Parameter ordering for multi-corner static timing analysis

A method and system for decreasing processing time in multi-corner static timing analysis. In one embodiment, parameters are ordered in a parameter order by decreasing magnitude of impact on variability of timing. In one example, a decreasing parameter order is utilized to order slack cutoff values that are assigned across a parameter process space. In another example, a decreasing parameter order is utilized to perform a multi-corner timing analysis on one or more dependent parameters in an independent fashion.

RELATED APPLICATION DATA

This application is related to U.S. patent application Ser. No. 11/679,834, filed Feb. 27, 2007, entitled “Variable Threshold System and Method for Multi-Corner Static Timing Analysis,” which is incorporated herein by reference in its entirety.

FIELD OF THE DISCLOSURE

The present disclosure generally relates to the field of static timing analysis. In particular, the present disclosure is directed to a system and method for parameter ordering in multi-corner static timing analysis.

BACKGROUND

Static timing analysis (STA) is utilized to verify integrated circuit design and analyze circuit performance. In circuit design, one signal may need to arrive at a particular point in a circuit path at a particular time with respect to another signal. A timing test with respect to a pair of timing test points is typically to compare two signals to determine whether a particular requirement on their relative arrival time is met. The difference of the relative arrival time of two signals at the timing test point is referred to as “slack”. Two paths on which signals propagate to arrive at the pair of timing test points (e.g., clock and data pins of a flip-flop circuit) are often referred to as racing paths. Timing of integrated circuits may vary due to the effects of environmental and process variation parameters. In multi-corner static timing analysis, each source of variation to be analyzed is modeled as a parameter having an impact on a delay of a circuit path and/or a circuit. Example sources of variation include, but are not limited to, voltage, metal width, temperature, transistor channel length, transistor threshold voltage, gate oxide thickness, other process controlled performance changing parameters. In one example, each of the parameters is used to model process, environmental conditions, and aging affects in static timing analysis can be toggled between its extreme distribution endpoints. Any specific setting of these parameter values is referred to as a corner. In one example, a parameter may be set to one of its extreme values (e.g., a 3SIGMA extreme value). In such an example, one parameter setting provides a fastest signal propagation checked in a timing analysis and the other corner provides a slowest signal propagation in a timing analysis as a function of this parameter. A static timing analysis may start with each parameter in a set having its values set to a particular extreme, called a starting corner.

Parameters for analysis in timing tests typically can be independent or dependent. In one example, an independent parameter allows for a given path to be evaluated at the corners of that parameter irrespective of the corner settings of other process variable/parameters. However, dependent parameters typically must be evaluated with respect to settings of other parameters. In such an analysis, testing of combinations of multiple parameter settings may occur in a multi-corner timing analysis. In such an analysis with n parameters, there may be 2nextreme corner combinations that require evaluation in order to determine the worst slack across all process corners. As the number of parameters to test increases and the complexity of integrated circuit designs continues to grow, the analysis of the large number of extreme corner combinations for each path of an integrated circuit becomes difficult, if not impossible, to perform in a reasonable amount of time. Reduction of the number of paths requiring full multi-corner analysis at all 2nprocess corners can reduce the time required to perform a full chip analysis within a reasonable runtime.

One manner to reduce the number of paths to analyze in a multi-corner analysis involves comparing a slack value obtained from a starting corner analysis to an initial threshold, often referred to as a slack cutoff. In one example, a slack cutoff threshold may be determined empirically for a given integrated circuit technology and/or set of environmental conditions (e.g., process variations) that apply to the integrated circuit by identifying an upper bound on the slack change of any path going from a starting corner to any other corner in the process space. If a starting corner slack determined for a path passes a chosen slack cutoff value, it is estimated that the path would pass all corner analyses. Thus, any path that has a starting corner slack that is above a starting corner slack cutoff can be removed from analysis as it will likely pass multi-corner analysis. This can reduce the number of paths for multi-corner analysis. However, in order to reduce the possibility of having paths that potentially have a timing failure from erroneously being removed from analysis, the slack cutoff value is often set at a fairly high value. This, in turn, may lead to an undesirably low reduction in the number of paths that require full multi-corner analysis.

SUMMARY OF THE DISCLOSURE

In one embodiment, a computerized method of decreasing processing time in multi-corner static timing analysis is provided. The method includes determining an n number of dependent parameters (Pi), each dependent parameter (Pi) having an impact on variability of timing; ensuring the n number of dependent parameters (Pi) are organized in a decreasing parameter order from a first parameter P1having a largest impact on variability of timing to a last parameter Pnhaving a smallest impact on variability on timing; and performing a multi-corner timing analysis by utilizing the decreasing parameter order to output an indication of timing verification for one or more paths of an integrated circuit design.

In another embodiment, a computerized method of decreasing processing time in multi-corner static timing analysis is provided. The method includes determining an n number of dependent parameters (Pi), each dependent parameter (Pi) having an impact on variability of timing; ensuring the n number of dependent parameters (Pi) are organized in a decreasing parameter order from a first parameter P1having a largest impact on variability of timing to a last parameter Pnhaving a smallest impact on variability on timing; conducting a starting corner timing analysis to determine a starting corner slack for each path of one or more predetermined paths of an integrated circuit design; varying parameter P1in the parameter order to a non-starting corner parameter value to determine a first non-starting corner slack for each path; comparing the starting corner slack for each path with a corresponding first non-starting corner slack to determine a worst slack value for each path at P1; analyzing each path by varying a next parameter Piin the parameter order, starting with P2, to a non-starting corner parameter value while holding any other unvaried parameter at its starting corner parameter value and holding any previously varied parameter at a corner parameter value that produced its corresponding worst slack value, the analyzing including: determining a second non-starting corner slack for each path; and comparing the second non-starting corner slack for each path with a corresponding worst slack value determined from the most recent prior comparing step to update the worst slack value for each path at Pi; repeating the analyzing step for each remaining parameter Piin the parameter order and determining a final worst slack value for each path from the worst slack value determined by the varying of the last parameter in the parameter order; outputting an indication of timing verification based on the final worst slack for each path of one or more paths of the integrated circuit design.

In yet another embodiment, a computer readable medium containing computer executable instructions implementing a method of decreasing processing time in multi-corner static timing analysis is provided. The instructions include a set of instructions for determining an n number of dependent parameters (Pi), each dependent parameter (Pi) having an impact on variability of timing; a set of instructions for ensuring the n number of dependent parameters (Pi) are organized in a decreasing parameter order from a first parameter P1having a largest impact on variability of timing to a last parameter Pnhaving a smallest impact on variability on timing; and a set of instructions for performing a multi-corner timing analysis by utilizing the decreasing parameter order to output an indication of timing verification for one or more paths of an integrated circuit design.

DETAILED DESCRIPTION

Embodiments of the present disclosure include a system and method for reducing processing time in multi-corner static timing analysis. In one embodiment, a variable slack cutoff scheme is utilized for a process space of a number of parameters to be used in a multi-corner analysis. In another embodiment, the parameters of a process space are organized in decreasing order of delay sensitivity for each parameter. In one example of such an embodiment, slack cutoff values attributed to each parameter in a variable slack cutoff scheme are organized in the same order as the parameters. In yet another embodiment, a multi-corner timing analysis may be performed using a variable slack cutoff scheme to reduce the time required to process a number of paths through multi-corner timing analysis. These and other embodiments and aspects are discussed further below with respect to the examples illustrated inFIGS. 1 to 6.

Embodiments of the present disclosure include a system and method for reducing processing time in multi-corner static timing analysis. In one embodiment, a variable slack cutoff scheme is utilized for a process space of a number of parameters to be used in a multi-corner analysis. In another embodiment, the parameters of a process space are organized in decreasing order of delay sensitivity for each parameter. In one example of such an embodiment, slack cutoff values attributed to each parameter in a variable slack cutoff scheme are organized in the same order as the parameters. In yet another embodiment, a multi-corner timing analysis may be performed using a variable slack cutoff scheme to reduce the time required to process a number of paths through multi-corner timing analysis. These and other embodiments and aspects are discussed further below with respect to the examples illustrated inFIGS. 1 to 6.

FIG. 1illustrates one embodiment of a method100. At step105, parameters for use in a multi-corner timing analysis are determined. The set of parameters determined make up a process space for the analysis. In one example, n number of parameters may be determined. In such an example, for ease of description each parameter may be designated as Pi, where i can be a value from 1 to n. The full parameter process space for this example would include P1, P2, . . . Pn, with the parameters Pithought of as being in a parameter order from P1to Pn. A full process space may be viewed as including any number of subdivisions (i.e., a process sub-space) of the entire process space. In one example, a process sub-space may be defined for each of the parameters Pi (e.g., one or more parameter process sub-spaces defined by Pi→n). The concept of a full process space including one or more process sub-spaces does not require that a full process space actually be divided (e.g. physically or logically in a software implementation) into separate groups. The concept of process sub-spaces is utilized further below in determining one or more slack cutoffs for a variable slack cutoff scheme.

To illustrate parameters and process spaces further, an exemplary set of parameters for use in a timing analysis may include six (6) parameters Pisuch that the full process space would include {P1, P2, P3, P4, P5, P6}. This full process space may be viewed to include any number of process sub-spaces (e.g., the same number of process sub-spaces as the number of parameters, here six). In this example, the full process space may include six process sub-spaces defined by Pi→n(e.g., a process sub-space for P1including {P1, P2, P3, P4, P5, P6}; a process sub-space for P2including {P2, P3, P4, P5, P6}; a process sub-space for P3including {P3, P4, P5, P6}; a process sub-space for P4including {P4, P5, P6}; a process sub-space for P5including {P5, P6}; and a process sub-space for P6including {P6}). Although, an example of n=6 is utilized throughout this description for illustrative purposes, it should be noted that any number n parameters may be utilized.

In one example, a process sub-space for determining a slack cutoff (ci) may be defined as Pi→n, such that the process sub-space includes all parameters from the full process space that are from the ith parameter to the nth parameter. For the example discussed above where n=6, a slack cutoff (ci) may be determined corresponding to each of the parameters {P1, P2, P3, P4, P5, P6}. In this example, for P1a corresponding slack cutoff (c1) may be determined by estimating an upper bound on a slack change of any path that moves from a starting corner to any other corner in the process sub-space including parameters P1to P6{P1, P2, P3, P4, P5, P6}. For P2a corresponding slack cutoff (c2) may be determined by estimating an upper bound on a slack change of any path that moves from a starting corner to any other corner in the process sub-space including parameters P2to P6{P2, P3, P4, P5, P6}. For P3a corresponding slack cutoff (c3) may be determined by estimating an upper bound on a slack change of any path that moves from a starting corner to any other corner in the process sub-space including parameters P3to P6{P3, P4, P5, P6}. For P4a corresponding slack cutoff (c4) may be determined by estimating an upper bound on a slack change of any path that moves from a starting corner to any other corner in the process sub-space including parameters P4to P6{P4, P5, P6}. For P5a corresponding slack cutoff (c5) may be determined by estimating an upper bound on a slack change of any path that moves from a starting corner to any other corner in the process sub-space including parameters P1to P6{P5, P6}. For P6a corresponding slack cutoff (c6) may be determined by estimating an upper bound on a slack change of any path that moves from a starting corner to any other corner in the process sub-space including parameters P6to P6{P6}.

FIG. 2illustrates a graphical depiction plotting one example of a variable slack cutoff scheme200for an exemplary full process space having n=6. In this example, the parameters {P1, P2, P3, P4, P5, P6} are represented on the x-axis of the plot. For each parameter Pi, a corresponding slack cutoff ciis shown with increasing slack value on the y-axis. Each slack cutoff (ci) may be determined as discussed above with respect toFIG. 1. In this example, parameters P1to P6are shown organized in a parameter order such that the corresponding slack cutoff values c1to c6are in descending order. In other examples, alternate parameter ordering may be utilized. One exemplary aspect of a variable slack cutoff scheme (e.g., scheme200) may be increased efficiency and reduced analysis time when parameters are organized in a parameter order such that corresponding slack cutoff values are in a descending order. In one example, parameters may be organized in a parameter order P1to Pnsuch that corresponding impact on variability of timing for each parameter Piare in a descending order (e.g., parameter P1having the highest impact on variability of timing and Pnhaving the lowest impact on variability of timing). Examples of impact on variability of timing include, but are not limited to, a path slack variability, a path latency variability, a path delay variability, a path slew variability, and any combinations thereof. Those of ordinary skill may recognize a variety of ways to determine a delay sensitivity, a path delay variability, a path slack variability, a path slew variability, and/or a path latency variability for a particular parameter. Further embodiments involving the ordering of one or more parameters in a parameter order are discussed below with respect toFIG. 4.

Referring again toFIG. 1, at step115, a multi-corner timing analysis is performed on one or more paths of an integrated circuit design utilizing the variable slack cutoff scheme determined in step110. Each slack cutoff (ci) may be used when analyzing a path with respect to a one or more parameters (Pi). For example, as a worst slack value is determined for a path as analysis moves off of a starting corner to one or more corner parameter values of a particular parameter (Pi), the corresponding slack cutoff (ci+1) is used in testing the worst slack value to determine potential timing failure for the path. It should be noted that in such an example after parameter Pn-1is varied and the resultant worst slack compared with cn, a further step of varying Pnmay occur to determine an additional worst slack that may be compared with a user-defined slack threshold (e.g., a signoff slack, as is known to those of ordinary skill) to determine a timing verification for a path remaining in the analysis. One embodiment of a use of a variable slack cutoff scheme, such as the scheme determined in step110is further discussed below with respect to the example set forth inFIG. 3.

At step120, timing verification information determined by multi-corner analysis of one or more paths at step115is output. Output of timing verification information may be in one or more of a variety of forms. Examples of an output include, but are not limited to, representation of an indicator of timing verification information as a displayable image (e.g., via a display device), representation of an indicator of timing verification information as a physical printout (e.g., via a printer of a computing device), transfer of a data element including an indicator of timing verification information (e.g., via an electrical connection, wired or wireless) to a device (e.g., a storage device, a remote computing device), evaluation of pulse width versus the rise/fall times of a signal, and any combinations thereof. In one example, multi-corner analysis of step115may be implemented using a computing device. Discussion of one example of a computing environment for implementation of one or more aspects of method100is provided below with respect toFIG. 6. A multi-corner timing analysis, such as that performed in step115, may utilize one or more timing analysis tools. Those of ordinary skill will recognize from the description herein how to configure a timing analysis tool to utilize a variable slack cutoff scheme and perform a multi-corner timing analysis as described herein. Examples of a timing analysis tool include, but are not limited to, EINSTIMER available from International Business Machines, and PRIMETIME available from Synopsys. In another example, output from a computing device performing multi-corner timing analysis may be via generation of data representing a displayable image that includes an indication of timing verification of one or more paths analyzed. The displayable image may be displayed via a display device. Examples of a display device include, but are not limited to, a liquid crystal display (LCD), a cathode ray tube (CRT), a plasma display, and any combinations thereof.

FIG. 3illustrates one embodiment of a timing analysis300. In one example, timing analysis may be performed as part of a multi-corner timing analysis (e.g., multi-corner timing analysis of step115ofFIG. 1) and may utilize, as set forth below, a variable slack cutoff scheme (e.g., variable slack cutoff scheme as determined by step110ofFIG. 1, variable slack cutoff scheme200ofFIG. 2).

At step305, a starting corner timing analysis is performed to determine a starting corner slack value for each of one or more paths in an integrated circuit design. A starting corner may be any corner and is usually chosen to result in somewhat pessimistic slack values. In one example, a starting corner may be a corner that will give a slowest path delay in a worst case (WC) timing test. In another example, a starting corner may be a corner that will give a fastest path delay in a best case (BC) timing test. A timing analysis may include one or more levels of testing of the starting corner on the paths of the integrated circuit. Starting corner timing analysis may be performed on any number of paths of an integrated circuit design. In one example, starting corner timing analysis is performed on a single path of an integrated circuit design. In another example, starting corner timing analysis is performed on a subset of all of the paths of an integrated circuit design. In yet another example, starting corner timing analysis is performed on all paths of an integrated circuit design.

At step310, each starting corner slack value is compared to an initial slack cutoff to determine if the corresponding path has a starting corner slack value that fails the slack cutoff. In one example, the initial slack cutoff is any slack cutoff estimating an upper bound on the slack change of any path going from the starting corner to any other corner of a full process space of parameters to be analyzed. In another example, the initial slack cutoff is a slack cutoff (c1) of a variable slack cutoff scheme (e.g., variable slack cutoff scheme200).

At step315, any path that passes the initial slack cutoff is passed to step320. At step320, further multi-corner analysis for paths that pass the initial slack cutoff may be bypassed. In one example, paths that are bypassed for further analysis at step320are paths that are likely to pass timing verification for all corners of the full process space. Any path that fails the initial slack cutoff (e.g., slack cutoff c1) is passed to step325for further analysis. Passing or failing a cutoff may depend on the precision of the determination of the cutoff upper bound (e.g., if the upper bound itself includes slack values that should pass, analysis will be to those slack values that are greater than or equal to the slack cutoff; if the upper bound itself includes slack values that should not pass, analysis will be to those slack values that are greater than the slack cutoff). In one example, a path having a slack value that is greater than or equal to a slack cutoff may pass the cutoff (e.g., a path that is determined to be likely to pass all corners of a timing test may require no further analysis). In such an example, a path having a slack value that is less than a slack cutoff will fail the cutoff. In another example, a path having a slack value that is greater than a slack cutoff may pass the cutoff. In such an example, a path having a slack value that is less than or equal to a slack cutoff will fail the cutoff.

Steps325through360, as described below, may iterate depending on the number of parameters (Pi) utilized in a particular analysis. At step325, one or more remaining paths of the paths that failed the most recent slack cutoff comparison (e.g., for a first iteration of step325those paths that failed comparison of the starting corner slack with the initial slack cutoff) are further analyzed. This further analysis includes varying the next parameter Piin the parameter order of PI to Pnto obtain a slack value for each of its corner parameter values (e.g., one of the non-starting corner parameter 3-SIGMA extreme values). For a first iteration of step325, the next parameter Piwill be P1. For subsequent iterations of step325, the next parameter is the parameter Pithat occurs next in the parameter order. During this analysis, at step330, parameters that have not yet been varied are held at their starting corner parameter values and parameters that have been previously varied are held at the corner parameter value that caused the worst slack value for a path, as described below with respect to step335. In one example, a parameter Pimay have two corner parameter values (e.g., a minimum extreme and a maximum extreme) of which one is the starting corner parameter value. In such an example, parameter Piis moved off of its starting corner parameter value to its other corner parameter value and a slack is determined. The one or more paths that are analyzed starting at each iteration of step325may be all of the paths that failed the previous slack cutoff comparison of a subset of those paths that failed the previous slack cutoff comparison. Those of ordinary skill will recognize a variety of processes for selecting a subset of paths for testing. In one example, a plurality of paths of an integrated circuit design may lead to the same timing test point of the design (e.g., a plurality of paths leading to a single logical latch). In such an example, one or more of this plurality of paths may be tested for timing failure as representative of all of the paths leading to that timing test point (e.g., a path that is known to be likely to have the highest potential delay variation of the plurality of paths leading to a timing test point). The worst slack of this one or more selected paths may be used as representative of all of the paths leading to the timing test point. In another example, any path that has a worst slack value that is below a user-defined threshold (e.g., below zero) analysis on that path may be bypassed as the path is determined via the user-defined threshold to likely have a timing violation.

At step335, a worst slack value for Piis determined for each of the one or more remaining paths. A worst slack value is determined by finding the worst slack of the slacks produced at each corner parameter value for Pi.

At step340, for each of the remaining paths, the worst slack value for the varying of Piis compared with the slack cutoff ci+1of a variable slack cutoff scheme (e.g., a variable slack cutoff scheme as discussed above with respect toFIGS. 1 and 2). In one example, during a first iteration of step340, P1was varied at step325. In such an example, the worst slack for each path for the varying of P1to each of its corners is compared with slack cutoff c2. In another example, where P3was varied at step325, the worst slack for each path for the varying of P3to each of its corner parameter values is compared with slack cutoff c4.

At step345, each path that passes slack cutoff ci+1may be bypassed for further analysis at step320. Each path that fails slack cutoff ci+1is further analyzed through steps350and360as described below. At step350, it is determined if during the latest iteration of steps325to345the parameter Pn-1was varied. If parameter Pn-1was the most recent varied parameter, the iteration ends. Any remaining paths may be further analyzed with respect to varying of Pn to determine an additional worst slack value for each remaining path. Each additional worst slack value may be compared with a user-defined slack threshold (e.g., a signoff slack) to determine a timing verification for each additionally analyzed path. If parameter Pn-1has not yet been varied, step360is implemented. At step360, it is determined if all paths passed the last slack cutoff comparison. If all paths passed the last slack cutoff comparison, there are no remaining paths to be further analyzed and method300ends. If paths remain that failed the last slack cutoff comparison, step325is reiterated for the next parameter Piin the parameter order.

Referring again to steps325to360with respect to an example where number of parameters n=6, the following discussion will illustrate one example of implementation of steps325to360on a particular path. In this example, during the first iteration of step325to360, parameter P1is varied from its starting corner parameter value to each of its other corner parameter values while holding P2to P6at their respective starting corner parameter values. A worst slack for the path is determined for P1and compared to slack cutoff c2. If the worst slack passes slack cutoff c2, the analysis of the path ends. If the worst slack fails cutoff c2, the analysis continues. Since P1is not Pn-1(which in this example is P5) and for illustrative purposes we will describe a path that fails the latest slack cutoff comparison, iteration of steps325to360continue. During the next iteration, parameter P2is varied from its starting corner parameter value, parameter P1is held at its corner parameter value that generated the worst slack, and parameters P3to P6are held at their starting corner parameter values. A worst slack for the path is determined for P2and compared to slack cutoff c3. If the worst slack passes slack cutoff c3, the analysis of the path ends. If the worst slack fails cutoff c3, the analysis continues. During the next iteration, parameter P3is varied from its starting corner parameter value, parameters P1to P2are held at their corner that generated the worst slack, and parameters P4to P6are held at their starting corner values. A worst slack for the path is determined for P3and compared to slack cutoff c4. If the worst slack passes slack cutoff c4, the analysis of the path ends. If the worst slack fails cutoff c4, the analysis continues. During the next iteration, parameter P4is varied from its starting corner parameter value, parameters P1to P3are held at their corner parameter value that generated the worst slack, and parameters P5to P6are held at their starting corner parameter values. A worst slack for the path is determined for P4and compared to slack cutoff c5. If the worst slack passes slack cutoff c5, the analysis of the path ends. If the worst slack fails cutoff c5, the analysis continues. During the next iteration, parameter P5is varied from its starting corner parameter value, parameters P1to P4are held at their corner parameter value that generated the worst slack, and parameter P6is held at its starting corner parameter value. A worst slack for the path is determined for P5and compared to slack cutoff c6. If the worst slack passes slack cutoff c6, the analysis of the path ends at step350with the timing verification for the path passing. If the worst slack fails cutoff c6, the iteration ends. Such paths that fail cutoff c6may be further analyzed by varying parameter P6while holding parameters P1to P5at the corner parameter values that generated the worst slack. The worst slack in varying P6may be compared to a user-defined threshold to determine a timing verification for each path.

FIG. 4illustrates yet another embodiment of a method400. At step405of method400, an n number of dependent parameters (Pi) are determined. Each of the dependent parameters Pihas a determinable impact on variability of timing. A dependent parameter is a parameter that has an impact on variability of timing that depends on another parameter in a process space (e.g., a process space {P1, P2, . . . Pn}). An independent parameter is a parameter that has an impact on variability of timing that can be analyzed in a timing analysis irrespective of other parameter values. Timing analysis utilizing the corner parameter values of independent parameters may be executed one parameter at a time without attention to parameter combinations (reducing the impact on runtime due to the 2ncombination problem). In one exemplary aspect of method400, a parameter order for dependent parameters (e.g., the parameter order discussed below with respect to step410) may be determined that allows a pseudo-independent treatment to occur during multi-corner timing analysis. An example of such a treatment is set forth below with respect toFIG. 5.

In an alternative embodiment, a parameter order may include n number of dependent parameters Pifrom P1to Pnand one or more independent parameters. In such an embodiment, the n number of dependent parameters Pimay be arranged in descending order of impact on variability of timing as described above with respect to step410. The one or more independent parameters may be added to the parameter order after the last dependent parameter Pn. In another alternative embodiment, one or more of the dependent parameters Pithat are arranged in the decreasing parameter order as described above with respect to step410may be repeated in the parameter order after the last dependent parameter Pn.

FIG. 5illustrates one embodiment of a multi-corner timing analysis500that may utilize a decreasing parameter order as described with respect toFIG. 4. Analysis500includes at step505, conducting a starting corner timing analysis to determine a starting corner slack value for each path of one or more predetermined paths of an integrated circuit design. For example, each dependent parameter Piin a parameter order may be set to a starting parameter value (e.g., the starting corner). The parameter order in this embodiment is such that the parameters are ordered in decreasing order of impact on variability of timing. As discussed above, an optional example may include one or more independent parameters and/or a repeat of one or more of dependent parameters P1to Pnarranged in the parameter order after the last parameter Pnin the decreasing variability portion of the parameter order. At step510, parameter P1is varied to a non-starting corner to determine a non-starting corner slack value for each path that is to be analyzed. The non-starting corner slack value for each path is compared to the corresponding starting corner slack value to determine a worst slack value for each path. Steps520to540of method500may iterate as described below depending on the number of parameters (Pi) utilized in a particular analysis.

At step540, it is determined if the last parameter in the parameter order has been varied. If the last parameter has not been varied during the last iteration of step520, step520is iterated again for the next parameter Piin the parameter order. If the last parameter has been varied during the last iteration of step520, the most recently updated value for the worst slack for each path is output at step545as a final worst slack value. Various types of outputs are discussed above. Each final worst slack value may be utilized to determine a timing verification for a corresponding path. In one example, a final worst slack value may be compared with a user-defined threshold (e.g., a signoff slack value) to determine an indication of timing verification.

Referring again to steps510to540with respect to an example where the number of dependent parameters n=6, the following discussion will illustrate one example of implementation of steps510to540on a particular path. At step510, parameter P1is varied to its non-starting corner parameter value and a non-starting corner slack is determined for each path. At step515, the non-starting corner slack is compared to the starting corner slack to determine a worst slack value for the varying of parameter P1. At the first iteration of step520, parameter P2is varied to a non-starting corner parameter value while holding parameter P1at its corner parameter value that produced the worst slack value determined at step515and holding parameters P3to P6at their starting corner parameter values. At step530, a non-starting corner slack is determined for each path for the varying of parameter P2. At step535, this non-starting corner slack is compared to the worst slack value for the varying of parameter P1. A new worst slack value is determined from these two values. Step520iterates for parameter P3. At this iteration of step520, parameter P3is varied to a non-starting corner parameter value while holding parameters P1and P2at their respective corner parameter values that produced the worst slack value determined at the prior iterations and holding parameters P4to P6at their starting corner parameter values. At step530, a non-starting corner slack is determined for each path for the varying of parameter P3. At step535, this non-starting corner slack is compared to the worst slack value for the varying of parameter P2. A new worst slack value is determined from these two values. Step520iterates for parameter P4. At this iteration of step520, parameter P4is varied to a non-starting corner parameter values while holding parameters P1to P3at their respective corner parameter values that produced the worst slack value determined at the prior iterations and holding parameters P5to P6at their starting corner parameter values. At step530, a non-starting corner slack is determined for each path for the varying of parameter P4. At step535, this non-starting corner slack is compared to the worst slack value for the varying of parameter P3. A new worst slack value is determined from these two values. Step520iterates for parameter P5. At this iteration of step520, parameter P5is varied to a non-starting corner parameter value while holding parameters P1to P4at their respective corner parameter values that produced the worst slack value determined at the prior iterations and holding parameter P6at its starting corner parameter value. At step530, a non-starting corner slack is determined for each path for the varying of parameter P5. At step535, this non-starting corner slack is compared to the worst slack value for the varying of parameter P4. A new worst slack value is determined from these two values. Step520iterates for parameter P6. At this iteration of step520, parameter P6is varied to a non-starting corner parameter value while holding parameters P1to P5at their respective corner parameter values that produced the worst slack value determined at the prior iterations. At step530, a non-starting corner slack is determined for each path for the varying of parameter P6. At step535, this non-starting corner slack is compared to the worst slack value for the varying of parameter P5. A new worst slack value is determined from these two values. This worst slack value is output at step545as a final worst slack value.

It is to be noted that the aspects and embodiments described herein may be conveniently implemented using one or more machines (e.g., a general purpose computing device) programmed according to the teachings of the present specification, as will be apparent to those of ordinary skill in the computer art. For example, various aspects of a method of reducing processing time in multi-corner static timing analysis, such as methods100,300,400,500may be implemented as machine-executable instructions (i.e., software coding), such as program modules executed by one or more machines. Typically a program module may include routines, programs, objects, components, data structures, etc. that perform specific tasks. Appropriate machine-executable instructions can readily be prepared by skilled programmers based on the teachings of the present disclosure, as will be apparent to those of ordinary skill in the software art.

Such software may be a computer program product that employs a machine-readable medium. A machine-readable medium may be any medium that is capable of storing and/or encoding a sequence of instructions for execution by a machine (e.g., a general purpose computing device) and that causes the machine to perform any one of the methodologies and/or embodiments described herein. Examples of a machine-readable medium include, but are not limited to, a magnetic disk (e.g., a conventional floppy disk, a hard drive disk), an optical disk (e.g., a compact disk “CD”, such as a readable, writeable, and/or re-writable CD; a digital video disk “DVD”, such as a readable, writeable, and/or rewritable DVD), a magneto-optical disk, a read-only memory “ROM” device, a random access memory “RAM” device, a magnetic card, an optical card, a solid-state memory device (e.g., a flash memory), an EPROM, an EEPROM, and any combinations thereof. A machine-readable medium, as used herein, is intended to include a single medium as well as a collection of physically separate media, such as, for example, a collection of compact disks or one or more hard disk drives in combination with a computer memory.

Examples of a general purpose computing device include, but are not limited to, a computer workstation, a terminal computer, a server computer, a handheld device (e.g., tablet computer, a personal digital assistant “PDA”, a mobile telephone, etc.), a web appliance, a network router, a network switch, a network bridge, any machine capable of executing a sequence of instructions that specify an action to be taken by that machine, and any combinations thereof. In one example, a general purpose computing device may include and/or be included in, a kiosk.

FIG. 6shows a diagrammatic representation of one embodiment of a general purpose computing device in the exemplary form of a computer system600within which a set of instructions for causing the device to perform any one or more of the aspects and/or methodologies of the present disclosure may be executed. Computer system600includes a processor605and a memory610that communicate with each other, and with other components, via a bus615. Bus615may include any of several types of bus structures including, but not limited to, a memory bus, a memory controller, a peripheral bus, a local bus, and any combinations thereof, using any of a variety of bus architectures.

Memory610may include various components (e.g., machine readable media) including, but not limited to, a random access memory component (e.g, a static RAM “SRAM”, a dynamic RAM “DRAM”, etc.), a read only component, and any combinations thereof. In one example, a basic input/output system620(BIOS), including basic routines that help to transfer information between elements within computer system600, such as during start-up, may be stored in memory610. Memory610may also include (e.g., stored on one or more machine-readable media) instructions (e.g., software)625embodying any one or more of the aspects and/or methodologies of the present disclosure. In another example, memory610may further include any number of program modules including, but not limited to, an operating system, one or more application programs, other program modules, program data, and any combinations thereof.

Computer system600may also include a storage device630. Examples of a storage device (e.g, storage device630) include, but are not limited to, a hard disk drive for reading from and/or writing to a hard disk, a magnetic disk drive for reading from and/or writing to a removable magnetic disk, an optical disk drive for reading from and/or writing to an optical media (e.g., a CD, a DVD, etc.), a solid-state memory device, and any combinations thereof. Storage device630may be connected to bus615by an appropriate interface (not shown). Example interfaces include, but are not limited to, SCSI, advanced technology attachment (ATA), serial ATA, universal serial bus (USB), IEEE 1394 (FIREWIRE), and any combinations thereof. In one example, storage device630may be removably interfaced with computer system600(e.g., via an external port connector (not shown)). Particularly, storage device630and an associated machine-readable medium635may provide nonvolatile and/or volatile storage of machine-readable instructions, data structures, program modules, and/or other data for computer system600. In one example, software625may reside, completely or partially, within machine-readable medium635. In another example, software625may reside, completely or partially, within processor605.

Computer system600may also include an input device640. In one example, a user of computer system600may enter commands and/or other information into computer system600via input device640. Examples of an input device640include, but are not limited to, an alpha-numeric input device (e.g., a keyboard), a pointing device, a joystick, a gamepad, an audio input device (e.g., a microphone, a voice response system, etc.), a cursor control device (e.g., a mouse), a touchpad, an optical scanner, a video capture device (e.g., a still camera, a video camera), touchscreen, and any combinations thereof. Input device640may be interfaced to bus615via any of a variety of interfaces (not shown) including, but not limited to, a serial interface, a parallel interface, a game port, a USB interface, a FIREWIRE interface, a direct interface to bus615, and any combinations thereof.

A user may also input commands and/or other information to computer system600via storage device630(e.g., a removable disk drive, a flash drive, etc.) and/or a network interface device645. A network interface device, such as network interface device645may be utilized for connecting computer system600to one or more of a variety of networks, such as network650, and one or more remote devices655connected thereto. Examples of a network interface device include, but are not limited to, a network interface card, a modem, and any combination thereof. Examples of a network or network segment include, but are not limited to, a wide area network (e.g., the Internet, an enterprise network), a local area network (e.g., a network associated with an office, a building, a campus or other relatively small geographic space), a telephone network, a direct connection between two computing devices, and any combinations thereof. A network, such as network650, may employ a wired and/or a wireless mode of communication. In general, any network topology may be used. Information (e.g., data, software625, etc.) may be communicated to and/or from computer system600via network interface device645.

Computer system600may further include a video display adapter660for communicating a displayable image to a display device, such as display device665. Examples of a display device include, but are not limited to, a liquid crystal display (LCD), a cathode ray tube (CRT), a plasma display, and any combinations thereof. In addition to a display device, a computer system600may include one or more other peripheral output devices including, but not limited to, an audio speaker, a printer, and any combinations thereof. Such peripheral output devices may be connected to bus615via a peripheral interface670. Examples of a peripheral interface include, but are not limited to, a serial port, a USB connection, a FIREWIRE connection, a parallel connection, and any combinations thereof.

A digitizer (not shown) and an accompanying pen/stylus, if needed, may be included in order to digitally capture freehand input. A pen digitizer may be separately configured or coextensive with a display area of display device665. Accordingly, a digitizer may be integrated with display device665, or may exist as a separate device overlaying or otherwise appended to display device665.

In one exemplary aspect, a method of reducing processing time in multi-corner static timing analysis, such as methods100,200,300,400, may significantly reduce the runtime of a multi-corner timing analysis.