Delay Extraction Based Equivalent Elmore Model For RLC On-Chip Interconnects

As feature sizes for VLSI technology is shrinking, associated with higher operating frequency, signal integrity analysis of on-chip interconnects has become a real challenge for circuit designers. For this purpose, computer-aided-design (CAD) tools are necessary to simulate signal propagation of on-chip interconnects which has been an active area for research. Although SPICE models exist which can accurately predict signal degradation of interconnects, they are computationally expensive. As a result, more effective and analytic models for interconnects are required to capture the response at the output of high speed VLSI circuits. This thesis contributes to the development of efficient and closed form solution models for signal integrity analysis of on-chip interconnects. The proposed model uses a delay extraction algorithm to improve the accuracy of two-pole Elmore based models used in the analysis of on-chip distributed RLC interconnects. In the proposed scheme, the time of fight signal delay is extracted without increasing the number of poles or affecting the stability of the transfer function. This algorithm is used for both unit step and ramp inputs. From the delay rational approximation of the transfer function, analytic fitted expressions are obtained for the 50% delay and rise time for unit step input. The proposed algorithm is tested on point to point interconnections and tree structure networks. Numerical examples illustrate improved 50% delay and rise time estimates when compared to traditional Elmore based two-pole models

Modeling and Analysis of Noise and Interconnects for On-Chip Communication Link Design

This thesis considers modeling and analysis of noise and interconnects in onchip communication. Besides transistor count and speed, the capabilities of a modern design are often limited by on-chip communication links. These links typically consist of multiple interconnects that run parallel to each other for long distances between functional or memory blocks. Due to the scaling of technology, the interconnects have considerable electrical parasitics that affect their performance, power dissipation and signal integrity. Furthermore, because of electromagnetic coupling, the interconnects in the link need to be considered as an interacting group instead of as isolated signal paths. There is a need for accurate and computationally effective models in the early stages of the chip design process to assess or optimize issues affecting these interconnects. For this purpose, a set of analytical models is developed for on-chip data links in this thesis. First, a model is proposed for modeling crosstalk and intersymbol interference. The model takes into account the effects of inductance, initial states and bit sequences. Intersymbol interference is shown to affect crosstalk voltage and propagation delay depending on bus throughput and the amount of inductance. Next, a model is proposed for the switching current of a coupled bus. The model is combined with an existing model to evaluate power supply noise. The model is then applied to reduce both functional crosstalk and power supply noise caused by a bus as a trade-off with time. The proposed reduction method is shown to be effective in reducing long-range crosstalk noise. The effects of process variation on encoded signaling are then modeled. In encoded signaling, the input signals to a bus are encoded using additional signaling circuitry. The proposed model includes variation in both the signaling circuitry and in the wires to calculate the total delay variation of a bus. The model is applied to study level-encoded dual-rail and 1-of-4 signaling. In addition to regular voltage-mode and encoded voltage-mode signaling, current-mode signaling is a promising technique for global communication. A model for energy dissipation in RLC current-mode signaling is proposed in the thesis. The energy is derived separately for the driver, wire and receiver termination.Siirretty Doriast

A closed-form integration method for state-space time-domain analysis of electronic circuits and systems

While most traditional circuit simulation programs such as SPICE rely upon numerical integration techniques to perform transient analysis, this dissertation presents an alternative approach that relies on closed-form integration. Traditional numerical approaches offer no hope of finding an analytical solution, even if it is known that the solutions will be in a simple functional form. By using closed-form methods, the computer can find the exact analytical solution to the network and completely avoid problems associated with numerical approximations, determining appropriate integration step sizes, stiff systems of differential equations, or accumulated global error. Computer run time is independent of the amount of time simulated. The closed-form analysis program described in this paper constructs state equations from a SPICE-like input deck and solves the network by computing its eigenvalues. The program automatically separates out the complementary solution and the particular solution due to each input, combining them to produce the complete solution. The program can recursively handle hierarchically defined networks. With closed-form solutions, the design engineer can determine exponential decay rates, phase shifts, time delays and oscillation periods directly from the formulas rather than having to estimate them from an output plot. Resonance conditions and network instability are automatically detected by examining the eigenvalues. The design engineer may numerically evaluate the closed-form formulas at any point in time by compiling the output with another program

Lane Compression: A Lightweight Lossless Compression Method for Machine Learning on Embedded Systems

This article presents Lane Compression, a lightweight lossless compression technique for machine learning that is based on a detailed study of the statistical properties of machine learning data. The proposed technique profiles machine learning data gathered ahead of run-time and partitions values bit-wise into different lanes with more distinctive statistical characteristics. Then the most appropriate compression technique is chosen for each lane out of a small number of low-cost compression techniques. Lane Compression’s compute and memory requirements are very low and yet it achieves a compression rate comparable to or better than Huffman coding. We evaluate and analyse Lane Compression on a wide range of machine learning networks for both inference and re-training. We also demonstrate the profiling prior to run-time and the ability to configure the hardware based on the profiling guarantee robust performance across different models and datasets. Hardware implementations are described and the scheme’s simplicity makes it suitable for compressing both on-chip and off-chip traffic. Samsung Advanced Institute of Technology (SAIT

Investigation of Interconnect and Device Designs for Emerging Post-MOSFET and Beyond Silicon Technologies

Title from PDF of title page viewed May 31, 2017Dissertation advisor: Masud H. ChowdhuryVitaIncludes bibliographical references (pages 94-108)Thesis (Ph.D.)--School of Computing and Engineering and Department of Physics and Astronomy. University of Missouri--Kansas City, 2016The integrated circuit industry has been pursuing Moore’s curve down to deep nanoscale dimensions that would lead to the anticipated delivery of 100 billion transistors on a 300 mm² die operating below 1V supply in the next 5-10 years. However, the grand challenge is to reliably and efficiently take the full advantage of the unprecedented computing power offered by the billions of nanoscale transistors on a single chip. To mitigate this challenge, the limitations of both the interconnecting wires and semiconductor devices in integrated circuits have to be addressed. At the interconnect level, the major challenge in current high density integrated circuit is the electromagnetic and electrostatic impacts in the signal carrying lines. Addressing these problems require better analysis of interconnect resistance, inductance, and capacitance. Therefore, this dissertation has proposed a new delay model and analyzed the time-domain output response of complex poles, real poles, and double poles for resistance-inductance capacitance interconnect network based on a second order approximate transfer function. Both analytical models and simulation results show that the real poles model is much faster than the complex poles model, and achieves significantly higher accuracy in order to characterize the overshoot and undershoot of the output responses. On the other hand, the semiconductor industry is anticipating that within a decade silicon devices will be unable to meet the demands at nanoscale due to dimension and material scaling. Recently, molybdenum disulfide (MoS₂) has emerged as a new super material to replace silicon in future semiconductor devices. Besides, conventional field effect transistor technology is also reaching its thermodynamic limit. Breaking this thermal and physical limit requires adoption of new devices based on tunneling mechanism. Keeping the above mentioned trends, this dissertation also proposed a multilayer MoS₂ channel-based tunneling transistor and identifies the fundamental parameters and design specifications that need to be optimized in order to achieve higher ON-currents. A simple analytical model of the proposed device is derived by solving the time-independent Schrodinger equation. It is analytically proven that the proposed device can offer an ON-current of 80 A/m, a subthreshold swing (S) of 9.12 mV/decade, and a / ratio of 10¹².Introduction -- Previous models on interconnect designs -- Proposed delay model for interconnect design -- Investigation of tunneling for field effect transistor -- Study of molybdenum disulfide for FET applications -- Proposed molybdenum disulfide based tunnel transistor -- Conclusion -- Appendix A. Derivation of time delay model -- Appendix B. Derivation of tunneling current model Appendix C. Derivation of subthreshold swing mode

Power Reductions with Energy Recovery Using Resonant Topologies

The problem of power densities in system-on-chips (SoCs) and processors has become more exacerbated recently, resulting in high cooling costs and reliability issues. One of the largest components of power consumption is the low skew clock distribution network (CDN), driving large load capacitance. This can consume as much as 70% of the total dynamic power that is lost as heat, needing elaborate sensing and cooling mechanisms. To mitigate this, resonant clocking has been utilized in several applications over the past decade. An improved energy recovering reconfigurable generalized series resonance (GSR) solution with all the critical support circuitry is developed in this work. This LC resonant clock driver is shown to save about 50% driver power (\u3e40% overall), on a 22nm process node and has 50% less skew than a non-resonant driver at 2GHz. It can operate down to 0.2GHz to support other energy savings techniques like dynamic voltage and frequency scaling (DVFS). As an example, GSR can be configured for the simpler pulse series resonance (PSR) operation to enable further power saving for double data rate (DDR) applications, by using de-skewing latches instead of flip-flop banks. A PSR based subsystem for 40% savings in clocking power with 40% driver active area reduction xii is demonstrated. This new resonant driver generates tracking pulses at each transition of clock for dual edge operation across DVFS. PSR clocking is designed to drive explicit-pulsed latches with negative setup time. Simulations using 45nm IBM/PTM device and interconnect technology models, clocking 1024 flip-flops show the reductions, compared to non-resonant clocking. DVFS range from 2GHz/1.3V to 200MHz/0.5V is obtained. The PSR frequency is set \u3e3× the clock rate, needing only 1/10th the inductance of prior-art LC resonance schemes. The skew reductions are achieved without needing to increase the interconnect widths owing to negative set-up times. Applications in data circuits are shown as well with a 90nm example. Parallel resonant and split-driver non-resonant configurations as well are derived from GSR. Tradeoffs in timing performance versus power, based on theoretical analysis, are compared for the first time and verified. This enables synthesis of an optimal topology for a given application from the GSR

BUSTLE: a new circuit simulation tool using asymptotic waveform evaluation and piece-wise linear approach

Ankara : Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent University, 1990.Thesis (Master's) -- Bilkent University, 1990.Includes bibliographical references leaves 63-65BUSTLE, a new general purpose circuit simulation program is developed especially for the analysis of VLSI circuits. BUSTLE uses Asymptotic Waveform Evaluation (AWE), which is a new method to analyze linear(ized) circuits, and PWL approach for the I'epresentation of nonlinear devices. AWE employs a form of Fade approximation rather than numerical integration to approximate the behavior of linear(ized) circuits in either the time or the frequency domain. AWE is extended to match both derivative and integral moments to overcome the unstability problem.Dikmen, Cemal TamerM.S

Joint Protection Scheme for Deep Neural Network Hardware Accelerators and Models

Deep neural networks (DNNs) are utilized in numerous image processing, object detection, and video analysis tasks and need to be implemented using hardware accelerators to achieve practical speed. Logic locking is one of the most popular methods for preventing chip counterfeiting. Nevertheless, existing logic-locking schemes need to sacrifice the number of input patterns leading to wrong output under incorrect keys to resist the powerful satisfiability (SAT)-attack. Furthermore, DNN model inference is fault-tolerant. Hence, using a wrong key for those SAT-resistant logic-locking schemes may not affect the accuracy of DNNs. This makes the previous SAT-resistant logic-locking scheme ineffective on protecting DNN accelerators. Besides, to prevent DNN models from being illegally used, the models need to be obfuscated by the designers before they are provided to end-users. Previous obfuscation methods either require long time to retrain the model or leak information about the model. This paper proposes a joint protection scheme for DNN hardware accelerators and models. The DNN accelerator is modified using a hardware key (Hkey) and a model key (Mkey). Different from previous logic locking, the Hkey, which is used to protect the accelerator, does not affect the output when it is wrong. As a result, the SAT attack can be effectively resisted. On the other hand, a wrong Hkey leads to substantial increase in memory accesses, inference time, and energy consumption and makes the accelerator unusable. A correct Mkey can recover the DNN model that is obfuscated by the proposed method. Compared to previous model obfuscation schemes, our proposed method avoids model retraining and does not leak model information

SCEE 2008 book of abstracts : the 7th International Conference on Scientific Computing in Electrical Engineering (SCEE 2008), September 28 – October 3, 2008, Helsinki University of Technology, Espoo, Finland

This report contains abstracts of presentations given at the SCEE 2008 conference.reviewe