Method and system for implementing parallel execution in a computing system and in a circuit simulator

• US 8,224,636 B2
• Filed: 12/17/2003
• Issued: 07/17/2012
• Est. Priority Date: 12/17/2002
• Status: Active Grant

• Current Assignee: Cadence Design Systems Incorporated (Cadence Group)
• Original Assignee: Cadence Design Systems Incorporated (Cadence Group)
• Inventors: Kundert, Kenneth S.
• Primary Examiner(s): Patel, Shambhavi
• Application Number:
  US10/739,876
• Publication Number:
  US 20040261058A1
• Time in Patent Office: 3,135 Days
• Field of Search: 703/14, 703/2, 703/13, 703/15, 703/21, 703/22, 703/23, 716/103, 716/104, 716/132, 716/139, 717/150, 717/154, 717/160, 717/161
• US Class Current: 703/14
• CPC Class Codes: G01R 31/318357 Simulation computer simulation of digital circuits G06F30/3308
• CPC Class Codes: G01R 31/318364 as a result of hardware simulation, e.g. in an HDL environment computer-aided simulation of circuits G06F30/3308
• CPC Class Codes: G06F 11/261 by simulating additional hardware, e.g. fault simulation
• CPC Class Codes: G06F 13/105 where the programme performs an input/output emulation function
• CPC Class Codes: G06F 30/00 Computer-aided design [CAD]
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30
• CPC Class Codes: G06F 30/33 Design verification, e.g. functional simulation or model checking
• CPC Class Codes: G06F 30/3308 using simulation
• CPC Class Codes: G06F 30/367 Design verification, e.g. using simulation, simulation program with integrated circuit emphasis [SPICE], direct methods or relaxation methods

Abstract

A method and mechanism for implementing a general purpose scripting language that supports parallel execution is described. In one approach, parallel execution is provided in a seamless and high-level approach rather than requiring or expecting a user to have low-level programming expertise with parallel processing languages/functions. Also described is a system and method for performing circuit simulation. The present approach provides methods and systems that create reusable and independent measurements for use with circuit simulators. Also disclosed are parallelizable measurements having looping constructs that can be run without interference between parallel iterations. Reusability is enhanced by having parameterized measurements. Revisions and history of the operating parameters of circuit designs subject to simulation are tracked.

Claims

1. A computer program product comprising a memory having an iterative looping construct that, when executed by at least one computer, causes the at least one computer to performs a process of implementing the iterative looping construct, the process comprises:

using the at least one computer that comprises at least one processor to perform a process, the process comprising;

beginning loop processing;

creating an independent processing environment of multiple independent processing environments for each of multiple iterates in the iterative looping construct;

implementing the iterative looping construct by performing independent parallel iterations of activities for the loop processing within each of the multiple independent processing environments for each of the multiple iterates to simulate or emulate one or more activities of an electronic circuit over a range of parameter values that is provided to a measurement for the electronic circuit during at least some of the independent parallel iterations in the loop processing, without using serial looping constructs, wherein

the measurement is associated with a dataset that is stored independently to maintain independence of measurements,

the activities comprise one or more tasks identified in the loop processing, and

either an access to an index variable for the loop processing is removed, or the loop processing is performed without defining the index variable so the loop processing is performed without reference to the index variable during the loop processing;

resizing an N-dimensional array according to a total number of the multiple iterates in the iterative looping construct; and

knitting the dataset generated within the iterative looping construct, into a hierarchical collection of datasets to retain a hierarchical characteristic of a sub-measurement in a measurement.

2. The computer program product of claim 1 in which the iterative looping construct captures all variables that are declared outside the loop and assigned within the loop.

3. The computer program product of claim 2 in which a scalar captured by the loop corresponds to an original value when the loop is entered, and wherein the scalar is reset to the original value on every iteration unless acted upon by an incremental assignment operator.

4. The computer program product of claim 3 in which the scalar corresponds to scalar variables from a simulation control language.

5. The computer program product of claim 3 in which the scalar corresponds to circuit parameters or simulator options.

6. The computer program product of claim 2 in which a scalar captured by the loop corresponds to an original value when the loop is entered, and wherein scalars captured by an incremental assignment operator are not returned to the original value upon exiting the loop.

7. The computer program product of claim 6 in which incremental assignment operators correspond to +=, −

=, *=, or /=.

8. The computer program product of claim 6 in which a final value for the scalars captured by the incremental assignment operator is the results if all of the incremental operations were performed upon exit from the loop.

9. The computer program product of claim 2 in which a vector captured by the loop is resized to contain a same number of elements as the multiple iterates in the loop.

10. The computer program product of claim 9 in which each of the same number of elements of the captured vector corresponds to an iterate of the multiple iterates.

11. The computer program product of claim 9 in which an iterate cannot access any element in the vector except the one to which it corresponds.

12. The computer program product of claim 2 in which an array captured by the loop processing is visible as having one lower dimension within the loop processing than outside the loop processing.

13. The computer program product of claim 12 in which the one lower dimension within the loop processing is resized to have same number of elements as the multiple iterates in the loop processing.

14. The computer program product of claim 13 in which a one-dimensional vector captured by the loop processing is visible as a scalar inside the loop.

15. The computer program product of claim 1 in which the iterative looping construct iterates over corner sets.

16. The computer program product of claim 1 in which the iterative looping construct, on an iteration, attaches a value of a loop variable for an iterate to an element associated with the iterate for each vector captured by the loop processing, in which the loop variable is declared outside the loop processing and is assigned the value inside the loop processing.

17. The computer program product of claim 1 in which an iterate index and a total iteration count are attached to a loop variable as attributes.

18. The computer program product of claim 1 in which the iterative looping construct knits one or more datasets generated within the loop into a family of datasets, in which the one or more datasets generated within the loop processing are combined to add dimensions to at least one of the one or more datasets.

19. The computer program product of claim 1 in which the iterative looping construct runs each iterate in parallel without interference between the multiple of iterates.

20. The computer program product of claim 1 in which data values from parallel iterates are combined together.

21. The computer program product of claim 1 in which the iterative looping construct corresponds to a Foreach loop, wherein the Foreach loop is used to iteratively perform at least some of the activities for the loop processing.

22. The computer program product of claim 21 in which an output is an array of data over a range of a loop variable.

23. The computer program product of claim 21 in which the Foreach loop comprises a following form:

24. The computer program product of claim 21 in which the Foreach loop comprises a following form:

25. The computer program product of claim 21 in which the Foreach loop comprises a following format:

26. The computer program product of claim 1 in which the iterative looping construct comprises a search loop.

27. The computer program product of claim 26 in which the search loop comprises a following form:

28. The computer program product of claim 27 in which the first member is a target value of the iterate and the list is given as a vector of values, wherein the loop search begins at the first member of the list and continues towards an end of the list until the search loop finds the first member that results in the condition being true.

29. The computer program product of claim 26 in which the search loop comprises a following form:

30. The computer program product of claim 26 in which one or more members of the list are determined dynamically during a search based on a progress of the search.

31. The computer program product of claim 26 in which a binary search is performed.

32. The computer program product of claim 1 in which the iterative looping construct performs Monte Carlo analysis to analyze a random variable in the iterative looping construct.

33. The computer program product of claim 32 in which a number of trials in the Monte Carlo analysis is determined dynamically based at least in part on statistically evaluating results of the Monte Carlo analysis.

34. The computer program product of claim 33 in which the trials are determined dynamically, and the number of trials indicates a number of iterations in the Monte Carlo Analysis.

35. The computer program product of claim 1 further comprising re-dimensioning one or more arrays associated with the loop processing, in which the act of re-dimensioning adds a dimension to at least one of the one or more arrays by combining the at least one of the one or more arrays and another array of the one or more arrays.

36. The computer program product of claim 1 in which each of the independent parallel iterations is completely independent from other iterations.

37. The computer program product of claim 36 in which any particular iterate cannot access results computed by another iterate.

38. The computer program product of claim 1 in which the independent parallel iterations of the activities comprise simulation activities.

39. The computer program product of claim 1 in which the iterative looping construct is executed in a scripting language.

40. The computer program product of claim 1 further comprising restoring a scalar value for the loop processing to an initial value when the loop processing is entered on an iteration.

41. A computer implemented method for implementing an iterative looping construct, the computer implemented method comprising:

using the at least one computer that comprises at least one processor to perform a process, the process comprising;

beginning loop processing;

creating an independent processing environment of multiple processing environments for each of multiple iterates in the iterative looping construct;

implementing the iterative looping construct by performing independent parallel iterations of activities for the loop processing within each of the multiple independent processing environments for each of the multiple iterates to simulate or emulate one or more activities of an electronic circuit over a range of parameter values that is provided to a measurement for the electronic circuit during at least some of the independent parallel iterations in the loop processing without using serial looping constructs, wherein

the measurement is associated with a dataset that is stored independently to maintain independence of measurements,

the activities comprise one or more tasks identified in the loop processing, and

either an access to an index variable for the loop processing is removed, or the loop processing is performed without defining the index variable so the loop processing is performed without reference to the index variable during the loop processing;

resizing an N-dimensional array according to a total number of the multiple iterates in the iterative looping construct; and

knitting the dataset generated within the iterative looping construct, into a hierarchical collection of datasets to retain a hierarchical characteristic of a sub-measurement in a measurement.

43. The computer implemented method of claim 41, in which one or more scalars are returned to their respective initial value upon exiting the loop processing.

44. The computer implemented method of claim 41, in which one or more scalars captured by an incremental assignment operator are not returned to their respective initial value upon exiting the loop processing.

42. A system for executing a list of tasks in parallel, the method comprising:

one or more processors that is to;

begin loop processing;

create an independent processing environment of multiple independent processing environments for each of multiple iterates in the iterative looping construct;

implement the iterative looping construct by performing independent parallel iterations of activities for the loop processing within each of the multiple independent processing environments for each of the multiple iterates to simulate or emulate one or more activities of an electronic circuit over a range of parameter values that is provided to a measurement for the electronic circuit during at least some of the independent parallel iterations in the loop processing by using the iterative looping construct without using serial looping constructs, in which

the measurement is associated with a dataset that is stored independently to maintain independence of measurements,

the activities comprise one or more tasks identified in the loop processing, and

either an access to an index variable for the loop processing is removed, or the loop processing is performed without defining the index variable so the loop processing is performed without reference to the index variable during the loop processing,

resize an N-dimensional array according to a total number of the multiple iterates in the iterative looping construct; and

knit the dataset generated within the iterative looping construct, into a hierarchical collection of datasets to retain a hierarchical characteristic of a sub-measurement in a measurement.

45. The system of claim 42, in which an array captured by the loop processing comprises one lower dimension within the loop processing than outside the loop processing.

46. The system of claim 42, in which the iterative looping construct comprises an independent parameterized measurement that is used to measure one or more performance characteristics of an electronic circuit.