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News about TPL Dataflow

More on TPL Data Flow from Zlatko Michailov

Topics
.NET,
Languages,
Performance & Scalability,
Programming,
TPL Dataflow,
Task Parallel Library

We briefly interviewed Zlatko Michailov, author of the Guide to Implementing Custom TPL Dataflow Blocks.

Implementing Custom TPL Dataflow Blocks

Topics
.NET,
Parallel Programming,
Languages,
Performance & Scalability,
TPL Dataflow,
Programming,
Task Parallel Library

Dataflow Blocks are the backbone of the .NET 4.5’s new high performance parallel processing library. And while they offer a lot of functionality out of the box, there will be times when a custom block is necessary. Zlatko Michailov has put together a document outlining the process and many of the traps you may encounter.

Using Messaging and Scheduling for Lock-free Access to Shared State

Topics
.NET,
Languages,
Performance & Scalability,
Programming,
TPL Dataflow,
Task Parallel Library,
Architecture,
Message Passing

In a message passing system there may be times when mutable data must be shared amongst many tasks. In traditional programming this would be handled by a read-writer block, which would allow one writer thread to block all other threads while it updates the shared data. With a technique found in frameworks such as TPL Dataflow it is possible to avoid this.

Asynchronous Message Processing using Task Parallel Library and Reactive Extensions

Topics
.NET,
Languages,
Task Parallel Library,
Message Passing,
Reactive Extensions,
Programming,
Performance & Scalability,
TPL Dataflow

A new preview of TPL Dataflow has recently been released along with Visual Studio Async. Along with performance enhancements and stronger ties with the Reactive Framework, it is being positioned as a foundation for building actor/agent style frameworks as opposed to a complete solution.

TPL Dataflow – The Successor to CCR

Topics
.NET,
Concurrency,
Parallel Programming,
Languages,
Programming,
Task Parallel Library,
TPL Dataflow,
CCR

TPL Dataflow is Microsoft’s new library for highly concurrent applications. Using asynchronous message passing and pipelining, it promises to offer more control than thread pools and better performance than manual threading. The downside is that you have to adhere to design patterns that may be unfamiliar to .NET programmers.