American Studies Commons^™

Real Delay Graphical Probabilistic Switching Model For Vlsi Circuits, Vivekanandan Srinivasan

USF Tampa Graduate Theses and Dissertations

Power optimization is a crucial issue at all levels of abstractions in VLSI Design. Power estimation has to be performed repeatedly to explore the design space throughout the design process at all levels. Dynamic Power Dissipation due to Switching Activity has been one of the major concerns in Power Estimation. While many Simulation and Statistical Simulation based methods exist to estimate Switching Activity, these methods are input pattern sensitive, hence would require a large input vector set to accurately estimate Power. Probabilistic estimation of switching activity under Zero-Delay conditions, seriously undermines the accuracy of the estimation process, since it fails …

Stimulus-Free Rt Level Power Model Using Belief Propagation, Sathishkumar Ponraj

USF Tampa Graduate Theses and Dissertations

Power consumption is one of the major bottlenecks in current and future VLSI design. Early microprocessors, which consumed a few tens of watts, are now replaced by millions of transistors and with the introduction of easy-to-design tools to explore at unbelievable minimum dimensions, increase in chip density is increasing at a alarming rate and necessitates faster power estimation methods. Gate level power estimation techniques are highly accurate methods but when time is the main constraint, power has to be estimated a lot higher in the abstraction level. Estimating power at higher levels also saves valuable time and cost involved in …

A Heuristic Methodology For Locating Monitoring Stations To Detect Contamination Events In Potable Water Distribution Systems, James R. Chastain Jr.

USF Tampa Graduate Theses and Dissertations

The requirements to protect public water systems from intentional contamination have expanded in the years following September 11, 2001. The areal extent and non-linear nature of water demand and movement in the distribution system makes efficient location of sampling points difficult. This difficulty is compounded by the fact that contamination conceptually can occur at any point and at any time within the distribution system. Small to mid-sized water systems are especially at a disadvantage in addressing this issue due to limited resources available to them.

This paper proposes a heuristic methodology to identify strategic locations within the system that can …

A Complete Probabilistic Framework For Learning Input Models For Power And Crosstalk Estimation In Vlsi Circuits, Nirmal Munuswamy Ramalingam

USF Tampa Graduate Theses and Dissertations

Power disspiation is a growing concern in VLSI circuits. In this work we model the data dependence of power dissipation by learning an input model which we use for estimation of both switching activity and crosstalk for every node in the circuit. We use Bayesian networks to effectively model the spatio-temporal dependence in the inputs and we use the probabilistic graphical model to learn the structure of the dependency in the inputs. The learned structure is representative of the input model. Since we learn a causal model, we can use a larger number of independencies which guarantees a minimal structure. …

Graphical Probabilistic Switching Model: Inference And Characterization For Power Dissipation In Vlsi Circuits, Shiva Shankar Ramani

USF Tampa Graduate Theses and Dissertations

Power dissipation in a VLSI circuit poses a serious challenge in present and future VLSI design. A switching model for the data dependent behavior of the transistors is essential to model dynamic, load-dependent active power and also leakage power in active mode - the two components of power in a VLSI circuit. A probabilistic Bayesian Network based switching model can explicitly model all spatio-temporal dependency relationships in a combinational circuit, resulting in zero-error estimates. However, the space-time requirements of exact estimation schemes, based on this model, increase with circuit complexity [5, 24]. This work explores a non-simulative, importance sampling based, …

Estimation Of Switching Activity In Sequential Circuits Using Dynamic Bayesian Networks, Karthikeyan Lingasubramanian

USF Tampa Graduate Theses and Dissertations

This thesis presents a novel, non-simulative, probabilistic model for switching activity in sequential circuits, capturing both spatio-temporal correlations at internal nodes and higher order temporal correlations due to feedback. Switching activity, one of the key components in dynamic power dissipation, is dependent on input streams and exhibits spatio-temporal correlation amongst the signals. One can handle dependency modeling of switching activity in a combinational circuit by Bayesian Networks [2] that encapsulates the underlying joint probability distribution function exactly.

We present the underlying switching model of a sequential circuit as the time coupled logic induced directed acyclic graph (TC-LiDAG), that can be …