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A common application of generative programming is building high performance computational kernels highly tuned to the problem at hand. A typical linear algebra kernel is specialized to the numerical domain (rational, float, double, etc.), loop unrolling factors, array layout and a priori knowledge (e.g., the matrix being positive definite). It is tedious and error prone to specialize by hand, writing numerous variations of the same algorithm. The widely used generators such as ATLAS and SPIRAL reliably produce highly tuned specialized code but are difficult to extend. In ATLAS, which generates code using printf, even balancing parentheses is a challenge. According to the ATLAS creator, debugging is nightmare. A typed staged programming language such as MetaOCaml lets us state a general, obviously correct algorithm and add layers of specializations in a modular way. By ensuring that the generated code always compiles and letting us quickly test it, MetaOCaml makes writing generators less daunting and more productive. The readers will see it for themselves in this hands-on tutorial. Assuming no prior knowledge of MetaOCaml and only a basic familiarity with functional programming, we will eventually implement a simple domain-specific language (DSL) for linear algebra, with layers of optimizations for sparsity and memory layout of matrices and vectors, and their algebraic properties. We will generate optimal BLAS kernels. We shall get the taste of the "Abstraction without guilt".

Generative programming (Computer science)

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This book constitutes the proceedings of the 13th International Symposium on Functional and Logic Programming, FLOPS 2016, held in Kochi, Japan, in March 2016. The 14 papers presented in this volume were carefully reviewed and selected from 36 submissions. They cover the following topics: functional and logic programming; program transformation and re-writing; and extracting programs from proofs of their correctness. .

Computer Science --- Engineering & Applied Sciences --- Computer science. --- Computer programming. --- Software engineering. --- Programming languages (Electronic computers). --- Computer logic. --- Mathematical logic. --- Artificial intelligence. --- Computer Science. --- Software Engineering. --- Logics and Meanings of Programs. --- Programming Languages, Compilers, Interpreters. --- Mathematical Logic and Formal Languages. --- Artificial Intelligence (incl. Robotics). --- Programming Techniques. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Algebra of logic --- Logic, Universal --- Mathematical logic --- Symbolic and mathematical logic --- Symbolic logic --- Mathematics --- Algebra, Abstract --- Metamathematics --- Set theory --- Syllogism --- Computer science logic --- Logic, Symbolic and mathematical --- Computer languages --- Computer program languages --- Computer programming languages --- Machine language --- Languages, Artificial --- Computer software engineering --- Engineering --- Computers --- Electronic computer programming --- Electronic digital computers --- Programming (Electronic computers) --- Coding theory --- Informatics --- Science --- Programming --- Logic design. --- Artificial Intelligence. --- Design, Logic --- Design of logic systems --- Digital electronics --- Electronic circuit design --- Logic circuits --- Switching theory --- Functional programming (Computer science) --- Compilers (Computer programs). --- Machine theory. --- Computer Science Logic and Foundations of Programming. --- Compilers and Interpreters. --- Formal Languages and Automata Theory. --- Abstract automata --- Abstract machines --- Automata --- Mathematical machine theory --- Algorithms --- Recursive functions --- Robotics --- Compiling programs (Computer programs) --- Computer programs --- Programming software --- Systems software

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The goal of The Reasoned Schemer is to help the functional programmer think logically and the logic programmer think functionally. The authors of The Reasoned Schemer believe that logic programming is a natural extension of functional programming, and they demonstrate this by extending the functional language Scheme with logical constructs -- thereby combining the benefits of both styles. The extension encapsulates most of the ideas in the logic programming language Prolog.The pedagogical method of The Reasoned Schemer is a series of questions and answers, which proceed with the characteristic humor that marked The Little Schemer and The Seasoned Schmer. Familiarity with a functional language or with the first eight chapters of The Little Schemer is assumed. Adding logic capabilities required the introduction of new forms. The authors' goal is to show to what extent writing logic programs is the same as writing functional programs using these forms. In this way, the reader of The Reasoned Schemer will come to understand how simple logic programming is and how easy it is to define functions that behave like relations.

Scheme (Computer program language)