Arithmetic optimization techniques for hardware and software by Ryan Kastner

By Ryan Kastner

''Obtain greater process functionality, reduce strength intake, and keep away from hand-coding mathematics capabilities with this concise consultant to automatic optimization recommendations for and software program layout. High-level compiler optimizations and high-speed architectures for enforcing FIR filters are lined, that may increase functionality in communications, sign processing, special effects, and cryptography. Clearly Read more...

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Arithmetic optimizations are applicable when writing software as well as during the design of hardware components. This chapter gives a high-level overview of the software compilation process. We start by describing the basic structure of a modern compiler. Then we provide more detail about the compilation process including the place where arithmetic optimizations can be implemented. Finally, we describe the algebraic transformations that are used in current compilers. These include dataflow optimization, CSE, value numbering, loop invariant code motion, partial redundancy elimination (PRE), operator strength reduction, and the Horner form.

5 as described in the work by Gong et al. [20]. Scheduling, resource allocation, and binding can further optimize the description, as we describe in the following. 5 Algorithmic optimization Algorithmic optimizations use a set of techniques aimed at transforming the program representation in a manner that improves the performance of the application. For the most part, these are traditional optimizations typically used in software compilers. The term “optimization” is somewhat of a misnomer in that these techniques rarely find an optimal solution; rather they are aimed at enhancing some aspect of performance.

Kennedy and J. R. Allen, Optimizing Compilers for Modern Architectures: A Dependence-based Approach. San Francisco, CA: Morgan Kaufmann Publishers, 2001. [3] J. R. Levine, T. Mason, and D. Brown, Lex & yacc, second edition. Sebastopol, CA: O’Reilly & Associates, 1995. [4] J. Cocke and J. T. Schwartz, Programming Languages and Their Compilers: Preliminary Notes, Technical Report, Courant Institute of Mathematical Sciences, New York University, 1970. [5] J. R. Reif and H. R. Lewis, Symbolic evaluation and the global value graph, Proceedings of the 4th ACM SIGACT-SIGPLAN Symposium on Principles of Programming Languages, Los Angeles, 1977, pp.

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