An Adaptive Feature Based Low Power Motion Estimation Algorithm

Motion Estimation is one of the most power hungry operations in video coding. While optimal search (eg. full search)methods give best quality, non optimal methods are often used in order to reduce cost and power. Various algorithms have been used in practice that trade off quality vs. complexity. Global elimination is an algorithm based on pixel averaging to reduce complexity of motion search while keeping performance close to that of full search. We propose an adaptive version of the global elimination algorithm that extracts individual macro-block features using Hadamard transform to optimize the search. Performance achieved is close to the full search method and global elimination. Operational complexity and hence power is reduced by 30% to 45% compared to global elimination method.

A low power, process invariant keeper design for high speed dynamic logic circuits

A low power keeper circuit using the concept of rate sensing has been proposed. The proposed technique reduces the amount of short circuit power dissipation in the domino gate by 70% compared to the conventional keeper technique. Also the total power-delay product is 26% lower compared to the previously reported techniques. The process tracking capability of the design enables the domino gate to achieve uniform delay across different process corners. This reduces the amount of short circuit power dissipation that occurs in the cascaded domino gates by 90%. The use of the proposed technique in the read path of a register file reduces the energy requirement by 26% as compared to the other keeper techniques. The proposed technique has been prototyped in 130nm CMOS technology.

Executing Long-running Multi-component Applications on Batch Grids

Computational grids are increasingly being used for executing large multi-component scientific applications. The most widely reported advantages of application execution on grids are the performance benefits, in terms of speeds, problem sizes or quality of solutions, due to increased number of processors. We explore the possibility of improved performance on grids without increasing the application’s processor space. For this, we consider grids with multiple batch systems. We explore the challenges involved in and the advantages of executing long-running multi-component applications on multiple batch sites with a popular multi-component climate simulation application, CCSM, as the motivation.We have performed extensive simulation studies to estimate the single and multi-site execution rates of the applications for different system characteristics.Our experiments show that in many cases, multiple batch executions can have better execution rates than a single site execution.

Power Efficient Redundant Execution for Chip Multiprocessor

This paper describes the design of a power efficient microarchitecture for transient fault detection in chip multiprocessors (CMPs) We introduce a new per-core dynamic voltage and frequency scaling (DVFS) algorithm for our architecture that significantly reduces power dissipation for redundant execution with a minimal performance overhead. Using cycle accurate simulation combined with a simple first order power model, we estimate that our architecture reduces dynamic power dissipation in the redundant core by an mean value of 79% and a maximum of 85% with an associated mean performance overhead of only 1:2%

Scan cell reordering to minimize peak power during test cycle: A graph theoretic approach

Scan circuit is widely practiced DFT technology. The scan testing procedure consist of state initialization, test application, response capture and observation process. During the state initialization process the scan vectors are shifted into the scan cells and simultaneously the responses captured in last cycle are shifted out. During this shift operation the transitions that arise in the scan cells are propagated to the combinational circuit, which inturn create many more toggling activities in the combinational block and hence increases the dynamic power consumption. The dynamic power consumed during scan shift operation is much more higher than that of normal mode operation.

Phylogenetic Predictions on Grids

A phylogenetic or evolutionary tree is constructed from a set of species or DNA sequences and depicts the relatedness between the sequences. Predictions of future sequences in a phylogenetic tree are important for a variety of applications including drug discovery, pharmaceutical research and disease control. In this work, we predict future DNA sequences in a phylogenetic tree using cellular automata. Cellular automata are used for modeling neighbor-dependent mutations from an ancestor to a progeny in a branch of the phylogenetic tree. Since the number of possible ways of transformations from an ancestor to a progeny is huge, we use computational grids and middleware techniques to explore the large number of cellular automata rules used for the mutations. We use the popular and recurring neighbor-based transitions or mutations to predict the progeny sequences in the phylogenetic tree. We performed predictions for three types of sequences, namely, triose phosphate isomerase, pyruvate kinase, and polyketide synthase sequences, by obtaining cellular automata rules on a grid consisting of 29 machines in 4 clusters located in 4 countries, and compared the predictions of the sequences using our method with predictions by random methods. We found that in all cases, our method gave about 40% better predictions than the random methods.

Middleware for Long-running Applications on Batch Grids. Student Research Symposium poster

Computational grids with multiple batch systems (batch grids) can be powerful infrastructures for executing long-running multicomponent parallel applications. In this paper, we have constructed a middleware framework for executing such long-running applications spanning multiple submissions to the queues on multiple batch systems. We have used our framework for execution of a foremost long-running multi-component application for climate modeling, the Community Climate System Model (CCSM). Our framework coordinates the distribution, execution, migration and restart of the components of CCSM on the multiple queues where the component jobs of the different queues can have different queue waiting and startup times.