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As the demand for high-quality Internet increases, emerging network applications are spurring the need for faster, feature-rich, and cost-effective routers. Multifield packet classification in routers has been a computation-intensive data path function for software implementation. Therefore, solutions for packet classification based on hardware design, such as Ternary Content Addressable Memory (TCAM), are necessary to sustain gigabit line processing rate. Traditionally, TCAMs have been designed for storing prefixes. However, multifield packet classification usually involves two fields of arbitrary ranges that are TCP/IP layer 4 source and destination ports. Storing ranges in TCAMs relies on decomposing each individual range into multiple prefixes, which leads to range-to-prefix blowout. To reduce the total number of prefixes needed to represent all ranges, this paper proposes a 2-level TCAM architecture and two range-to-prefix conversion schemes. In the first proposed scheme, designed for disjoint ranges, the maximum number of entries needed in TCAM is 2m - 1 for m disjoint ranges. In the second proposed scheme, designed for contiguous ranges, only m TCAM entries are needed. In a general case of n arbitrary ranges, all ranges can first be converted into disjoint ranges or contiguous ranges and then the proposed algorithms can be applied. As a result, only 4n - 3 TCAM entries are needed for the disjoint ranges and only 2n + 1 TCAM entries are needed for contiguous ranges. This paper also proposes insertion and deletion algorithms to accommodate incremental changes to the range sets. The experiments made show that the proposed range-to-prefix conversion schemes perform better than the existing schemes in terms of the number of required TCAM entries and execution time for range update operations. [ABSTRACT FROM AUTHOR]

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]