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28:14
Java Follow 203 Followers

Maurice Naftalin on Java Lambdas, Java 8 Streams, Parallelism

Interview with Maurice Naftalin Follow 1 Followers on  Sep 12, 2015

Maurice Naftalin explains uses for lambdas in Java, how streams work in in Java 8, parallel streams and threading, side effects, and much more.

22:08
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Neha Narula on the Latest Research in Databases, Transactions, Distributed Programming

Interview with Neha Narula Follow 0 Followers on  Jun 08, 2015

Neha Narula talks about the latest research and concepts in distributed programming and databases, reducing the overhead of transactions, are multicore systems like distributed systems, and much more.

30:52
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Jeremy Pollack of Ancestry.com on Test-driven Development and More

Interview with Jeremy Pollack Follow 0 Followers on  Feb 15, 2014

Hadoop, the distributive file system and MapReduce are just a few of the topics covered in this interview recorded live at QCon San Francisco 2013. Industry-standard Agile implementation and a lot of testing, assures the development team at Ancestry.com that they have an app that can handle the large traffic demands of the popular genealogy site.

21:36
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Felix Klock II on Parallel JavaScript

Interview with Felix Klock II Follow 0 Followers on  Feb 10, 2014

Felix Klock II explains Parallel JavaScript (née RiverTrail): how it brings parallelism to JavaScript, what data structures and types it supports, how it relates to ECMAScript 6 specs and much more.

16:52
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Interview with Barbara Liskov

Interview with Barbara Liskov Follow 0 Followers on  Apr 02, 2013 1

Barbara Liskov keynoted at QCon London 2013 on the power of abstraction. Afterwards, InfoQ caught up with up with her to ask her about language design, modularity and distributed computation.

15:27
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David Nolen on Logic and Constraint Programming, Core.logic, Mozart/Oz

Interview with David Nolen Follow 1 Followers on  Mar 08, 2013

David Nolen explains the ideas behind logic and constraint programming, how they're used in his Clojure core.logic library, Prolog, the features in the Oz language and Mozart/Oz, and much more.

36:10
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Duncan Coutts on Parallelism and Concurrency with Haskell, Distributed Programming with Cloud Haskell

Interview with Duncan Coutts Follow 0 Followers on  Feb 21, 2013

Duncan Coutts explains the nature of Concurrency and Parallelism in Haskell, its threading and STM implementation, Erlang OTP's influence on CloudHaskell for distributed programming, Monads, and more.

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Damian Conway on the State of Perl, Perl 6, Writing Parsers and DSLs

Interview with Damian Conway Follow 0 Followers on  Jan 02, 2013

Damian Conway explains where Perl 5.x is used today and why (hint: the CPAN library repository), and what Perl 6 offers: modern OOP, an optional type system, libraries for parallelism and concurrency, and very powerful built-in tools for parsing including extensible grammars.

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Rick Hudson on Parallel JavaScript (RiverTrail)

Interview with Rick Hudson Follow 0 Followers on  Oct 01, 2012

In this interview, Intel's Rick Hudson talks about Parallel JavaScript (formerly known as "RiverTrail"), a new parallel programming API designed specifically for JavaScript. Rick describes RiverTrail and its vision of how to leverage current and future parallel hardware from within the browser and JavaScript.

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Viktor Klang on Akka, Futures and Promises, Scala

Interview with Viktor Klang Follow 0 Followers on  Jun 14, 2012

Viktor Klang talks about the features of Akka 2.x and future releases, Akka's approach to fault tolerance, the effort to unify Futures in Scala, and the state of functional programming.

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James Spooner on Data Flow Parallelism and Hardware Acceleration

Interview with James Spooner Follow 0 Followers on  Jun 01, 2012 1

James Spooner explains how Data Flow Parallelism works and how it helps to design efficient parallel algorithms. Also: OOP vs. Parallelism.

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John Nolan on the State of Hardware Acceleration with GPUs/FPGAs, Parallel Algorithm Design

Interview with John Nolan Follow 0 Followers on  Jan 19, 2012 1

John Nolan shows the state of hardware acceleration with GPUs and FPGAs, why it's hard to write efficient code for them, and why to favor polymorphism over if statements for performance.

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