Embedded computer systems are characterized by the presence of a processor running application specific software. A large number of these systems must satisfy real-time constraints. This paper examines the problem of determining the bound on the running time of a given program on a given processor. An important aspect of this problem is determining the extreme case program paths. The state of the art solution here relies on an explicit enumeration of program paths. This runs out of steam rather quickly since the number of feasible program paths is typically exponential in the size of the program. We present a solution for this problem, which considers all paths implicitly by using integer linear programming. This solution is implemented in the program cinderella which currently targets a popular embedded processor -- the Intel i960. The preliminary results of using this tool are presented here.

The traditional approach to worst-case static-timing analysis is becoming unacceptably conservative due to an ever-increasing number of circuit and process effects. We propose a fundamentally different framework that aims to significantly improve the accuracy of timing predictions through fully probabilistic analysis of gate and path delays. We describe a bottom-up approach for the construction of joint probability density function of path delays, and present novel analytical and algorithmic methods for finding the full distribution of the maximum of a random path delay space with arbitrary path correlations.

This paper addresses the problem of accurately computing the delay of a combinational logic circuit in the floating mode of operation. (In this mode the state of the circuit is considered to be unknown when a vector is applied at5 the inputs.) It is well known that using the length of the topologically longest path as an estimate of circuit delay may be pessimistic since this path may be false, i.e., it cannot propagate an event. Thus, the true delay corresponds to the length of the longest true path. This forces us to examine the conditions under which a path is true. We introduce the notion of static cosensitization of paths which leads us to necessary and sufficient conditions for determining the truth or falsity of a single path, or a set of paths. We apply these results to develop a delay computation algorithm that has the unique feature that it is able to determine the truth or falsity of entire sets of paths simultaneously. This algorithm uses conventional stuck-at-fault testing techniques to arrive at a delay computation method that is both correct and computationally practical, even for particularly difficult circuits.

This paper discusses a statistical approach to static timing analysis. Delays of gates and wires are modeled by stochastic values instead of the triple best case, typical and worst case delay. This has the advantage of avoiding the overly pessimistic (optimistic) outcome of traditional worst (best) case calculations. The paper proposes a new approximate scheme to perform the delay calculations with stochastic delay values in linear time. The results are validated with Monte Carlo simulations. From a mathematical analysis some counter--intuitive properties of delays in the presence of uncertain delay values are shown. The results section shows that that traditional worst--case timing analysis is on average 21% too pessimistic for the set of IWLS '91 combinational benchmark circuits for a given delay model. Also, it is shown that the traditional typical delay calculation underestimates the most likely circuit delay by 0 -- 14%. Furthermore, due to the mathematical properties of the delay...

As cycle times in high-performance digital systems shrink faster than simple process improvement allows, sequencing overhead consumes an increasing fraction of the clock period. In particular, the overhead of traditional domino pipelines can consume 25% or more of the cycle time in aggressive systems. Fortunately, the designer can hide much of this overhead through better design techniques. The key to skew-tolerant design is avoiding hard edges in which data must setup before a clock edge but will not continue propagating until after the clock edge. Skew-tolerant domino circuits use multiple overlapping clocks to eliminate latches, removing hard edges and hiding the sequencing overhead.

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Abstract not found

In chip design, one of the main objectives is to decrease its clock cycle. On the design stage, this time is usually estimated by using worst-case (interval) techniques, in which we only use the bounds on the parameters that lead to delays. This analysis does not take into account that the probability of the worst-case values is usually very small; thus, the resulting estimates are over-conservative, leading to unnecessary over-design and under-performance of circuits. If we knew the exact probability distributions of the corresponding parameters, then we could use Monte-Carlo simulations (or the corresponding analytical techniques) to get the desired estimates. In practice, however, we only have partial information about the corresponding distributions, and we want to produce estimates that are valid for all distributions which are consistent with this information.

Maximum instantaneous power in VLSI circuits has a great impact on circuit's reliability and the design of power and ground lines. To synthesize highly reliable systems, accurate estimates of maximum power must be obtained in various design phases. Unfortunately, determining the input patterns to induce the maximum current (power) is essentially a combinatorial optimization problem. Even for circuits with small number of primary inputs (PI's), it is CPU time intensive to conduct exhaustive search in the input vector space. The only feasible way is to find good upper and lower bounds of the maximum power, and to make the gap between these two bounds as narrow as possible. In this paper, we present a continuous optimization approach to efficiently generate tight lower bounds of the maximum instantaneous power for CMOS circuits. In our approach, each primary input (PI) of the circuit is allowed to assume any real number between 0 and 1. Maximum power estimation for CMOS circuits is then t...