Shrirang K. Karandikar

Techniques for Fast Physical Synthesis

The traditional purpose of physical synthesis is to perform timing closure , i.e., to create a placed design that meets its timing specifications while also satisfying electrical, routability, and signal integrity constraints. In modern design flows, physical synthesis tools hardly ever achieve this goal in their first iteration. The design team must iterate by studying the output of the physical synthesis run, then potentially massage the input, e.g., by changing the floorplan, timing assertions, pin locations, logic structures, etc., in order to hopefully achieve a better solution for the next iteration. The complexity of physical synthesis means that systems can take days to run on designs with multimillions of placeable objects, which severely hurts design productivity. This paper discusses some newer techniques that have been deployed within IBMs physical synthesis tool called PDS that significantly improves throughput. In particular, we focus on some of the biggest contributors to runtime, placement, legalization, buffering, and electric correction, and present techniques that generate significant turnaround time improvements

Fast Algorithms for Slew-Constrained Minimum Cost Buffering

As a prevalent constraint, sharp slew rate is often required in circuit design, which causes a huge demand for buffering resources. This problem requires ultrafast buffering techniques to handle large volume of nets while also minimizing buffering cost. This problem is intensively studied in this paper. First, a highly efficient algorithm based on dynamic programming is proposed to optimally solve slew buffering with discrete buffer locations. Second, a new algorithm using the maximum matching technique is developed to handle the difficult cases in which no assumption is made on buffer input slew. Third, an adaptive buffer selection approach is proposed to efficiently handle slew buffering with continuous buffer locations. Fourth, buffer blockage avoidance is handled, which makes the algorithms ready for practical use. Experiments on industrial netlists demonstrate that our algorithms are very effective and highly efficient: we achieve about 90x speedup and save up to 20% buffer area over the commonly used van Ginneken style buffering. The new algorithms also significantly outperform previous works that indirectly address the slew buffering problem.

Fast algorithms for slew constrained minimum cost buffering

As a prevalent constraint, sharp slew rate is often required in circuit design which causes a huge demand for buffering resources. This problem requires ultra-fast buffering techniques to handle large volume of nets, while also minimizing buffering cost. This problem is intensively studied in this paper. First, a highly efficient algorithm based on dynamic programming is proposed to optimally solve slew buffering with discrete buffer locations. Second, a new algorithm is developed to handle the difficult cases in which no assumption is made on buffer input slew. Third, an adaptive buffer selection approach is proposed to efficiently handle slew buffering with continuous buffer locations. Experiments on industrial netlists demonstrate that our algorithms are very effective and highly efficient: we achieve > 100times speed up and save up to 40% buffer area over the commonly-used van Ginneken style buffering

Technology mapping for SOI domino logic incorporating solutions for the parasitic bipolar effect

We present a technology mapping algorithm for implementing a random logic gate network in domino logic. The target technology of implementation is silicon-on-insulator (SOI). SOI devices exhibit an effect known as parasitic bipolar effect (PBE), which can lead to incorrect logic values in the circuit. Our algorithm solves the technology mapping problem by permitting several transformations during the mapping process in order to avoid PBE, such as transistor reordering, altering the way that transistors are organized into gates, and adding pMOS discharge transistors. We minimize the total cost of implementation, which includes discharge transistors required for correct functioning. Our algorithm generates solutions that reduce the number of discharge transistors required by 53% and reduces the size of the final solution by 6.3% on average. We compare our results with a modification of a current technology mapping algorithm for bulk CMOS domino logic that reduces the cost of the final solution and find that our algorithm outperforms this method.

Logical effort based technology mapping

We propose a new approach to library-based technology mapping, based on the method of logical effort. Our algorithm is close to optimal for fanout-free circuits, and is extended to solve the load-distribution problem for circuits with fanout. On average, benchmark circuits mapped using our approach are 25.39% faster than the solutions obtained from SIS.

Fast comparisons of circuit implementations

Digital designs can be mapped to different implementations using diverse approaches, with varying cost criteria. Post-processing transforms, such as transistor sizing can drastically improve circuit performance, by optimizing critical paths to meet timing specifications. However, most transistor sizing tools have high execution times, and the attainable circuit delay can be determined only after running the tool. In this paper, we present an approach for fast transistor sizing that can enable a designer to choose one among several functionally identical implementations. Our algorithm computes the minimum achievable delay of a circuit with a maximum average error of 5.5% in less than a second for even the largest benchmarks.

Technology Mapping Using Logical Effort for Solving the Load-Distribution Problem

Technology mapping is a crucial step in the synthesis of digital designs and can be used to obtain mapped circuits that are optimized for delay or area. Current tree-based mapping algorithms break the circuit into individual trees and map these optimally. However, these solutions are not globally optimal. This paper presents a new approach to delay-optimal mapping based on the principle of logical effort. This algorithm maps individual trees such that the solution of the entire circuit is optimal. In traditional technology mapping, the best match for a gate depends on the load being driven, which is not known at the matching stage. Current algorithms handle this situation by generating matches for all loads and selecting the best match at a later stage. This strategy works for fan-out-free circuits but breaks down at multiple fan-out points where each fan-out has to be sized correctly, depending on its criticality. This can have a significant impact on the selection of matches as well but has not been adequately addressed in the published literature. We refer to the correct sizing of branches of multiple fan-out points as the load-distribution problem, which is formally defined and solved in the context of technology mapping in this paper. The effect of the new logical effort-based mapping algorithm, combined with correct sizing of individual branches of a multiple fan-out point, leads to implementations that are closer to the global optimum. On the average, benchmark circuits mapped using our approach are 39.45% faster and 32.77% smaller than those obtained using SIS.

The nuts and bolts of physical synthesis

As technology scaling advances to the 45 and 32 nanometer nodes, more devices can fit onto a chip, which impliescontinued rapid design size growth. Naturally, it becomes increasingly challenging to achieve design closure on these enormous chips with tight performance and power constraints. Physical synthesis has emerged as a critical and powerful component of modern design methodologies to conquer such challenges. Starting from logic-level net list, physical synthesis creates a legally placed design while attempting to satisfy timing, power, and electrical constraints simultaneously. This paper briefly outlines the core components of physical synthesis timing closure and discusses some recent techniques that improve the solution quality and throughput of the physical synthesis process.

Fast estimation of area-delay trade-offs in circuit sizing

Appropriately sizing a circuit can improve its performance significantly. However, this is a time consuming transform, and it is therefore difficult to compare different implementations of a circuit in terms of the cost overhead required for a particular delay target. This paper presents a fast estimator of the complete area-delay trade-off curve of a given circuit, allowing a designer to choose the most appropriate implementation for a given delay. We observe excellent fidelity with the actual area-delay curves (94.13% correct comparisons), with an average error of 5.76% in the area differences predicted.