#Matlab cuda emulator code#

#Matlab cuda emulator code#

It would have been great to implement something like a 'test mode' which could have shown a big 'warning' (just single precission, not IEEE complient, etc.) for the parallel processing toolbox just to test code on gpus with compute capability 1.0-1.2. In fact, I bought a brand new notebook which I ordered with nvidia graphics card in order to write Matlab programs with usage of GPU power (just to test my code!), but I simply cannot use ist. This is simply not available for a 14.1'' notebook. However, it is not possible to order this business notebook with a nividi graphics card with compute capability 1.3 or greater. I want to have this small and light notebook for code development in Matlab when I am on business trips, so that I can run the developed codes later on my workstation in my office with double precision.ДЄfter installation of Matlab, I was shocked that I read that GPU processing is not possible since the nvidia graphics card has 'only' compute capability 1.2. Just 3 weeks ago, I bought a new business notebook from Dell (Latitude E6410) with i5 CPU, 14.1'' Display, 8GB RAM, 500GB disc, and a nvidia graphics card (NVS 3100m). But for my new business notebook it is not. However, your argument that all new graphic cards (which I expect in brand new notebooks) are compute capability 1.3 or greater ist unfortunately not true.ДЄt my office everything is fine, since I have a workstation with a Tesla C2050 with compute capability 2.0. I understand your arguments to be IEEE complient and to support double precision. More information on the GPU capabilities, including video tutorials examples and how-toвЂ™s can be found at. I'm afraid there is no way to remove this restriction on the product. Obviously we are sorry that our product can't be used on all machines with CUDA cards, but we believe the trade-off in user experience and confidence is worth it. Thus we opted for compute capability 1.3 or greater, knowing that most cards going forward would be suitable for use on our system and that we could rely on the underlying hardware to give the answers our users expect. All new graphics cards are compute capability 1.3 or greater (the latest Fermi architecture is 2.0 and 2.1 and provides very good single and double performance). We obviously realize that there are some algorithms that will work with non-IEEE compliant single arithmetic, but trying to draw a line around such a set was something that we believe is not in our usersвЂ™ interest, since some expected algorithms would be unavailable on some hardware.ДЇurthermore single-only cards are being phased out by NVIDIA.

We were worried that only giving results in single precision and with non-IEEE compliance was too much of a risk to support. We feel that it is important that MathWorks products always give what are termed 'correct' answers, which is something that we strive extremely hard to ensure in the code we write. IEEE-compliance in 1.3 (1.2 and earlier doesn't implement IEEE-compliant maths whereas 1.3 is compliant in both single and double) Double support in 1.3 (1.2 and earlier has NO support for double precision numbers, you can only undertake single precision arithmetic)Дў.

The key differentiators between compute capability 1.2 and 1.3 (for MATLAB users) are:ДЎ. The first point to make is that this wasn't a decision we took lightly we thought long and hard about the differences between 1.2 (and earlier) and 1.3 (and later) and what they meant to users in MATLAB. I'm currently the lead architect for Parallel Computing Tools here at MathWorks and I'd like to explain why we chose to require Compute Capability 1.3 in the NVIDIA CUDA cards that can be used with the R2010b release of Parallel Computing ToolboxвЂ™s new GPU functionality and particularly why we chose not to support older cards.