CUDA 7.5: FP16, GPU Lambdas, GPU Instruction-Level Profiling

http://devblogs.nvidia.com/parallelforall/new-features-cuda-7-5/

by bsprings • 11 years ago

40 15 11 years ago

devblogs.nvidia.com

krapht4• 11 years ago

CUDA has been on my list of things to learn for quite some time. The ecosystem is just so much nicer than OpenCL... if I didn't have to support non-Nvidia GPUs, I'd have already gotten on the bandwagon.

enos_feedler• 11 years ago

Ugh, totally agree. They need to open source this stack and get all vendors on it. Its one of those things that is really holding back GPGPU innovation.

If you've been following Docker at all, they just did this by donating "runc" to a new effort called the open container project. NVIDIA should develop a reference x86 implementation of CUDA. Something that works great on multicore and then donate it to OpenCL or something. Or maybe OpenCL catches up soon.

artmageddon3• 11 years ago

I have the same desire to learn it too, but the only problem is I don't know what I'd use it for :/

krapht4• 11 years ago

Any problem where you have large vectors or matrices of floats and must add, subtract, divide, or multiply on them in parallel for performance reasons. A GPU is like a miniature datacenter in your computer!

But, unlike a real datacenter, it's only good for floats. But many financial, scientific, and gaming applications are only bottlenecked by the need to crunch floats, not arbitrary data types.

My mental model of a GPU is a device that has a million billion miniature 4-function calculators inside it that can all do things at once.

dman• 11 years ago

Ive been using OpenCL recently, and have had a pretty nice experience generally. Are there any things in particular from the CUDA ecosystem that you miss?

krapht4• 11 years ago

I don't know much about CUDA, just what I see from my co-workers who do get to use it. The Visual Studio integration looks amazing. The C++ api is cleaner. I am told there are lots of little quality-of-life API things that are better from people who have used both.

varelse2• 11 years ago

Lots of good stuff, and some not so good stuff:

"Deprecated: legacy (environment variable-based) command-line profiler. Use the more capable nvprof command-line profiler instead."

IMO there are way too many use cases for the command-line profiler to get rid of it, probably ever.

sipherhex• 11 years ago

nvprof is still a command line profiler, and has even more features.

varelse2• 11 years ago

And there are a lot of cases where it doesn't work, specifically with elaborate MPI scenarios and over a network/VPN. Specifically, I do not wish to jump through hoops to enable remote profiling over heavily IT-restricted networks.

For simple apps, nvprof is great. For real low-level blood and guts CUDA optimization, the command-line profiler is still indispensable. Killing it is enough reason for me to go code FPGAs in OpenCL instead of GPUs in CUDA.

CUDA 7.5: FP16, GPU Lambdas, GPU Instruction-Level Profiling

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