11–20 of 82 posts
I had forgotten just how much I hate java namespaces. import edu.syr.pcpratts.rootbeer.testcases.rootbeertest.serialization.MMult; This seems like a pretty amazing project if the claims are true, though - I wasn't aware that CUDA was able to express so many of the concepts used to implement Java applications. The performance data in the slides is certainly compelling!
http://nvidianews.nvidia.com/Releases/NVIDIA-Contributes-CUD...
in other words, with that and the right frontend, you can take Language X, compile to LLVM IR, and run it through the PTX backend to get CUDA.
however, in the grand scheme of things, this probably doesn't make GPU programming significantly easier to your average developer (as you still have to deal with big complicated parallel machines); what it really does is ease integration into various codebases in those different languages.
I had forgotten just how much I hate java namespaces. import edu.syr.pcpratts.rootbeer.testcases.rootbeertest.serialization.MMult; This seems like a pretty amazing project if the claims are true, though - I wasn't aware that CUDA was able to express so many of the concepts used to implement Java applications. The performance data in the slides is certainly compelling!
The only reason you see the fully qualified class names is because the IDE does this automatically for you. If there were no IDEs everyone would be using the *s;
Its pretty cool. Of course you are probably using that GPU in a desktop, but an on die GPU in a server class machine? Something to consider.
I think most of the GPU-based bitcoin farmers are using desktop hardware, but I might be wrong.
I had forgotten just how much I hate java namespaces. import edu.syr.pcpratts.rootbeer.testcases.rootbeertest.serialization.MMult; This seems like a pretty amazing project if the claims are true, though - I wasn't aware that CUDA was able to express so many of the concepts used to implement Java applications. The performance data in the slides is certainly compelling!
import edu.syr.pcpratts. ; The only reason you see the fully qualified class names is because the IDE does this automatically for you. If there were no IDEs everyone would be using the *s;
Its pretty cool. Of course you are probably using that GPU in a desktop, but an on die GPU in a server class machine? Something to consider.
The GPU in a desktop is the only interesting kind of GPU. The built-in GPU in servers is ten years behind the current cutting edge on desktops. Though servers can have PCI Express slots for modern GPU installation. I think most of the GPU-based bitcoin farmers are using desktop hardware, but I might be wrong.
One is the tiny ancient GPUs used to drive VGA outputs on servers. Those are hardly even worth talking about; they're only there so that you can hook a monitor up in an emergency.
And then there are real server GPUs, like nVidia Tesla stuff. Those typically don't even have video outputs, but they're on par with modern high-end gaming GPUs, possibly even better at some tasks.
I believe most bitcoin farmers are still using desktop GPUs, but that's largely just because they're running relatively simple kernels, all things considered, and because desktop GPUs are cheaper and easier to source.
Earlier quoted context omitted.
import edu.syr.pcpratts. ; The only reason you see the fully qualified class names is because the IDE does this automatically for you. If there were no IDEs everyone would be using the *s;
Wildcard imports are a bad idea regardless of whether you're using an IDE or not due to the risk of future name conflicts.
Pretty much everyone uses an IDE anyway so it's not like namespaces are ever an issue unless you do come across that rare name clash.
Earlier quoted context omitted.
import edu.syr.pcpratts. ; The only reason you see the fully qualified class names is because the IDE does this automatically for you. If there were no IDEs everyone would be using the *s;
Wildcard imports are a bad idea regardless of whether you're using an IDE or not due to the risk of future name conflicts.
Its pretty cool. Of course you are probably using that GPU in a desktop, but an on die GPU in a server class machine? Something to consider.
The GPU in a desktop is the only interesting kind of GPU. The built-in GPU in servers is ten years behind the current cutting edge on desktops. Though servers can have PCI Express slots for modern GPU installation. I think most of the GPU-based bitcoin farmers are using desktop hardware, but I might be wrong.