The WSJ just published this story: Trading Firms Turn To Videogame Chips To Get Even Faster.

The article primarily focuses on FPGAs.  Nvidia is mentioned as well as OpenCL.

Another company that uses FPGA's to process market data is Exegy.

I suspect that GPUs are being looked at very closely by Wall Street but one challenge that early adopters need to overcome is architecting a solution that gets away from the simple but latent "kernel launch and wait" approach:

1. copy data to device
2. launch kernel
3. wait for kernel completion
4. copy results from device

Now that CUDA supports page-locked/write-combining/mapped/overlapped memory and 2.0 supports concurrent data transfers you can quickly imagine some architectures and long-running kernels that might help you avoid the approach listed above and drive compute latencies downward.

Having worked with both high-speed market data feeds and the entire trading workflow, I can think of GPU applications ranging from mundane processing tasks all the way up to HFT.

I'm sure that there are plenty of people who have already done this and aren't talking about it!

Update 5/18/2010:  There sure are.  Take a look at Hanweck & Associates' Volera product.  They're repricing the entire options market with 10 milliseconds of latency.  Note that the OPRA feed is expected to produce 14B messages/day by the end of 2010.