This paper presents an advanced DAG-based algorithm for datapath synthesis that targets area minimization using logic-level resource sharing. The problem of identifying common specification logic is formulated using unweighted graph isomorphism problem, in contrast to a weighted graph isomorphism using AIGs. In the context of gate-level datapath circuits, our algorithm solves the unweighted graph isomorphism problem in linear time. The experiments are conducted within an industrial synthesis flow that includes the complete high-level synthesis, logic synthesis and placement and route procedures. Experimental results show a significant runtime improvements compared to the existing datapath synthesis algorithms.

Traditional datapath synthesis for standard-cell designs go through extraction of arithmetic operations from the high-level description, high-level synthesis, and netlist generation. In this paper, we take a fresh look at applying high-level synthesis methodologies in logic synthesis. We present a DAG-Aware synthesis technique for datapaths synthesis which is implemented using And-Inv-Graphs. Our approach targets area minimization. The proposed algorithm includes identifying vector multiplexers, searching for common specification logic, and reallocating multiplexers in the Boolean network. We propose an algorithm to identify common specification logic by using subgraph isomorphism. Experimental results show that our technique can provide over 10% area reduction beyond the traditional design flow. The proposed algorithm is tested on industry designs and academic benchmark suits using IBM 14nm technology.

Achieving timing-closure has become one of the hardest tasks in logic synthesis due to the required stringent timing constraints in very large circuit designs. In this paper, we propose a novel synthesis paradigm to achieve timing-closure called Timing-Aware CUt Enumeration (TACUE). In TACUE, optimization is conducted through three aspects: (1) a new divide-and-conquer strategy is proposed that generates multiple sub-cuts on the critical parts of the circuit; (2) two cut enumeration strategies are proposed; (3) an efficient parallel synthesis framework is offered to reduce computation time. Experiments on large and difficult industrial benchmarks show the promise of the proposed method.

Power consumption has become a major consideration in nanometer chip design. Since the dynamic power is proportional to V dd2, and the static power is proportional to V dd, lowering power supply voltage is an efficient method to reduce the power usage.

Routability or wiring congestion in a very large scale integration chip is becoming increasingly important as chip complexity increases. Congestion has a significant impact on performance, yield, and chip area. Although advances in placement algorithms have attempted to alleviate this problem, the inherent structure of the logic netlist has a significant impact on the routability irrespective of the placement algorithm used. Placement algorithms find optimal assignments of locations to the logic and do not have the ability to change the netlist structure. Significant decisions regarding the circuit structure are made early in synthesis during the technology-independent logic-optimization step. Optimizations in this step use literal count as a metric for optimization and do not adequately capture the intrinsic entanglement of the netlist. Two circuits with identical literal counts may have significantly different congestion characteristics after placement. In this paper, we postulate that a property of the network structure called adhesion can make a significant contribution to routing congestion. We then provide a metric to measure this property. We evaluate the utility of adhesion as measured by this metric to estimate and optimize postrouting congestion early in the design flow. A heuristic for measuring adhesion is evaluated as well.

Routability or wiring congestion in a VLSI chip is becoming increasingly important as chip complexity increases. Congestion has a significant impact on performance, yield and chip area. Although advances in placement algorithms have attempted to alleviate this problem, the inherent structure of the logic netlist has a significant impact on the routability irrespective of the placement algorithm used. Placement algorithms find optimal assignment of locations to the logic and do not have the ability to change the netlist structure. Significant decisions regarding the circuit structure are made early in synthesis such as during the technology independent logic optimization step. Optimizations in this step use literal count as a metric for optimization and do not adequately capture the intrinsic entanglement of the netlist. Two circuits with identical literal counts may have significantly different congestion characteristics post placement. In this paper, we motivate that a property of the network structure called adhesion can make a significant contribution to routing congestion. We then provide a metric to measure this property. We also show that adhesion as measured by this metric can be used in addition to literal counts to estimate and optimize post routing congestion early in the design flow.

Novel methodology and algorithms to seamlessly integrate logic synthesis and physical placement through a transformational approach are presented. Contrary to most placement algorithms that minimize a global cost function based on an abstract representation of the design, we decomposed the placement function into a set of transforms and coupled them directly with incremental timing, noise, and/or power analyzers. This coupling results in a direct and more accurate feedback on optimizations for placement actions. These placement transforms are then integrated with traditional logic synthesis transforms leading to a converging set of optimizations based on the concurrent manipulation of boolean, electrical, as well as physical data. Experimental results indicate that the proposed approach creates an efficient converging design flow that eliminates placement and synthesis iteration. It results in timing improvements, and maintains other global placement measures such as wire congestion and wire length. The flexibility of the transformational approach allows us to easily add, extend and support more sophisticated algorithms that involve critical as well as non-critical regions and target a variety of metrics including noise, yield and manufacturability:.