complex. These interconnect fabrics have become a bottleneck in improving overall system effciency. As a result, the design paradigm for multi-core chips is gradually shifting from a core-centric architecture towards an interconnect-centric architecture, where system efficiency is limited by the fabric rather than the processing ability of any individual core. This dissertation introduces three novel and synergistic circuit techniques to improve scalability of switch fabrics to make on-die integration of hundreds to thousands of cores feasible. 1) A matrix topology is proposed for designing a fully connected switch fabric that re-uses output buses for programming, and stores shue congurations at cross points. This significantly reduces routing congestion, lowers area/power, and improves per- formance. Silicon measurements demonstrate 47% energy savings in a 64-lane SIMD processor fabricated in 65nm CMOS over a conventional implementation. 2) A novel approach to handle high radix arbitration along with data routing is proposed. It optimally uses existing cross-bar interconnect resources without requiring any additional overhead. Bandwidth exceeding 2Tb/s is recorded in a test prototype fabricated in 65nm. 3) Building on the later, a new circuit topology to manage and update priority adaptively within the switch fabric without incurring additional delay or area is then proposed. Several assist circuit techniques, such as a thyristor based sense amplifier and self regenerating bi-directional repeaters are proposed for high speed energy efficient signaling to and from the switch fabric to improve overall routing efficiency. Using these techniques a 64 x 64 switch fabric with 128b data bus fabricated in 45nm achieves a throughput of 4.5Tb/s at single cycle latency while operating at 559MHz.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91506/1/sudhirks_1.pd

Memory Hierarchy Design for Next Generation Scalable Many-core Platforms

Performance and energy consumption in modern computing platforms is largely dominated by the memory hierarchy. The increasing computational power in the multiprocessors and accelerators, and the emergence of the data-intensive workloads (e.g. large-scale graph traversal and scientific algorithms) requiring fast transfer of large volumes of data, are two main trends which intensify this problem by putting even higher pressure on the memory hierarchy. This increasing gap between computation speed and data transfer speed is commonly referred as the “memory wall” problem. With the emergence of heterogeneous Three Dimensional (3D) Integration based on through-silicon-vias (TSV), this situation has started to recover in the past years. On one hand, it is now possible to improve memory access bandwidth and/or latency by either stacking memories directly on top of processors or through abstracted memory interfaces such as Micron’s Hybrid Memory Cube (HMC). On the other hand, near memory computation has become worthy of revisiting due to the cost-effective integration of logic and memory in 3D stacks. These two directions bring about several interesting opportunities including performance improvement, energy and cost reduction, product miniaturization, and modular design for improved time to market. In this research, we study the effectiveness of the 3D integration technology and the optimization opportunities which it can provide in the different layers of the memory hierarchy in cluster-based many-core platforms ranging from intra-cluster L1 to inter-cluster L2 scratchpad memories (SPMs), as well as the main memory. In addition, by moving a part of the computation to where data resides, in the 3D-stacked memory context, we demonstrate further energy and performance improvement opportunities

Design of Optical Interconnect Transceiver Circuits and Network-on-chip Architectures for Inter- and Intra-chip Communication

The rapid expansion in data communication due to the increased multimedia applications and cloud computing services necessitates improvements in optical transceiver circuitry power efficiency as these systems scale well past 10 Gb/s. In order to meet these requirements, a 26 GHz transimpedance amplifier (TIA) is presented in a 0.25-µm SiGe BiCMOS technology. It employs a transformer-based regulated cascode (RGC) input stage which provides passive negative-feedback gain that enhances the effective transconductance of the TIA’s input common-base transistor; reducing the input resistance and pro- viding considerable bandwidth extension without significant noise degradation or power consumption. The TIA achieves a 53 dBΩ single-ended transimpedance gain with a 26√ GHz bandwidth and 21.3 pA/H z average input-referred noise current spectral density. Total chip power including output buffering is 28.2 mW from a 2.5 V supply, with the core TIA consuming 8.2 mW, and the chip area including pads is 960 µm × 780 µm. With the advance of photonic devices, optical interconnects becomes a promising technology to replace the conventional electrical channels for the high-bandwidth and power efficient inter/intra-chip interconnect. Second, a silicon photonic transceiver is presented for a silicon ring resonator-based optical interconnect architecture in a 1V standard 65nm CMOS technology. The transmitter circuits incorporate high-swing drivers with non-linear pre-emphasis and automatic bias-based tuning for resonance wavelength stabilization. An optical forwarded-clock adaptive inverter-based transimpedance amplifier (TIA) receiver trades-off power for varying link budgets by employing an on-die eye monitor and scaling the TIA supply for the required sensitivity. At 5 GB/s operation, the ring modulator un- der 4Vpp driver achieves 12.7dB extinction ratio with 4.04mW power consumption, while a 0.28nm tuning range is obtained at 6.8µW/GHz efficiency with the bias-based tuning scheme implemented with the 2Vpp transmitter. When tested with a wire-bonded 150f- F p-i-n photodetector, the receiver achieves -12.7dBm sensitivity at a BER=10−15 and consumes 2.2mW at 8 GB/s. Third, a novel Nano-Photonic Network-on-Chip (NoC) architecture, called LumiNoC, is proposed for high performance and power-efficient interconnects for the chip-multi- processors (CMPs). A 64-node LumiNoC under synthetic traffic enjoys 50% less latency at low loads versus other reported photonic NoCs, and ∼25% less latency versus the electrical 2D mesh NoCs on realistic workloads. Under the same ideal throughput, LumiNoC achieves laser power reduction of 78%, and overall power reduction of 44% versus competing designs

Embedded dynamic programming networks for networks-on-chip

PhD ThesisRelentless technology downscaling and recent technological advancements in three dimensional integrated circuit (3D-IC) provide a promising prospect to realize heterogeneous system-on-chip (SoC) and homogeneous chip multiprocessor (CMP) based on the networks-onchip (NoCs) paradigm with augmented scalability, modularity and performance. In many cases in such systems, scheduling and managing communication resources are the major design and implementation challenges instead of the computing resources. Past research efforts were mainly focused on complex design-time or simple heuristic run-time approaches to deal with the on-chip network resource management with only local or partial information about the network. This could yield poor communication resource utilizations and amortize the benefits of the emerging technologies and design methods. Thus, the provision for efficient run-time resource management in large-scale on-chip systems becomes critical. This thesis proposes a design methodology for a novel run-time resource management infrastructure that can be realized efficiently using a distributed architecture, which closely couples with the distributed NoC infrastructure. The proposed infrastructure exploits the global information and status of the network to optimize and manage the on-chip communication resources at run-time. There are four major contributions in this thesis. First, it presents a novel deadlock detection method that utilizes run-time transitive closure (TC) computation to discover the existence of deadlock-equivalence sets, which imply loops of requests in NoCs. This detection scheme, TC-network, guarantees the discovery of all true-deadlocks without false alarms in contrast to state-of-the-art approximation and heuristic approaches. Second, it investigates the advantages of implementing future on-chip systems using three dimensional (3D) integration and presents the design, fabrication and testing results of a TC-network implemented in a fully stacked three-layer 3D architecture using a through-silicon via (TSV) complementary metal-oxide semiconductor (CMOS) technology. Testing results demonstrate the effectiveness of such a TC-network for deadlock detection with minimal computational delay in a large-scale network. Third, it introduces an adaptive strategy to effectively diffuse heat throughout the three dimensional network-on-chip (3D-NoC) geometry. This strategy employs a dynamic programming technique to select and optimize the direction of data manoeuvre in NoC. It leads to a tool, which is based on the accurate HotSpot thermal model and SystemC cycle accurate model, to simulate the thermal system and evaluate the proposed approach. Fourth, it presents a new dynamic programming-based run-time thermal management (DPRTM) system, including reactive and proactive schemes, to effectively diffuse heat throughout NoC-based CMPs by routing packets through the coolest paths, when the temperature does not exceed chip’s thermal limit. When the thermal limit is exceeded, throttling is employed to mitigate heat in the chip and DPRTM changes its course to avoid throttled paths and to minimize the impact of throttling on chip performance. This thesis enables a new avenue to explore a novel run-time resource management infrastructure for NoCs, in which new methodologies and concepts are proposed to enhance the on-chip networks for future large-scale 3D integration.Iraqi Ministry of Higher Education and Scientific Research (MOHESR)

Low Power Analog to Digital Converters in Advanced CMOS Technology Nodes

The dissertation presents system and circuit solutions to improve the power efficiency and address high-speed design issues of ADCs in advanced CMOS technologies. For image sensor applications, a high-performance digitizer prototype based on column-parallel single-slope ADC (SS-ADC) topology for readout of a back-illuminated 3D-stacked CMOS image sensor is presented. To address the high power consumption issue in high-speed digital counters, a passing window (PW) based hybrid counter topology is proposed. To address the high column FPN under bright illumination conditions, a double auto-zeroing (AZ) scheme is proposed. The proposed techniques are experimentally verified in a prototype chip designed and fabricated in the TSMC 40 nm low-power CMOS process. The PW technique saves 52.8% of power consumption in the hybrid digital counters. Dark/bright column fixed pattern noise (FPN) of 0.0024%/0.028% is achieved employing the proposed double AZ technique for digital correlated double sampling (CDS). A single-column digitizer consumes total power of 66.8μW and occupies an area of 5.4 µm x 610 µm. For mobile/wireless receiver applications, this dissertation presents a low-power wide-bandwidth multistage noise-shaping (MASH) continuous-time delta-sigma modulator (CT-ΔΣM) employing finite impulse response (FIR) digital-to-analog converters (DACs) and encoder-embedded loop-unrolling (EELU) quantizers. The proposed MASH 1-1-1 topology is a cascade of three single-loop first-order CT-ΔΣM stages, each of which consists of an active-RC integrator, a current-steering DAC, and an EELU quantizer. An FIR filter in the main 1.5-bit DAC improves the modulator’s jitter sensitivity performance. FIR’s effect on the noise transfer function (NTF) of the modulator is compensated in the digital domain thanks to the MASH topology. Instead of employing a conventional analog direct feedback path, a 1.5-bit EELU quantizer based on multiplexing comparator outputs is proposed; this approach is suitable for highspeed operation together with power and area benefits. Fabricated in a 40-nm low-power CMOS technology, the modulator’s prototype achieves a 67.3 dB of signal-to-noise and distortion ratio (SNDR), 68 dB of signal-to-noise ratio (SNR), and 68.2 dB of dynamic range (DR) within 50.5 MHz of bandwidth (BW), while consuming 19 mW of total power (P). The proposed modulator features 161.5 dB of figure-of-merit (FOM), defined as FOM = SNDR + 10 log10 (BW/P)

Low Power Memory/Memristor Devices and Systems

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