InfoQ Homepage Parallel Programming Content on InfoQ
-
Fine Grained Coordinated Parallelism in a Real World Application
Mohammad Rezaei discusses fine-grained parallelism along with an algorithm called Aggregation and a concurrent map built to help dealing with it.
/presentations/Fine-Grained-Parallelism/en/smallimage/Mohamad.JPG)
-
River Trail: Adding Data Parallelism to JavaScript
Richard L. Hudson introduces River Trail, a JavaScript parallel programming API enabling a JavaScript developer to take advantage of the hardware’s parallel computing capabilities.
/presentations/River-Trail/en/smallimage/Ric.JPG)
-
Introduction to CUDA C
Cyril Zeller introduces NVIDIA CUDA development, showing how to write and execute C programs on the GPU, how to manage GPU memory and communication with the CPU.
/presentations/Introduction-to-CUDA-C/en/smallimage/Cyril.JPG)
-
Concurrent Programming Using The Disruptor
Trisha Gee introduces Disruptor, a concurrency framework based on a data structure – a ring buffer – that enables fast message passing in a parallel environment.
/presentations/Concurrent-Programming-Using-The-Disruptor/en/smallimage/Trisha.JPG)
-
Objects, Anomalies, and Actors: The Next Revolution
Steve Vinoski believes that actor-oriented languages such as Erlang are better prepared for the challenges of the future: cloud, multicore, high availability and fault tolerance.
/presentations/Objects-Anomalies-and-Actors-The-Next-Revolution/en/smallimage/Steve.JPG)
-
Panel: Multicore, Manycore, and Cloud Computing
Joshua Bloch, Robert Bocchino, Sebastian Burckhardt, Hassan Chafi, Russ Cox, Benedict Gaster, Guy Steele, David Ungar, and Tucker Taft discuss the future of computing in a multicore world.
/presentations/Panel-Multicore-Manycore-Cloud-Computing/en/smallimage/Panel.JPG)
-
Java SE: A Youthful Maturity
Danny Coward talks on how Oracle intends to maintain Java in the front line by investing in two features that are trendy today: support for multiple JVM languages and parallel programming.
/presentations/Java-SE-A-Youthful-Maturity/en/smallimage/Danny.JPG)
-
Perception and Action: An Introduction to Clojure's Time Model
Stuart Halloway discusses how we use a total control time model, proposing a different one that represents the world more accurately helping to solve some of the concurrency and parallelism problems.
/presentations/An-Introduction-to-Clojure-Time-Model/en/smallimage/Stuart.JPG)
-
Actor Thinking
Dale Schumacher explains the actor concept and how it helps us build a computational model resembling the reality around us more accurately than the object-oriented model.
/presentations/Actor-Thinking/en/smallimage/Dale.JPG)
-
Parallel Programming Patterns: Data Parallelism
Ralph Johnson presents several data parallelism patterns, including related Java, C# and C++ libraries from Intel and Microsoft, comparing it with other forms of parallelism such as actor programming.
/presentations/Parallel-Programming-Patterns/en/smallimage/Ralph.JPG)
-
Parallel Programming Patterns: Data Parallelism
Ralph Johnson presents several data parallelism patterns, including related libraries from Intel and Microsoft, comparing it with other forms of parallel programming such as actor programming.
/presentations/Data-Parallelism/en/smallimage/Ralph.JPG)
-
How to Think about Parallel Programming: Not!
Guy L. Steele Jr. believes that programmers should not think about parallelism, but languages should provide ways to transparently run tasks in parallel by supporting independence-based constructs.
/presentations/Thinking-Parallel-Programming/en/smallimage/GuySteele.JPG)