We present a noise-driven effective capacitance method for estimating the combined propagation noise and crosstalk noise. Gate propagation noise rules are efficiently calculated inside the Ceff procedure to determine a linear Thevenin model of the victim driver. A voltage-dependent current source model [2, 6] of the driver, along with a load capacitor is analyzed to generate the gate output waveform, from which noise rules are directly extracted. This method removes potential errors introduced in traditional look-up table or fitted-equation based noise rules. The linear driver Thevenin model can then be employed to analyze the propagation noise, while the same Thevenin resistance can be used to analyze the crosstalk noise. The combined coupling and propagation noise can then be estimated using superposition. In this work, we extend the popular timing-driven effective capacitance method into the noise domain. Similar to the effective capacitance method in timing analysis, this technique can successfully separate the nonlinear driver analysis from the linear interconnect analysis. In addition, the linear driver model can significantly ease the task of finding the worst-case peak alignment among all the victim and aggressor noise sources. Experimental results on both RC and RLC nets from industry designs show both accuracy and efficiency compared to SPICE results.

We present an early-stage global wire-design methodology that simultaneously considers the performance needs for both signal lines and power grids under congestion considerations. An iterative procedure is employed in which the global routing is performed according to a congestion map that includes the resource utilization of the power grid, followed by a step in which the power grid is adjusted to relax the congestion in crowded regions. This adjustment is in the form of wire removal in noncritical regions, followed by a wire-sizing step that overcomes the voltage noise after wire removal and a wire-width resizing that meets the maximum current-density constraint. Experimental results show that the overall routability can be significantly improved while the power-grid noise is maintained within both the voltage-drop and current-density constraints.

With the scaling of technology, power grid noise is becoming increasingly significant for circuit performance. A typical power grid circuit contains millions of linear elements, making noise analysis and verification challenging in terms of both run time and memory. We propose a power grid reduction scheme based on algebraic multigrid principles, in which the coarser-level grid and the restriction operators are constructed automatically from the circuit matrices. This method is suitable for large-scale power grid transient and AC analysis. Experimental results show an order of magnitude speed-up over flat analysis in addition to practical tradeoffs for accuracy, CPU time and memory usage.

Leakage power is emerging as a new critical challenge in the design of high performance integrated circuits. Leakage is increasing dramatically with each technology generation and is expected to dominate system power. This paper describes a static (i.e input independent) technique for efficient and accurate leakage estimation. A probabilistic technique is presented to compute the average leakage of combinational circuits. The proposed technique gives accurate results with an average error of only 2% for the ISCAS benchmarks and accurately predict both subthreshold and gate leakage as well as the leakage sensitivities to process and environmental parameters.

Leakage power is emerging as a key design challenge in current and future CMOS designs. Since leakage is critically dependent on operating temperature and power supply, we present a full chip leakage estimation technique which accurately accounts for power supply and temperature variations. State of the art techniques are used to compute the thermal and power supply profile of the entire chip. Closed-form models are presented which relate leakage to temperature and VDD variations. These models coupled with the thermal and VDD profile are used to generate an accurate full chip leakage estimation technique considering environmental variations. The results of this approach are demonstrated on large-scale industrial designs.

Fast progress on VLSI technology makes clock skew more susceptible to process variations. We propose DME/BST based algorithms for clock tree routing to improve skew tolerance to process variations. The worst case skew due to process variations is estimated and employed to guide the decision making during the routing. Our method can be applied to general non-zero skew requirements. Minimizing total wirelength is considered as a secondary objective at the same time. Experimental results on benchmark circuits demonstrate great improvement on process variation tolerance through our algorithms.

This paper presents an efficient method for optimizing power/ground (P/G) networks by widening wires and adding decoupling capacitors (decaps). It proposes a structured skeleton that is intermediate to the conventional method that uses full meshes, which are hard to analyze efficiently, and tree-structured networks, which provide poor performance. As an example, we consider a P/G network structure modeled as an overlying mesh with underlying trees originating from the mesh, which eases the task of analysis with acceptable performance sacrifices. A fast and efficient event-driven P/G network simulator is proposed, which hierarchically simulates the P/G network with an adaptation of PRIMA to handle nonzero initial conditions. An adjoint network that incorporates the variable topology of the original P/G network, as elements switch in and out of the network, is constructed to calculate the transient adjoint sensitivity over multiple intervals. The gradients of the most critical node with respect to each wire width and decap are used by a sensitivity-based heuristic optimizer that minimizes a weighted sum of the wire and the decap area. Experimental results show that this procedure can be used to efficiently optimize large networks.

With technology scaling, the trend for high-performance integrated circuits is toward ever higher operating frequency, lower power supply voltages, and higher power dissipation. This causes a dramatic increase in the currents being delivered through the on-chip power grid and is recognized in the 2001 International Technology Roadmap for Semiconductors as one of the difficult challenges. The addition of decoupling capacitances (decaps) is arguably the most powerful degree of freedom that a designer has for power-grid noise abatement and is becoming more important as technology scales. In this paper, we propose and demonstrate an algorithm for the automated placement and sizing of decaps in application specific integrated circuit (ASIC)-like circuits. The problem is formulated as one of nonlinear optimization and is solved using a sensitivity-based quadratic programming (QP) solver. The adjoint sensitivity method is applied to calculate the first-order sensitivities. We propose a fast convolution technique based on piecewise linear (PWL) compressions of the original and adjoint waveforms. Experimental results show that power grid noise can be significantly reduced after a judicious optimization of decap placement, with little change in the total chip area.

We present a global wire design methodology that simultaneously considers the performance needs for both signal lines and power grids under congestion considerations. An iterative procedure is employed in which the global routing is performed according to a congestion map that includes the resource utilization of the power grid, followed by a step in which the power grid is adjusted to relax the congestion in crowded regions. This adjustment is in the form of wire removal in noncritical regions, followed by a wire sizing step that overcomes the effects of wire removal. Experimental results show that the overall routability can be significantly improved while the power grid noise is maintained within the voltage droop constraint.

With technology scaling, the trend for high performance integrated circuits is towards ever higher operating frequency, lower power supply voltages and higher power dissipation. This causes a dramatic increase in the currents being delivered through the on-chip power grid and is recognized in the International Technology Roadmap for Semiconductors as one of the difficult challenges. The addition of decoupling capacitances (decaps) is arguably the most powerful degree of freedom that a designer has for power-grid noise abatement and is becoming more important as technology scales. In this paper, we propose and demonstrate an algorithm for the automated placement and sizing of decaps in ASIC-like circuits. The adjoint sensitivity method is applied to calculate the first-order sensitivity of the power grid noise with respect to every decap. We propose a fast convolution technique based on piecewise linear (PWL) compressions of the original and adjoint waveforms. Experimental results show that power grid noise can be significantly reduced after a judicious optimization of decap placement, with little change of the total chip area.

This paper hierarchically constructs a hybrid mesh/tree clock network structure consisting of overlying zero-skew clock meshes, with underlying zero-skew clock trees originating from the mesh nodes. We propose a mesh construction procedure, which guarantees zero skew under the Elmore delay model, using a simple and efficient linear programming formulation. Buffers are inserted to reduce the transition time (or rise time). As a post-processing step, wire width optimization under an accurate higher-order delay metric is performed to further minimize the transition time and propagation delay/skew. Experimental results show that the hybrid mesh/tree construction scheme can provide smaller propagation delay and transition time than a comparable clock tree.

This paper presents an efficient method for optimizing power/ground (P/G) networks by widening wires and adding decoupling capacitors (decaps). It proposes a structured skeleton that is intermediate to the conventional method that uses full meshes (which are hard to analyze efficiently), and tree-structured networks (which provide poor performance). As an example, we consider a P/G network structure modeled as an overlying mesh with underlying trees originating from the mesh, which eases the task of analysis with acceptable performance sacrifices. A fast and efficient event-driven P/G network simulator is proposed, which hierarchically simulates the P/G network with an adaptation of PRIMA to handle non-zero initial conditions. An adjoint network that incorporates the variable topology of the original P/G network, as elements switch in and out of the network, is constructed to calculate the transient adjoint sensitivity over multiple intervals. The gradients of the most critical node with respect to each wire width and decap are used by a sensitivity-based heuristic optimizer that minimizes a weighted sum of the wire and the decap area. Experimental results show that this procedure can be used to efficiently optimize large networks.