Abstract: A method for quantifying and analyzing intrinsic parallelism of an algorithm is adapted to be implemented by a computer, and includes the steps of: configuring the computer to represent the algorithm by means of a plurality of operation sets; configuring the computer to obtain a Laplacian matrix according to the operation sets; configuring the computer to compute eigenvalues and eigenvectors of the Laplacian matrix; and configuring the computer to obtain a set of information related to intrinsic parallelism of the algorithm according to the eigenvalues and the eigenvectors of the Laplacian matrix.

Abstract: A method of analyzing intrinsic parallelism of an algorithm, comprising: generating a dataflow graph which is composed of vertexes representing computation and directed edges denoting the dependency and flow of data from the algorithm; building a matrix representing the dataflow graph; and quantifying the intrinsic parallelism based on rank and dimension of the matrix representing the generated dataflow graph.

Abstract: A method of determining a design framework is implemented by an algorithm analyzer. The method includes configuring the algorithm analyzer to perform intrinsic complexity analysis of an algorithm for a predetermined application to obtain a set of parameters representing intrinsic characteristics of the algorithm. The method also includes configuring the algorithm analyzer to establish candidate design frameworks based on the parameters. Each candidate design framework includes a set of design constraints corresponding to the algorithm and which are used when designing a hardware and/or software configuration for implementing the predetermined application. The method also includes configuring the algorithm analyzer to analyze the suitability of the set of design constraints of each candidate design framework based on given specification restrictions of the predetermined application to determine which candidate design framework(s) is suited for the predetermined application.

Abstract: A motion estimation method includes: (A) defining one pixel in a reference image as a center of search (CS) corresponding to a target pixel set in a current image; (B) determining a center error (CE) signal; (C) defining another pixel in the reference image as a target of search (TS) with reference to the CS, one candidate search vector available for selection from a vector set, and a step size; (D) determining a target error (TE) signal; (E) determining whether to update the CS and the CE signal; (F) if determined, updating the CS, the CE signal and the vector set; (G) repeating steps (C)˜(F) using a candidate search vector selected from the vector set and the same step size until there is no candidate search vector available for selection in the vector set; (H) repeating steps (C)˜(G) using a smaller step size until a predetermined value is reached; and (I) computing a motion vector based on the target pixel set and one pixel set that includes the CS.