Do more with multicore! Our tools parallelize your C/C++ program
Need to optimize code for a complex multicore platform? vfEmbedded solves the hard problem of partitioning and mapping your software onto your ARM-based or x86-based SoC platform. vfEmbedded lets you model your embedded platform, then takes you through the process of analyzing, parallelizing, and implementing your code.
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Want to extract more performance out of your multicore x86 system? vfThreaded-x86 fully analyzes and parallelizes your code, reaching the highest-performance on the latest multicore x86 machines. Our correct-by-construction approach avoids introducing those hard-to-find threading bugs.
More about vfThreaded-x86 »We’re moving into a bigger office
Marco Jacobs, Vector Fabrics blog, January 11, 2012
Vector Fabrics is expanding, and as a result we’ll be moving into a bigger and nicer office on January 13th. We’ll still be in Eindhoven, the smartest region in the world, in the city center. Restaurants, hotels and the famous PSV soccer stadium are within a few walking minutes. The railway station is roughly a 10-minute walk. Perhaps it goes without saying, but there will be no disruption in our service.
Happy new year!
Marco Jacobs, Vector Fabrics blog, January 10, 2012
We’re excited about 2012. More and more multicore products are being introduced, alleviating the need to optimize software applications for these high-performance processors. We’re moving into a new and larger office, as we’re expanding our team. We have many more good things to come in 2012. You can try our latest release, with many new features, and sign up for a free trial here. Click on the image below to view our happy new year wish. Multicore is our bread and butter, and thus our message can be viewed in single-core or multi-core fashion. Enjoy!
Multithreading examples for C programs, Part 1
Andrei Terechko, Vector Fabrics blog, November 18, 2011
Have you ever parallelized a C or C++ program? Then you got a slowdown first, didn’t you? Parallelization is a tough call because of data dependencies hiding behind pointers, unclear multithreading overheads, unexpected processor and OS behaviour, let alone potential starvation and deadlocks. Luckily, in the past 40 years computer engineers have been constantly accumulating best practices of industry-proven solutions to common concurrency challenges. They call them parallelization patterns.