It has been a while since my last post here, but I’m back! I had access to the French version of this book, thanks to the publisher.
CUDA is now in the trend, and there are several books, one of them I’ve also reviewed.
Massively parallel processors are in the mood today. We had small parallel processors with a few cores and the ability to launch serevral threads on one core, we have now many cores on one processor and at the other end of the spectrum, we have GPUs. CPUs vendors are now going in this direction with Larabee and Fusion, and GPUs will still have more cores/threads/… It’s thus mandatory to understand this shift now.
Due to the end of the free lunch, manufacturers started to provide differents processing units and developers started to go parallel. It’s kind of back to the future, as accelerators existed before today (the x87 FPU started as a coprocessor, for instance). If those accelerators were integrated into the CPU, their instruction set were also.
Today’s accelerators are not there yet. The tools are not ready yet (code translators) and usual programming practices may not be adequate. All the ecosystem will evolve, accelerators will change (GPUs are the main trend, but they will be different in a few years), so what you will do today needs to be shaped with these changes in mind. How is it possible to do so? Is it even possible?