This document discusses how to program FPGAs using free and open source software tools. It explains what an FPGA is and how it works, and walks through examples of using Verilog to program simple logic gates and circuits on an FPGA board. These include turning on an LED, implementing a NAND gate in hardware, and using the FPGA as an interactive input/output device. The document promotes the IceStorm toolchain for programming Lattice FPGA boards and outlines several other hardware description languages and frameworks. It concludes by discussing future developments that could expand the use of open source FPGA programming.
This document summarizes a presentation about improvements to Gradle's daemon feature in version 3.0. The daemon runs as a long-lived background process to speed up builds. New features include the daemon being enabled by default, being more robust on Windows, and integrating with build scans. The daemon also becomes more resource-aware and intelligent over time through machine learning. Users are encouraged to try the new daemon features and provide feedback to further improve Gradle's performance.
Introduction to functional programming using Ocamlpramode_ce
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The document provides an introduction to functional programming concepts using Ocaml as the teaching language. It outlines the workshop plan which will cover Ocaml syntax, important functional programming concepts, and understanding the functional paradigm through Ocaml. It then discusses Ocaml background, where Ocaml is used, the Ocaml REPL, function definition, type inference, recursion, tail calls and TCO, higher order functions, algebraic data types, pattern matching, immutability, and more.
The document discusses Groovy programming, particularly its use in writing scripts that often resemble Java code. It contains code snippets illustrating the differences between Java and Groovy, specifically in terms of class definitions, getters and setters, and string manipulation. Additionally, it explores features such as dependency injection, data binding, and syntax simplifications that Groovy introduces to streamline Java-like development.
Scala is a programming language that runs on the JVM and fuses functional and object-oriented paradigms. It aims to provide functional programming for programmers with an imperative mindset. Key features include functions as first-class values, pattern matching, traits for composition, and seamless interoperability with Java. While some features appear to be language features, many are actually implemented via libraries. The Scala community is growing with adoption by companies and increasing support in tools and publications.
This document provides an overview of advanced features in Scala, focusing on concepts like higher kind projection, contravariant functors, and monadic composition. It discusses the implementation and significance of functions and types that enhance functional programming in Scala, particularly in the context of machine learning applications. The content also covers practical aspects such as streams, views, and the use of type classes to improve code reusability and design flexibility.
Introduction to Functional Programming with Scalapramode_ce
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The document provides an introduction to functional programming with Scala. It outlines the following topics that will be covered: learning Scala syntax and writing simple programs; important functional programming concepts like closures, higher-order functions, purity, lazy evaluation, currying, tail calls, immutability, and type inference; and understanding the functional programming paradigm through Scala. It also provides some background information on Scala and examples of Scala code demonstrating various concepts.
This document discusses how to program FPGAs using free and open source software tools. It explains what an FPGA is and how it works, and walks through examples of using Verilog to program simple logic gates and circuits on an FPGA board. These include turning on an LED, implementing a NAND gate in hardware, and using the FPGA as an interactive input/output device. The document promotes the IceStorm toolchain for programming Lattice FPGA boards and outlines several other hardware description languages and frameworks. It concludes by discussing future developments that could expand the use of open source FPGA programming.
This document summarizes a presentation about improvements to Gradle's daemon feature in version 3.0. The daemon runs as a long-lived background process to speed up builds. New features include the daemon being enabled by default, being more robust on Windows, and integrating with build scans. The daemon also becomes more resource-aware and intelligent over time through machine learning. Users are encouraged to try the new daemon features and provide feedback to further improve Gradle's performance.
Introduction to functional programming using Ocamlpramode_ce
?
The document provides an introduction to functional programming concepts using Ocaml as the teaching language. It outlines the workshop plan which will cover Ocaml syntax, important functional programming concepts, and understanding the functional paradigm through Ocaml. It then discusses Ocaml background, where Ocaml is used, the Ocaml REPL, function definition, type inference, recursion, tail calls and TCO, higher order functions, algebraic data types, pattern matching, immutability, and more.
The document discusses Groovy programming, particularly its use in writing scripts that often resemble Java code. It contains code snippets illustrating the differences between Java and Groovy, specifically in terms of class definitions, getters and setters, and string manipulation. Additionally, it explores features such as dependency injection, data binding, and syntax simplifications that Groovy introduces to streamline Java-like development.
Scala is a programming language that runs on the JVM and fuses functional and object-oriented paradigms. It aims to provide functional programming for programmers with an imperative mindset. Key features include functions as first-class values, pattern matching, traits for composition, and seamless interoperability with Java. While some features appear to be language features, many are actually implemented via libraries. The Scala community is growing with adoption by companies and increasing support in tools and publications.
This document provides an overview of advanced features in Scala, focusing on concepts like higher kind projection, contravariant functors, and monadic composition. It discusses the implementation and significance of functions and types that enhance functional programming in Scala, particularly in the context of machine learning applications. The content also covers practical aspects such as streams, views, and the use of type classes to improve code reusability and design flexibility.
Introduction to Functional Programming with Scalapramode_ce
?
The document provides an introduction to functional programming with Scala. It outlines the following topics that will be covered: learning Scala syntax and writing simple programs; important functional programming concepts like closures, higher-order functions, purity, lazy evaluation, currying, tail calls, immutability, and type inference; and understanding the functional programming paradigm through Scala. It also provides some background information on Scala and examples of Scala code demonstrating various concepts.
4. オブジェクト指向と
関数型の融合
Have the best of both worlds.
Construct elegant class hierarchies
for maximum code reuse and
extensibility, implement their behavior
using higher-order functions. Or
anything in-between.
— from http://www.scala-lang.org/
Object-Oriented Meets Functional
17. オブジェクト指向的コイン
case class OoCoin(private var head: Boolean) {
def flip() = { head = !head }
def stay() = {} // do nothing
def get = head
}
Object-Oriented Coin
18. オブジェクト指向的コイン
case class OoCoin(private var head: Boolean) {
def flip() = { head = !head }
def stay() = {} // do nothing
def get = head
}
var (variable) で宣言し
たフィールドに再代入
Object-Oriented Coin
19. val c = OoCoin(true)
c.flip()
c.stay()
c.flip()
println("Showing a head? " + c.get)
63. case class CoinAction[A](action: Coin => (Coin, A))
extends (Coin => (Coin, A)) {
def apply(c: Coin) = action(c)
def +[B](next: CoinAction[B]): CoinAction[B] =
flatMap(_ => next)
def map[B](f: A => B): CoinAction[B] = CoinAction { c0 =>
val (c1, a) = apply(c0)
(c1, f(a))
}
def flatMap[B](f: A => CoinAction[B]): CoinAction[B] =
CoinAction { c0 =>
val (c1, a) = apply(c0)
f(a)(c1)
}
}
64. case class CoinAction[A](action: Coin => (Coin, A))
extends (Coin => (Coin, A)) {
def apply(c: Coin) = action(c)
def +[B](next: CoinAction[B]): CoinAction[B] =
flatMap(_ => next)
def map[B](f: A => B): CoinAction[B] = CoinAction { c0 =>
val (c1, a) = apply(c0)
(c1, f(a))
}
def flatMap[B](f: A => CoinAction[B]): CoinAction[B] =
CoinAction { c0 =>
val (c1, a) = apply(c0)
f(a)(c1)
}
}
Coin のメソッドをどこ
からも呼び出してない
65. case class State[S, +A](run: S => (S, A)) {
def map[B](f: A => B): State[S, B] =
State { s =>
val (s2, a) = run(s)
(s2, f(a))
}
def flatMap[B](f: A => State[S, B]): State[S, B] =
State { s =>
val (s2, a) = run(s)
f(a).run(s2)
}
}
Coin を型パラメーター
S として抽象化
Functional Programming in Scala
http://www.manning.com/bjarnason/ より抜粋、一部改変
66. type CoinAction[A] = State[Coin, A]
val flip: CoinAction[Boolean] = State { c =>
val head = !c.head
(Coin(head), head)
}
val stay: CoinAction[Boolean] = State(c => (c, c.head))
CoinAction を type alias
として定義
70. Scalaz
Scalaz provides purely functional
data structures to complement those
from the Scala standard library.
— from http://typelevel.org/projects/scalaz/