Challenges in Multi-Core Era – Part 3

Previously, I compared the performance of today’s popular operating systems with respect to multi-core processors.  In this final part to Challenges in Multi-Core Era, I’ll talk about the multi-core capabilities found in today’s programming languages and development tools.

The Programming Languages

When language architects were designing the foundations of the most popular programming languages, multi-core microprocessors were hidden in laboratories. Only high performance servers had access to multiprocessing systems. Just a few specialized workstations had more than one CPU installed. Therefore, C# and Java offered support for concurrency and multi-threading intended to offer more responsive applications. However, language architects didn’t design this support to optimize applications for future multi-core CPUs. Hence, nowadays, it is really difficult to optimize existing code to take advantage of multi-core CPUs using frameworks prepared for serial code.

In order to take full advantage of multi-core, the applications need a task-based design and a task-based programming. There is no silver bullet. So far, there is no way to optimize an application recompiling it without changes. Some developers expected this to happen. There is a great need for new designs, new programming techniques and new tools. The software development industry needs a new great paradigm shift.

Besides, developers need a framework capable of handling tasks. There are new programming languages, or new versions of older concepts, like functional programming. Functional programming makes it easier to code task-based designs and to split the work to be done in multiple independent tasks that could be run in parallel on multi-core CPUs.

There are many new programming languages with a great focus on functional programming, prepared to take full advantage of multi-core and to offer a great scalability. Just to mention a few:

  • Scala
  • Haskell. Yes, the one that has more than twenty years. Pure functional programming languages are back and they can be the future for parallel programming.
  • Microsoft Axum (formerly Maestro).
  • Microsoft F#.

However, do developers want to begin learning new programming languages? Most developers want to leverage their existing knowledge to move onto multi-core programming.

C++ and Fortran programmers had early access to parallel programming. Nowadays, these are the only programming languages that can take advantage of the full power offered by modern microprocessors. C++ is closer to the hardware. Hence, it allows many optimizations that aren’t available in any other programming language – apart from C and assembler. You can access all the vectorization capabilities from C++ and Fortran.

OpenMP has been offering a high quality multi-platform and open source shared-memory parallel programming API to C/C++ and Fortran for many years now. Besides, Intel Threading Building Blocks, also known as TBB, allows developers to express parallelism in C++ applications to take advantage of multi-core.

Message Passing Interface (MPI), is a language-independent communications protocol used to program parallel computers. You can use MPI to take advantage of multi-core on many programming languages. However, its main focus is to help develop applications to run on clusters and high performance computers.

Intel offers compilers and libraries optimized to take advantage of multi-core. However, you still require coding your applications considering new parallel designs. The usage of vectorization in their math libraries is a great plus point. There is an outstanding opportunity for new libraries and components optimized for multi-core and vectorization. Parallelism brings new opportunities to the software development industry.

There are new companies taking advantage of the need for multi-core optimizations, like Cilk Arts, offering its Cilk++ compiler. It is based on GCC and includes a modified compiler and debugger to simplify multi-core programming for Linux and Windows platforms.

Mac OS X’s Xcode development environment offers access to Grand Central Dispatch and OpenCL. OpenCL allows C programs to run in the GPU instead of loading the main CPU. The interest of developers in Xcode has really grown since multi-core and OpenCL.

C# and Java are evolving in order to offer developers new ways of expressing parallelism in their code. Indeed, they are changing many aspects that were designed for another world, the old single-core machines.  Some of these changes include new garbage collectors, new frameworks and features, new functional approaches and task-based programming capabilities.

Java 7 will offer the new fork-join framework, really optimized for multi-core.

C# 4.0 (Visual Studio 2010) will add task-based programming capabilities and parallelized LINQ (PLINQ). Besides, it will allow the possibility to manage the desired degrees of parallelism.

Furthermore, there are new DSLs (Domain Specific Languages) to add parallel programming capabilities to existing high-level languages. For example, GParallelizer adds nice parallel programming capabilities to Groovy.

Most modern programming languages are evolving or adding inter-operatibility capabilities with other languages to favor multi-core programming.

However, don’t forget about vectorization. Mono, a free and open source .Net compiler, offers access to SSE3 and SSE4 for C# developers.

A few years ago, concurrency was about threads. Now, experts are talking about tasks and fibers. Why? Because in order to develop an application using a task based approach, threads are too heavy. Tasks and fibers are lightweight concurrency elements, much lighter than threads. They allow developers to implement complex task-based designs without the complexities of threads.

Ruby 1.9 added fibers and it simplify the creation of pipelines. Pipelines take great advantage of Hyper-Threading combined with multi-core.

If you want to go parallel, follow James Reinders’ eight key rules for multi-core programming. You can apply them to any combination of programming language, framework, compiler and virtual machine.

Java 7 and .Net 4 will not offer framework support for vectorization (SIMD instructions). SIMD has been there since Pentium MMX microprocessor.  This decision doesn’t make sense especially considering that there is a huge market for smart professionals in the new parallelism age.

The New Tools

A well-known proverb says “A good workman is known by his tools”.

A parallelized application requires new debugging and testing techniques. You need to catch potential bugs introduced by concurrency.

Intel has been offering tools for High Performance Computing and parallelism for many years now. A few weeks ago, Intel launched one of the most complete parallel toolkits for C/C++ developers, Intel Parallel Studio. Among many other features, it helps developers to compile applications tuned for multi-core CPUs and to find concurrency specific bugs and bottlenecks. You should expect to see more tools like this coming on the next quarters.

Visual Studio 2010 will add enhanced multi-monitor support capabilities. You’ll need more than one monitor in order to debug applications running with a task-based approach. It will also add task-based debugging capabilities. However, Visual Studio 2010 has recently entered Beta 1. Therefore, if you want to develop an application using a task-based approach using C# 3.0, you still have to work with threads. Visual Studio 2008 offers nice multithreading debugging capabilities.

Most IDEs are changing to offer new task-based programming, debugging and testing capabilities. You have to test parallelized applications on multi-core CPUs. Many bugs aren’t going to appear when running them on single-core CPUs.

There are many free tools to help you in the multi-core jungle. You can monitor your applications and test their concurrency efficiency using Process Explorer and Intel Concurrency Checker.  If you use these tools to check commercial software, you’ll be able to see the need for new multi-core aware developers. Besides, you’ll see a lot of opportunities in the multi-core age.

By the way, multi-core programming has a high quality weekly talk show lead by Intel experts, Parallel Programming Talk.


While the old free lunch is over, the industry is reshaping itself to take advantage of the new microprocessors architectures of today and tomorrow.

Hardware will continue to advance and offer more parallel processing capabilities, even though the software industry is moving more slowly than expected.

Bottom line is that multi-core seems to be a really sustainable competitive advantage that requires a great paradigm shift from developers throughout the software lifecycle. There is light at the end of the tunnel. Are you ready to reach it?

About the author: Gaston Hillar has more than 15 years of experience in IT consulting, IT product development, IT management, embedded systems and computer electronics. He is actively researching about parallel programming, multiprocessor and multicore since 1997. He is the author of more than 40 books about computer science and electronics.

Gaston is currently focused on tackling the multicore revolution, researching about new technologies and working as an independent IT consultant, and a freelance author. He contributes with Dr Dobb’s Parallel Programming Portal, http://www.go-parallel and is a guest blogger at Intel Software Network

Gaston holds a Bachelor degree in Computer Science and an MBA.You can find him in and

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