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Five Nvidia CUDA-Enabled Apps Tested

Posted by ScuttleMonkey on from the need-for-speed dept.

crazipper writes "Much fuss has been made about Nvidia's CUDA technology and its general-purpose computing potential. Now, in 2009, a steady stream of launches from third-party software developers sees CUDA gaining traction at the mainstream. Tom's Hardware takes five of the most interesting desktop apps with CUDA support and compares the speed-up yielded by a pair of mainstream GPUs versus a CPU-only. Not surprisingly, depending on the workload you throw at your GPU, you'll see results ranging from average to downright impressive."

3 of 134 comments (clear)

  1. Tied to a card by ComputerDruid · · Score: 5, Insightful

    What I don't understand is why people hype a technology that is tied to a specific manufacturer of card. If nvidia died tomorrow, we'd have a fair amount of code thats no longer relevant, unless there was some way to design cards that are CUDA-capable but not nvidia.

    Also worth noting that I'd completely forgotten CUDA even ran on windows, as I've only heard it in the context of linux recently.

    1. Re:Tied to a card by gustgr · · Score: 5, Insightful

      OpenCL will hopefully help to set a solid ground for GPU and CPU parallel computing, and since it is not technically very different from CUDA, porting existing applications to OpenCL will not be a challenge. Nowadays with current massively parallel technology the hardest part is making the algorithms parallel, not programming any specific device.

  2. Re:Nice, but... by Jah-Wren+Ryel · · Score: 5, Insightful

    Does it matter? Linux is not anywhere close to the target market,

    Linux support for CUDA matters hugely, Linux boxes are head and shoulders above any other market for CUDA-based software. That's because linux is the OS for supercomputing nowadays and CUDA's biggest niche is the exact same kind of number crunching that is typically associated with supercomputer workloads.

    In fact, these GPUs are yet another example of how there is nothing new under the sun. A GPU is very much like the vector processor of Cray-style supercomputing (when Cray was still alive that is) aka SIMD (single instruction, multiple data).

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