Squeeze more performance from Parallelism

In many posts, such as: The Future of the Parallelism and its Challenges I mentioned that synchronization the access to the shared resource is the major challenge to write parallel code.

The synchronization and coordination take long time from the overall execution time, which reduce the benefits of the parallelism; the synchronization and coordination also reduce the scalability.

There are many forms of synchronization and coordination, such as:

• Create Task object in frameworks such as: Microsoft TPL, Intel TDD, and Parallel Runtime Library. Create and enqueue task objects require synchronization that it’s takes long time especially if we create it into recursive work such as: Quick Sort algorithm.
• Synchronization the access to shared data.

But there are a few techniques to avoid these issues, such as: Shared-Nothing, Actor Model, and Hyper Object (A.K.A. Combinable Object). Simply if we reduce the shared data by re-architect our code this will gives us a huge benefits in performance and scalability.

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Parallel Programming for real-world

Multicore computers shift the burden of software performance from chip designers and architects to software developers.

What is the parallel Computing ? and what the different between Multi-Threading and Concurrency and Parallelism ? and what is differences between task and data parallel ? and how we can use it ?

Fundamental article into Parallel Programming...

The Future of the Parallelism and its Challenges

The Future of the Parallelism and its Challenges

Research and education in Parallel computing technologies is more important than ever. Here I present a perspective on the past contributions, current status, and future direction of the parallelism technologies. While machine power will grow impressively, increased parallelism, rather than clock rate, will be driving force in computing in the foreseeable future. This ongoing shift toward parallel architectural paradigms is one of the greatest challenges for the microprocessor and software industries. In 2005, Justin Ratter, chief technology officer of Intel Corporation, said ‘We are at the cusp of a transition to multicore, multithreaded architectures, and we still have not demonstrated the ease of programming the move will require…’

Key points:

• A Little history
• Parallelism Challenges
• Under the hood, Parallelism Challenges
  • Synchronization problems
  • CAS problems
• The future of the parallelism

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DyradLINQ

The goal of DryadLINQ is to make distributed computing on large compute cluster simple enough for ordinary programmers. DryadLINQ combines two important pieces of Microsoft technology: the Dryad distributed execution engine and the .NET Language Integrated Query (LINQ).

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Dyrad

The Dryad Project is investigating programming models for writing parallel and distributed programs to scale from a small cluster to a large data-center.

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