CUDA
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9.0
- noun
- /ˈkuːdə/
- Specialized
- Researchers use CUDA to accelerate simulations in scientific computing, making them run much faster than traditional CPU processing.
- CUDA cores
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Watch on YouTubeNow, does it all eventually boil down to CUDA and NVIDIA GPUs?
- Now, does it all eventually boil down to CUDA and NVIDIA GPUs?
- Performs very well if you're doing things that are CUDA based or compute based.
- You'll see listings with with NVIDIA, it might be SMS and CUDA cores.
- And so likewise, NVIDIA cares a lot about CUDA.
- People like data centers based on GPUs and CUDA will be the future all NVIDIA, right?
- So I actually just opened up a fresh CUDA.
Examples
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Emphasizing the fact that some simulations can be more efficient on CUDA than traditional CPUs, NVIDIA gave an example of the material sciences application WL-LSMS.
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Performs very well if you're doing things that are CUDA based or compute based.
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Now take a look at the single-threaded CUDA example.
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You can extend Tiano by writing C or CUDA code.
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In terms of actual CUDA applications, those have increased in popularity as well, as you'd likely expect.
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So that is fewer shaders, fewer CUDA cores, all of that kind of stuff.
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Now, does it all eventually boil down to CUDA and NVIDIA GPUs?
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To date, 415 million+ CUDA GPUs have been shipped.
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The CUDA platform enhances the use of GPUs for general-purpose computing.
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With 2% of the lines of code being changed for CUDA's sake, the throughput for a given simulation has been increased from 3.08 PFLOPs to 10+ PFLOPs.
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Surface Forms
Etymology
CUDA comes from the phrase Compute Unified Device Architecture, a name made by NVIDIA. Here compute means 'to calculate' and unified means 'together', so the name helps you remember it is a system to make a graphics card do many calculations fast, which is why CUDA now means the platform and tools for running fast code on NVIDIA graphics cards.