Majority-Vote Cellular Automata, Ising Dynamics, and P-Completeness

We study cellular automata where the state at each site is decided by a majority vote of the sites in its neighborhood. These are equivalent, for a restricted set of initial conditions, to non-zero probability transitions in single spin-flip dynamics of the Ising model at zero temperature. We show that in three or more dimensions these systems can simulate Boolean circuits of AND and OR gates, and are therefore P-complete. That is, predicting their state t time-steps in the future is at least as hard as any other problem that takes polynomial time on a serial computer. Therefore, unless a widely believed conjecture in computer science is false, it is impossible even with parallel computation to predict majority-vote cellular automata, or zero-temperature single spin-flip Ising dynamics, qualitatively faster than by explicit simulation.Comment: 10 pages with figure

Performance of the LHCb muon system

The performance of the LHCb Muon system and its stability across the full 2010 data taking with LHC running at ps = 7 TeV energy is studied. The optimization of the detector setting and the time calibration performed with the first collisions delivered by LHC is described. Particle rates, measured for the wide range of luminosities and beam operation conditions experienced during the run, are compared with the values expected from simulation. The space and time alignment of the detectors, chamber efficiency, time resolution and cluster size are evaluated. The detector performance is found to be as expected from specifications or better. Notably the overall efficiency is well above the design requirementsComment: JINST_015P_1112 201

Approximate and timing-speculative hardware design for high-performance and energy-efficient video processing

Since the end of transistor scaling in 2-D appeared on the horizon, innovative circuit design paradigms have been on the rise to go beyond the well-established and ultraconservative exact computing. Many compute-intensive applications – such as video processing – exhibit an intrinsic error resilience and do not necessarily require perfect accuracy in their numerical operations. Approximate computing (AxC) is emerging as a design alternative to improve the performance and energy-efficiency requirements for many applications by trading its intrinsic error tolerance with algorithm and circuit efficiency. Exact computing also imposes a worst-case timing to the conventional design of hardware accelerators to ensure reliability, leading to an efficiency loss. Conversely, the timing-speculative (TS) hardware design paradigm allows increasing the frequency or decreasing the voltage beyond the limits determined by static timing analysis (STA), thereby narrowing pessimistic safety margins that conventional design methods implement to prevent hardware timing errors. Timing errors should be evaluated by an accurate gate-level simulation, but a significant gap remains: How these timing errors propagate from the underlying hardware all the way up to the entire algorithm behavior, where they just may degrade the performance and quality of service of the application at stake? This thesis tackles this issue by developing and demonstrating a cross-layer framework capable of performing investigations of both AxC (i.e., from approximate arithmetic operators, approximate synthesis, gate-level pruning) and TS hardware design (i.e., from voltage over-scaling, frequency over-clocking, temperature rising, and device aging). The cross-layer framework can simulate both timing errors and logic errors at the gate-level by crossing them dynamically, linking the hardware result with the algorithm-level, and vice versa during the evolution of the application’s runtime. Existing frameworks perform investigations of AxC and TS techniques at circuit-level (i.e., at the output of the accelerator) agnostic to the ultimate impact at the application level (i.e., where the impact is truly manifested), leading to less optimization. Unlike state of the art, the framework proposed offers a holistic approach to assessing the tradeoff of AxC and TS techniques at the application-level. This framework maximizes energy efficiency and performance by identifying the maximum approximation levels at the application level to fulfill the required good enough quality. This thesis evaluates the framework with an 8-way SAD (Sum of Absolute Differences) hardware accelerator operating into an HEVC encoder as a case study. Application-level results showed that the SAD based on the approximate adders achieve savings of up to 45% of energy/operation with an increase of only 1.9% in BD-BR. On the other hand, VOS (Voltage Over-Scaling) applied to the SAD generates savings of up to 16.5% in energy/operation with around 6% of increase in BD-BR. The framework also reveals that the boost of about 6.96% (at 50°) to 17.41% (at 75° with 10- Y aging) in the maximum clock frequency achieved with TS hardware design is totally lost by the processing overhead from 8.06% to 46.96% when choosing an unreliable algorithm to the blocking match algorithm (BMA). We also show that the overhead can be avoided by adopting a reliable BMA. This thesis also shows approximate DTT (Discrete Tchebichef Transform) hardware proposals by exploring a transform matrix approximation, truncation and pruning. The results show that the approximate DTT hardware proposal increases the maximum frequency up to 64%, minimizes the circuit area in up to 43.6%, and saves up to 65.4% in power dissipation. The DTT proposal mapped for FPGA shows an increase of up to 58.9% on the maximum frequency and savings of about 28.7% and 32.2% on slices and dynamic power, respectively compared with stat

Improving timing verification and delay testing methodologies for IC designs

textThe task of ensuring the correct temporal behavior of IC designs, both before and after fabrication, is extremely important. It is becoming even more imperative as the demand for performance increases and process technology advances into the deep sub-micron region. This dissertation tackles the key issues in the timing verification and delay testing methodologies. An efficient methodology is presented to identify false timing paths in the timing verification methodology which utilizes ATPG technique and timing information from an ordered list of timing paths according to the delay information. This dissertation also presents a speed binning methodology which utilizes structural delay tests successfully instead of functional tests. In addition, it establishes a methodology which quantifies the correlation between the timing verification prediction and actual silicon measurement of timing paths. This quantification methodology lays the foundation for further research to study the impact of deep submicron effects on design performanceElectrical and Computer Engineerin

Gate-level timing analysis and waveform evaluation

Static timing analysis (STA) is an integral part of modern VLSI chip design. Table lookup based methods are widely used in current industry due to its fast runtime and mature algorithms. Conventional STA algorithms based on table-lookup methods are developed under many assumptions in timing analysis; however, most of those assumptions, such as that input signals and output signals can be accurately modeled as ramp waveforms, are no longer satisfactory to meet the increasing demand of accuracy for new technologies. In this dissertation, we discuss several crucial issues that conventional STA has not taken into consideration, and propose new methods to handle these issues and show that new methods produce accurate results. In logic circuits, gates may have multiple inputs and signals can arrive at these inputs at different times and with different waveforms. Different arrival times and waveforms of signals can cause very different responses. However, multiple-input transition effects are totally overlooked by current STA tools. Using a conventional single-input transition model when multiple-input transition happens can cause significant estimation errors in timing analysis. Previous works on this issue focus on developing a complicated gate model to simulate the behavior of logic gates. These methods have high computational cost and have to make significant changes to the prevailing STA tools, and are thus not feasible in practice. This dissertation proposes a simplified gate model, uses transistor connection structures to capture the behavior of multiple-input transitions and requires no change to the current STA tools. Another issue with table lookup based methods is that the load of each gate in technology libraries is modeled as a single lumped capacitor. But in the real circuit, the Abstract 2 gate connects to its subsequent gates via metal wires. As the feature size of integrated circuit scales down, the interconnection cannot be seen as a simple capacitor since the resistive shielding effect will largely affect the equivalent capacitance seen from the gate. As the interconnection has numerous structures, tabulating the timing data for various interconnection structures is not feasible. In this dissertation, by using the concept of equivalent admittance, we reduce an arbitrary interconnection structure into an equivalent π-model RC circuit. Many previous works have mapped the π-model to an effective capacitor, which makes the table lookup based methods useful again. However, a capacitor cannot be equivalent to a π-model circuit, and will thus result in significant inaccuracy in waveform evaluation. In order to obtain an accurate waveform at gate output, a piecewise waveform evaluation method is proposed in this dissertation. Each part of the piecewise waveform is evaluated according to the gate characteristic and load structures. Another contribution of this dissertation research is a proposed equivalent waveform search method. The signal waveforms can be very complicated in the real circuits because of noises, race hazards, etc. The conventional STA only uses one attribute (i.e., transition time) to describe the waveform shape which can cause significant estimation errors. Our approach is to develop heuristic search functions to find equivalent ramps to approximate input waveforms. Here the transition time of a final ramp can be completely different from that of the original waveform, but we can get higher accuracy on output arrival time and transition time. All of the methods mentioned in this dissertation require no changes to the prevailing STA tools, and have been verified across different process technologies

Artificial neural network model for arrival time computation in gate level circuits

Advances in the VLSI process technology lead to variations in the process parameters. These process variations severely affect the delay computation of a digital circuit. Under such variations, the various delays, i.e. net delay, gate delay, etc., are no longer deterministic. They are random in nature and are assumed to be probabilistic. They keep changing, based on factors such as process, voltage, temperature, and a few others. This calls for efficient tools to perform timing checks on a design. This work presents a technique to compute the arrival time of a digital circuit. The arrival time (AT) is computed using two different timing engines, namely, static timing analysis (STA) and statistical static timing analysis (SSTA). This work also aims to eliminate number of false paths. It uses a fast and efficient filtering method by utilizing ATPG stuck-at faults and path delay faults. ISCAS-89 benchmark circuits are used for implementation. The results obtained using the probabilistic approach are more accurate than the conventional STA. It has been verified with an Artificial Neural Network (ANN) model. The arrival time calculated using SSTA shows 7% improvement over that of STA. The absolute error is reduced twofold in the case of the ANN model for SSTA

Interval simulation: raising the level of abstraction in architectural simulation

Detailed architectural simulators suffer from a long development cycle and extremely long evaluation times. This longstanding problem is further exacerbated in the multi-core processor era. Existing solutions address the simulation problem by either sampling the simulated instruction stream or by mapping the simulation models on FPGAs; these approaches achieve substantial simulation speedups while simulating performance in a cycle-accurate manner This paper proposes interval simulation which rakes a completely different approach: interval simulation raises the level of abstraction and replaces the core-level cycle-accurate simulation model by a mechanistic analytical model. The analytical model estimates core-level performance by analyzing intervals, or the timing between two miss events (branch mispredictions and TLB/cache misses); the miss events are determined through simulation of the memory hierarchy, cache coherence protocol, interconnection network and branch predictor By raising the level of abstraction, interval simulation reduces both development time and evaluation time. Our experimental results using the SPEC CPU2000 and PARSEC benchmark suites and the MS multi-core simulator show good accuracy up to eight cores (average error of 4.6% and max error of 11% for the multi-threaded full-system workloads), while achieving a one order of magnitude simulation speedup compared to cycle-accurate simulation. Moreover interval simulation is easy to implement: our implementation of the mechanistic analytical model incurs only one thousand lines of code. Its high accuracy, fast simulation speed and ease-of-use make interval simulation a useful complement to the architect's toolbox for exploring system-level and high-level micro-architecture trade-offs

IC design for reliability

textAs the feature size of integrated circuits goes down to the nanometer scale, transient and permanent reliability issues are becoming a significant concern for circuit designers. Traditionally, the reliability issues were mostly handled at the device level as a device engineering problem. However, the increasing severity of reliability challenges and higher error rates due to transient upsets favor higher-level design for reliability (DFR). In this work, we develop several methods for DFR at the circuit level. A major source of transient errors is the single event upset (SEU). SEUs are caused by high-energy particles present in the cosmic rays or emitted by radioactive contaminants in the chip packaging materials. When these particles hit a N+/P+ depletion region of an MOS transistor, they may generate a temporary logic fault. Depending on where the MOS transistor is located and what state the circuit is at, an SEU may result in a circuit-level error. We analyze SEUs both in combinational logic and memories (SRAM). For combinational logic circuit, we propose FASER, a Fast Analysis tool of Soft ERror susceptibility for cell-based designs. The efficiency of FASER is achieved through its static and vector-less nature. In order to evaluate the impact of SEU on SRAM, a theory for estimating dynamic noise margins is developed analytically. The results allow predicting the transient error susceptibility of an SRAM cell using a closedform expression. Among the many permanent failure mechanisms that include time-dependent oxide breakdown (TDDB), electro-migration (EM), hot carrier effect (HCE), and negative bias temperature instability (NBTI), NBTI has recently become important. Therefore, the main focus of our work is NBTI. NBTI occurs when the gate of PMOS is negatively biased. The voltage stress across the gate generates interface traps, which degrade the threshold voltage of PMOS. The degraded PMOS may eventually fail to meet timing requirement and cause functional errors. NBTI becomes severe at elevated temperatures. In this dissertation, we propose a NBTI degradation model that takes into account the temperature variation on the chip and gives the accurate estimation of the degraded threshold voltage. In order to account for the degradation of devices, traditional design methods add guard-bands to ensure that the circuit will function properly during its lifetime. However, the worst-case based guard-bands lead to significant penalty in performance. In this dissertation, we propose an effective macromodel-based reliability tracking and management framework, based on a hybrid network of on-chip sensors, consisting of temperature sensors and ring oscillators. The model is concerned specifically with NBTIinduced transistor aging. The key feature of our work, in contrast to the traditional tracking techniques that rely solely on direct measurement of the increase of threshold voltage or circuit delay, is an explicit macromodel which maps operating temperature to circuit degradation (the increase of circuit delay). The macromodel allows for costeffective tracking of reliability using temperature sensors and is also essential for enabling the control loop of the reliability management system. The developed methods improve the over-conservatism of the device-level, worstcase reliability estimation techniques. As the severity of reliability challenges continue to grow with technology scaling, it will become more important for circuit designers/CAD tools to be equipped with the developed methods.Electrical and Computer Engineerin