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Ulrich Brenner

Publications and source records attributed to Ulrich Brenner.

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Delay-Optimum Adder Circuits with Linear Size

We present efficient circuits for the addition of binary numbers. We assume that we are given arrival times for all input bits and optimize the delay of the circuits, i.e.\ the time when the last output bit is computed. This contains the classical optimization of depth as a special case where all arrival times are $0$. In this model, we present, among other results, the fastest adder circuits of sub-quadratic size and the fastest adder circuits of linear size. In particular, for adding two $n$-numbers we get a circuits with linear size and delay $\log_2W+3\log_2\log_2n+4\log_2\log_2\log_2n +const$ where $\log_2W$ is a lower bound for the delay of any adder circuit (no matter what size it has).

cs.LO

Faster Linear-Size And-Or Path and Adder Circuits

We consider the fundamental problem of constructing fast and small circuits for binary addition. We propose a new algorithm with running time $\mathcal O(n \log_2 n)$ for constructing linear-size $n$-bit adder circuits with a significantly better depth guarantee compared to previous approaches: Our circuits have a depth of at most $\log_2 n + \log_2 \log_2 n + \log_2 \log_2 \log_2 n + \text{const}$, improving upon the previously best circuits by [12] with a depth of at most $\log_2 n + 8 \sqrt{\log_2 n} + 6 \log_2 \log_2 n + \text{const}$. Hence, we decrease the gap to the lower bound of $\log_2 n + \log_2 \log_2 n + \text{const}$ by [5] significantly from $\mathcal O (\sqrt{\log_2 n})$ to $\mathcal O(\log_2 \log_2 \log_2 n)$. Our core routine is a new algorithm for the construction of a circuit for a single carry bit, or, more generally, for an And-Or path, i.e., a Boolean function of type $t_0 \lor ( t_1 \land (t_2 \lor ( \dots t_{m-1}) \dots ))$. We compute linear-size And-Or path circuits with a depth of at most $\log_2 m + \log_2 \log_2 m + 0.65$ in time $\mathcal O(m \log_2 m)$. These are the first And-Or path circuits known that, up to an additive constant, match the lower bound by [5] and at the same time have a linear size. The previously fastest And-Or path circuits are only by an additive constant worse in depth, but have a much higher size in the order of $\mathcal O (m \log_2 m)$.

cs.DS

Constructing Depth-Optimum Circuits for Adders and AND-OR Paths

We examine the fundamental problem of constructing depth-optimum circuits for binary addition. More precisely, as in literature, we consider the following problem: Given auxiliary inputs $t_0, \dotsc, t_{m-1}$, so-called generate and propagate signals, construct a depth-optimum circuit over the basis {AND2, OR2} computing all $n$ carry bits of an $n$-bit adder, where $m=2n-1$. In fact, carry bits are AND-OR paths, i.e., Boolean functions of the form $t_0 \lor ( t_1 \land (t_2 \lor ( \dots t_{m-1}) \dots ))$. Classical approaches construct so-called prefix circuits which do not achieve a competitive depth. For instance, the popular construction by Kogge and Stone is only a $2$-approximation. A lower bound on the depth of any prefix circuit is $1.44 \log_2 m$ + const, while recent non-prefix circuits have a depth of $\log_2 m$ + $\log_2 \log_2 m$ + const. However, it is unknown whether any of these polynomial-time approaches achieves the optimum depth for all $m$. We present a new exponential-time algorithm solving the problem optimally. The previously best exact algorithm with a running time of $\mathcal O(2.45^m)$ is viable only for $m \leq 29$. Our algorithm is significantly faster: We achieve a running time of $\mathcal O(2.02^m)$ and apply sophisticated pruning strategies to improve practical running times dramatically. This allows us to compute optimum circuits for all $m \leq 64$. Combining these computational results with new theoretical insights, we derive the optimum depths of $2^k$-bit adder circuits for all $k \leq 13$, previously known only for $k \leq 4$. In fact, we solve a more general problem occurring in VLSI design: $delay$ optimization of a $generalization$ of AND-OR paths where AND and OR do not necessarily alternate. Our algorithm arises from our new structure theorem which characterizes delay-optimum generalized AND-OR path circuits.

cs.DM

Delay Optimization of Combinational Logic by And-Or Path Restructuring

We propose a dynamic programming algorithm that constructs delay-optimized circuits for alternating And-Or paths with prescribed input arrival times. Our algorithm fulfills best-known approximation guarantees and empirically outperforms earlier methods by exploring a significantly larger portion of the solution space. Our algorithm is the core of a new timing optimization framework that replaces critical paths of arbitrary length by logically equivalent realizations with less delay. Our framework allows revising early decisions on the logical structure of the netlist in a late step of an industrial physical design flow. Experiments demonstrate the effectiveness of our tool on 7nm real-world instances.

cs.DS

Faster Carry Bit Computation for Adder Circuits with Prescribed Arrival Times

We consider the fundamental problem of constructing fast circuits for the carry bit computation in binary addition. Up to a small additive constant, the carry bit computation reduces to computing an \aop, i.e., a formula of type $t_0 \land (t_1 \lor (t_2 \land ( \dots t_{m-1}) \dots )$ or $t_0 \lor (t_1 \land (t_2 \lor ( \dots t_{m-1}) \dots )$. We present an algorithm that computes the fastest known Boolean circuit for an \aop~ with given arrival times $a(t_0), \dotsc, a(t_{m-1})$ for the input signals. Our objective function is delay, a natural generalization of depth with respect to arrival times. The maximum delay of the circuit we compute is $\log_2 W + \log_2 \log_2 m + \log_2 \log_2 \log_2 m + 4.3$, where $W := \sum_{i = 0}^{m-1} 2^{a(t_i)}$. Note that $\lceil \log_2 W \rceil$ is a lower bound on the delay of any circuit depending on inputs $t_0, \dotsc, t_{m-1}$ with prescribed arrival times. Our method yields the fastest circuits for \aop s, carry bit computation and adders in terms of delay known so far.

cs.DS