Covid-19 and its impacts on consumer decision-making process

The term "virus" derives from the Latin word for "venom" and refers to a microscopic infectious agent. On the other hand, "corona" is named by its shape to look like a crown ring – the scientists who coined the word coronavirus in 1968 reasoned that the virus they were studying under a microscope resembled a solar corona (Steinmetz, 2020). COVID-19 was introduced when it was first detected in late 2019 and used letters from CO-Rona-VI-rus D-isease (Bhargava, 2020). Corona infections were initially seen as cold in 1965 (Kahn & McIntosh, 2005), which is almost six decades ago. Corona was formerly thought to be a basic, non-fatal virus to human beings until 2002. Before the world witnessed a Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) outbreak in November 2002, it was assumed that this virus mainly infected animals. However, this was proven incorrect. Ten years after that, a new pathogenic coronavirus known as the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) spread throughout the Middle East and caused a pandemic in several countries (Shereen et a., 2020)

Interconnect tree optimization algorithm in nanometer very large scale integration designs

This thesis proposes a graph-based maze routing and buffer insertion algorithm for nanometer Very Large Scale Integration (VLSI) layout designs. The algorithm is called Hybrid Routing Tree and Buffer insertion with Look-Ahead (HRTB-LA). In recent VLSI designs, interconnect delay becomes a dominant factor compared to gate delay. The well-known technique to minimize the interconnect delay is by inserting buffers along the interconnect wires. In conventional buffer insertion algorithms, the buffers are inserted on the fixed routing paths. However, in a modern design, there are macro blocks that prohibit any buffer insertion in their respective area. Most of the conventional buffer insertion algorithms do not consider these obstacles. In the presence of buffer obstacles, post routing algorithm may produce poor solution. On the other hand, simultaneous routing and buffer insertion algorithm offers a better solution, but it was proven to be NP-complete. Besides timing performance, power dissipation of the inserted buffers is another metric that needs to be optimized. Research has shown that power dissipation overhead due to buffer insertions is significantly high. In other words, interconnect delay and power dissipation move in opposite directions. Although many methodologies to optimize timing performance with power constraint have been proposed, no algorithm is based on grid graph technique. Hence, the main contribution of this thesis is an efficient algorithm using a hybrid approach for multi-constraint optimization in multi-terminal nets. The algorithm uses dynamic programming to compute the interconnect delay and power dissipation of the inserted buffers incrementally, while an effective runtime is achieved with the aid of novel look-ahead and graph pruning schemes. Experimental results prove that HRTB-LA is able to handle multi-constraint optimizations and produces up to 47% better solution compared to a post routing buffer insertion algorithm in comparable runtime

Timing Closure in Chip Design

Achieving timing closure is a major challenge to the physical design of a computer chip. Its task is to find a physical realization fulfilling the speed specifications. In this thesis, we propose new algorithms for the key tasks of performance optimization, namely repeater tree construction; circuit sizing; clock skew scheduling; threshold voltage optimization and plane assignment. Furthermore, a new program flow for timing closure is developed that integrates these algorithms with placement and clocktree construction. For repeater tree construction a new algorithm for computing topologies, which are later filled with repeaters, is presented. To this end, we propose a new delay model for topologies that not only accounts for the path lengths, as existing approaches do, but also for the number of bifurcations on a path, which introduce extra capacitance and thereby delay. In the extreme cases of pure power optimization and pure delay optimization the optimum topologies regarding our delay model are minimum Steiner trees and alphabetic code trees with the shortest possible path lengths. We presented a new, extremely fast algorithm that scales seamlessly between the two opposite objectives. For special cases, we prove the optimality of our algorithm. The efficiency and effectiveness in practice is demonstrated by comprehensive experimental results. The task of circuit sizing is to assign millions of small elementary logic circuits to elements from a discrete set of logically equivalent, predefined physical layouts such that power consumption is minimized and all signal paths are sufficiently fast. In this thesis we develop a fast heuristic approach for global circuit sizing, followed by a local search into a local optimum. Our algorithms use, in contrast to existing approaches, the available discrete layout choices and accurate delay models with slew propagation. The global approach iteratively assigns slew targets to all source pins of the chip and chooses a discrete layout of minimum size preserving the slew targets. In comprehensive experiments on real instances, we demonstrate that the worst path delay is within 7% of its lower bound on average after a few iterations. The subsequent local search reduces this gap to 2% on average. Combining global and local sizing we are able to size more than 5.7 million circuits within 3 hours. For the clock skew scheduling problem we develop the first algorithm with a strongly polynomial running time for the cycle time minimization in the presence of different cycle times and multi-cycle paths. In practice, an iterative local search method is much more efficient. We prove that this iterative method maximizes the worst slack, even when restricting the feasible schedule to certain time intervals. Furthermore, we enhance the iterative local approach to determine a lexicographically optimum slack distribution. The clock skew scheduling problem is then generalized to allow for simultaneous data path optimization. In fact, this is a time-cost tradeoff problem. We developed the first combinatorial algorithm for computing time-cost tradeoff curves in graphs that may contain cycles. Starting from the lowest-cost solution, the algorithm iteratively computes a descent direction by a minimum cost flow computation. The maximum feasible step length is then determined by a minimum ratio cycle computation. This approach can be used in chip design for several optimization tasks, e.g. threshold voltage optimization or plane assignment. Finally, the optimization routines are combined into a timing closure flow. Here, the global placement is alternated with global performance optimization. Netweights are used to penalize the length of critical nets during placement. After the global phase, the performance is improved further by applying more comprehensive optimization routines on the most critical paths. In the end, the clock schedule is optimized and clocktrees are inserted. Computational results of the design flow are obtained on real-world computer chips