Let’s get physical
By Simon Bisson & Mary Branscombe in Editorial
Posted in Processors, Silicon, Software on
Nvidia has decided that the visual computing world needs a conference, and has taken over San Jose to deliver just that. It’s an odd event, with a high-level academic parallel processing track running alongside highly analytical business sessions - and what’s billed as the world’s largest LAN party filling one of the conference halls.
Games may have made Nvidia, but it’s the rest of the graphics industry that keeps it going. Simulation and CAD drive much of today’s industrial design, while complex financial calculations can be run on GPU-powered parallel processors. It’s not just black hole plasma dynamics - it’s also the models that help calculate how a fusion reactor will operate. According to Nvidia GPU computing is bringing supercomputing to the desks of the people who need it the most - for just the cost of a video card.
One of the keynotes showcased a NASCAR simulator used by drivers to hone their skills. On stage we heard a populist story of what it was like to be a driver, and what it was like to use simulation tools. Off stage we heard a more interesting story about how the simulator developers were looking at using the latest generation of GPUs in their application. The ability to use a GPU for parallel processing - and the availability of powerful hardware physiscs engines - has made them completely rethink their next generation, as the new hardware features mean that they can now work on making the simulation more realistic.
That’s what the drivers want. Asked what he really wanted from a simulator, Kyle Busch didn’t talk about new high-resolution graphics or realtime ray tracing. What he wanted was more accurate physical behaviours. In the real world passing on the left is different from passing on the right, while slipstreaming another car can change the performance dramatically. A simulation may look real, but without the physics it’s not realistic at all.
One plan for the next generation is to move away from the current car model, with only 6-degrees of freedom. Instead, it really needs 72 degrees, for all the hinge and flex points - all of which are changing dynamically. That’s where parallel processing comes in, as it allows a car to be modelled in real time, taking advantage of physics engines to turn those model calculations into real world behaviours. Improving the simulation will mean more (and happier) customers - as well as a continually improving model that can be shared with vehicle manufacturers.
It’s an approach that requires specialist processing that goes beyond the traditional CPU. Don’t confuse it with the death of the CPU, though. There will always be a place for the traditional CPU - it’s just that silicon technology has become ubiquitous enough for specialist hardware to offload processor intensive functions.
Need to encrypt something? Just use the hardware cryptosystem built into a TPM. Need to do thread intensive Java? Hook up an Azul network processing appliance. Need to do complex vector calculations on large amounts of data? Use a GPU. Nvidia’s CEO Jen-Hsen Huang talks about it as heterogenous computing, where the CPU handles tasks, and more specialised hardware handle the complex tasks that tax general purpose silicon.
Intel and AMD may still say that general purpose processors are just what the world needs - but they’re still investing in HyperTransport and QuickPath, the fast buses that specialised silicon needs. I wonder why they’re doing that, if specialised silicon is the dead end they say it is. Is there something about Moore’s Law they’re not telling us?
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