Tag Archives: Multithreading

Threading in Python: Beating Moore’s Law

Threading in Python Herb Sutter of C++ fame wrote in 2005 that the end was in sight for single core CPUs keeping up with Moore’s Law. The way forward was multiple cores and concurrency, i.e. doing multiple things at the same time. If you have multiple systems or even multiple CPUs in a system then […]

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Basics of Parallelization – Part One

Basic tricks for parallelization code to take advantage of multiple cores and processors In today’s multicore systems, many programmers are leaving performance on the table. This multipart series shows how to get the most out of your hardware with multithreading and vectorization. Read on to see how Slashdot Media Contributing Editor Rick Leinecker gets started […]

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Getting Up to Date With Fortran

One of the oldest high-level languages, Fortran (short for FORmula TRANslation) is still used today in numeric and high-performance computing. It’s been used in the HPC arena for more than 20 years, and it’s been 58 years since the delivery of the first Fortran compiler. There have been 10 updates of the standard, including three […]

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Threading 101: Using Multiple Cores for Better Software Solutions

The performance bar for applications is much higher than it used to be. Users expect applications to be smooth and perform without waiting or delay. Fortunately, with multiple processors, most computers can achieve a high level of performance. This makes the user experience much better. But developers must rely on multi-threaded code that takes advantages […]

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Explicit Multithreading: The Pros and Cons

First, before detailing the pros and the cons, we need to establish some baseline understandings with regard to Explicit Multithreading (XMT). To start with, let’s look at sequential code execution, best described by the von Neumann model. In this model, single instructions pointed to by the instruction counter are fetched, decoded, and then executed. This […]

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Debugging Multithreaded Code

In this video, Rick Leinecker gets you started in the large topic of debugging multithreaded code. Rick covers preventing bugs, reverting to sequential code to help eliminate bugs, and why the debugger might mask multithreaded bugs. He also talks about effective use of trace statements to give you detailed information.

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Unintended Consequences of Parallel Computing: How to Avoid Pitfalls

In this blog, we’ll take an in-depth look at parallel computing, and examine some of the pitfalls that can thwart efforts for great code to create applications that sing. Parallel Is Not Always Faster Than Sequential There are times when changing code from sequential to parallel will slow it down. While this may seem surprising, […]

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