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In this paper, we present a bit-parallel multiplier for GF(2m) defined by an irreducible pentanomial ixm + xk3 + xk2 + xk1 + 1, where 1 ≤ k1 < k2 < k3 ≤ m/2. In order to design an efficient bit-parallel multiplier, we introduce a shifted polynomial basis and modify a reduction matrix presented by Reyhani-Masoleh and Hasan. As a result, the time complexity of the proposed multiplier is TA + (3 + [log2(m - 1)])Tx, where TA and Tx are the delay of one AND and one XOR gate, respectively. This result matches or outperforms the previously known results. On the other hand, the proposed multiplier has the same space complexity as the previously known multipliers except for special types of irreducible pentanomials. Note that its hardware architecture is similar to that presented by Reyhani-Masoleh and Hasan. [ABSTRACT FROM AUTHOR]

A Taylor Expansion Diagram (TED) is a compact, word-level, canonical representation for data flow computations that can be expressed as multivariate polynomials. TEDs are based on a decomposition scheme using Taylor series expansion that allows one to model word-level signals as algebraic symbols. This power of abstraction, combined with the canonicity and compactness of TED, makes it applicable to equivalence verification of dataflow designs. The paper describes the theory of TEDs and proves their canonicity. It shows how to construct a TED from an HDL design specification and discusses the application of TEDs in proving the equivalence of such designs. Experiments were performed with a variety of designs to observe the potential and limitations of TEDs for dataflow design verification. Application of TEDs to algorithmic and behavioral verification is demonstrated. [ABSTRACT FROM AUTHOR]