NVIDIA Tesla: GPU computing gets its own brand
At the moment, NVIDIA Tesla is primarily focused on the highest of the high-end, namely the oil, gas, and computational finance industries. That’s important to keep in mind because the Tesla introduction has answered another question we had when we first looked at CUDA: would it be limited to professional cards, even though the consumer GeForce cards would be capable of using CUDA? The answer is a resounding no. CUDA will be available across all product lines, although eventually there will be some features specific to GPU computing that are only available through the Tesla brand. Instead, Tesla, like Quadro, will be focused as a total solution. Workstations and software will be qualified to work with Tesla, with the same types of support as Quadro.
The basic unit of the current Tesla line, the Tesla C870, should be very familiar to anyone who’s seen the GeForce 8800. It’s essentially an 8800 GTX–a 575MHz core clock and 128 SPs at 1.35GHz–with 1.5GiB of GDDR3 RAM. Of course, it’s not quite an 8800 GTX–there are no display outputs at all on the card, even though it has a new version of the NVIO chip.
NVIDIA states that the C870 has a peak performance of 518 GFlops. Careful readers might already realize the implications of this number: the missing MUL is apparently now available in CUDA, increasing theoretical peak performance by 50% over what was previously stated for the 8800 GTX in CUDA. However, the conditions necessary for the MUL in the SFU to be used are unknown, and we don’t know whether or not the SFU MUL will ever be available in 3D applications. Still, the difference between a 50x and an 100x speedup is a lot less important than the difference between 1x and 50x, so we aren’t too concerned about the missing MUL. The C870 has an MSRP of $1299 and should be available in August.
The second product in the current Tesla line is the NVIDIA D870, called the “Deskside Supercomputer.” It’s very similar to the Quadro Plex; it’s two Tesla C870 cards in an external unit. Like the Quadro Plex, the D870 will connect to a host computer via an external PCIe 8x or 16x connection.
Because it’s simply two C870 cards in a more convenient form factor, the peak theoretical performance of the D870 is 1.036 TFlops. Keep in mind that CUDA doesn’t use any multi-chip interface like SLI. Instead, one thread on the CPU controls one CUDA device. So, in the case of the D870, there are two CUDA devices, and two CPU threads will be used to control them. As a result, if the data set can be spread across the two devices, there’s a linear increase in speed. There’s not any overhead from SLI or anything other than PCIe bandwidth, so the D870 really will be about twice as fast as the C870. The D870 has an MSRP of $7500 and, like the C870, is scheduled for availability in August.
Finally, there’s the utter beast of the family: the Tesla GPU Server. With availability targeted for Q4, it costs $12,000, and it’s twice as fast as the D870 with four G80 cards. The really terrifying thing here, however, is the form-factor. It fits four G80s into a 1U rack.
No Comments
No comments yet.
Comments RSS TrackBack Identifier URI
Leave a comment