Doctor of Philosophy

dissertationAbstraction plays an important role in digital design, analysis, and verification, as it allows for the refinement of functions through different levels of conceptualization. This dissertation introduces a new method to compute a symbolic, canonical, word-level abstraction of the function implemented by a combinational logic circuit. This abstraction provides a representation of the function as a polynomial Z = F(A) over the Galois field F2k , expressed over the k-bit input to the circuit, A. This representation is easily utilized for formal verification (equivalence checking) of combinational circuits. The approach to abstraction is based upon concepts from commutative algebra and algebraic geometry, notably the Grobner basis theory. It is shown that the polynomial F(A) can be derived by computing a Grobner basis of the polynomials corresponding to the circuit, using a specific elimination term order based on the circuits topology. However, computing Grobner bases using elimination term orders is infeasible for large circuits. To overcome these limitations, this work introduces an efficient symbolic computation to derive the word-level polynomial. The presented algorithms exploit i) the structure of the circuit, ii) the properties of Grobner bases, iii) characteristics of Galois fields F2k , and iv) modern algorithms from symbolic computation. A custom abstraction tool is designed to efficiently implement the abstraction procedure. While the concept is applicable to any arbitrary combinational logic circuit, it is particularly powerful in verification and equivalence checking of hierarchical, custom designed and structurally dissimilar Galois field arithmetic circuits. In most applications, the field size and the datapath size k in the circuits is very large, up to 1024 bits. The proposed abstraction procedure can exploit the hierarchy of the given Galois field arithmetic circuits. Our experiments show that, using this approach, our tool can abstract and verify Galois field arithmetic circuits up to 1024 bits in size. Contemporary techniques fail to verify these types of circuits beyond 163 bits and cannot abstract a canonical representation beyond 32 bits

A new class of array codes for memory storage

Abstract-In this article we describe a class of error control codes called "diff-MDS" codes that are custom designed for highly resilient computer memory storage. The error scenarios of concern range from simple single bit errors, to memory chip failures and catastrophic memory module failures. Our approach to building codes for this setting relies on the concept of expurgating a parity code that is easy to decode for memory module failures so that a few additional small errors can be handled as well, thus preserving most of the decoding complexity advantages of the original code while extending its original intent. The manner in which we expurgate is carefully crafted so that the strength of the resulting code is comparable to that of a Reed-Solomon code when used for this particular setting. An instance of this class of algorithms has been incorporated in IBM's zEnterprise mainframe offering, setting a new industry standard for memory resiliency