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I’ve just completed reading the white paper released by nvidia which you can find here.

Rather interestingly no mention of graphics performance has been made which, in a way, is really exciting. This has clearly been aimed at the high performance or throughput computing markets with the notable inclusion of ECC memory and increased double precision throughput along with the updated IEEE 754-2008 floating point support.

Concurrent kernel execution and faster context switching will allow, with the use of DAG’s, the optimization of execution on the devices rather than just working out the most efficient order of kernels to execute sequentially.

Also tucked away in the white paper is the mention of have predication at the instruction level which should give greater control of divergent paths in your kernels.

The inclusion of C++ support will appeal to a lot of people but am I rather unconvinced this is the correct way to go for throughput computing as it will encourage the use of all the old patterns that may work well in serial cases but are often rather poor for enabling maximum throughput.

There is a lot more in the paper and already an announcement by Oak Ridge that they will be using it in a new supercomputer.

All in all its a wonderful development and I can’t help feeling that computing took a substantial leap forward today.

In a previous post I mentioned fitting my Tesla C1060 onto my aging Asus motherboard. It has been working well but a combination of slow host<->device transfers speeds of less than 1GB/s,  2GB ram and a relatively slow processor encouraged me to upgrade.

Some of the prerequisites for my new personal super computer were:

a) Must be small - my desk area is limited and I don’t like putting computers on the floor where they consume dust better than any known vacuum cleaner…

b) Must have at least 2x pci express 2 (gen 2) slots as for decent GPU computing you need to get data in and out of the device as quickly as possible.

c) As quiet and cool as possible.

As it turns out the last one was the most tricky and needed the C1060 to do a bit of CFD for the airflow in the case.

After a lot of research, measurement and two days of building here are some pictures of the final result. The case is only 11″ x 11″ x 14″ - ok it’s not Exactly a cube…. but close enough :) The tape measure in the photos is to give some sense of scale.

Many thanks to NVidia who very kindly sent me two NVidia Tesla logos for me to stick onto the case!

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When picking up my rss feeds this morning from Google Reader (which is really good) I came across a very exciting article from NVidia claiming a massive speed increase in OpenGL. The article is here. 

In the past I mostly used PBO’s but have been using more and more VBO’s in the CFD visualizations so I will give these new extensions a try soon. Keep in mind it only applies to 185 and above drivers.