Anyone here used CUDA?
-
honey the codewitch wrote:
too much math
Is that even a thing?? :confused: On a completely unrelated note: that syntax thingamajig you're building (sorry for getting technical...). Can that be adapted to guess what syntax it's looking at? I'm assuming not because I'm guessing you have to provide it the syntax rules (laborious?) for it to understand a syntax. What I was thinking was "does your syntax thingy load a syntax from a standard syntax description library and parse from that?" I have a problem and am randomly looking around for a solution ;)
cheers Chris Maunder
Chris Maunder wrote:
I have a problem and am randomly looking around for a solution
let me introduce you your next secret weapon: Quick Answers[^] :rolleyes:
M.D.V. ;) If something has a solution... Why do we have to worry about?. If it has no solution... For what reason do we have to worry about? Help me to understand what I'm saying, and I'll explain it better to you Rating helpful answers is nice, but saying thanks can be even nicer.
-
Chris Maunder wrote:
What I was thinking was "does your syntax thingy load a syntax from a standard syntax description library and parse from that?"
Kind of. Glory takes a syntax description as a "grammar". The grammar itself is in XBNF format which is a lot like EBNF in terms of functionality but not as ugly.
Chris Maunder wrote:
Can that be adapted to guess what syntax it's looking at?
It can't guess what it's looking at, nor can it change grammar rules on the fly (table regeneration would be too slow), but what it can do is return all possible variations of what it's looking at. In order to get it to guess a grammar it would have to solve an undecidable problem, which is a problem. :laugh:
Real programmers use butterflies
honey the codewitch wrote:
it would have to solve an undecidable problem
So what you're saying is it needs a marriage counsellor.
cheers Chris Maunder
-
honey the codewitch wrote:
it would have to solve an undecidable problem
So what you're saying is it needs a marriage counsellor.
cheers Chris Maunder
haha! The problems crop up when trying divine hierarchies/trees of data from flat text.
Real programmers use butterflies
-
If so I was just wondering what sort of apps you've written or played with in order to use CUDA.
cheers Chris Maunder
I used Cuda in my Masters for simulating spiking neural networks. Ended up using cudafy (.Net library) as wanted C# familiarity. Certainly allowed me to run my simulations far quicker but don’t underestimate the amount of effort required to tune (and get right - debugging 1000s of threads isn’t fun) non-trivial algorithms.
-
If so I was just wondering what sort of apps you've written or played with in order to use CUDA.
cheers Chris Maunder
I used CUDA in my doctoral work in physics. Solving a non-linear partial differential equation via finite difference, I achieved a speed up of 32x on an NVIDIA GPU in my laptop, about 96 cores. It requires a different mode of thinking than we are used to, but it's worth it.
-
If so I was just wondering what sort of apps you've written or played with in order to use CUDA.
cheers Chris Maunder
Used it for a basic convolution like problem with a large overlap. The code I wrote is rather basic, the stuff around needed some attention to get it working, but it delivered in spite of not studying that much on it. But I'll wait for another real life application before delving into it again.
-
I played around a little with OpenCL and DirectCompute (when it was still fashionable), but not a direct CUDA API. I wouldn't know the first thing about that. All I did was throw some contrived distributed problems at it. Eventually I wanted to make some acoustic modeling Digital Signal Processing software using it to provide nice tube amp and analog synth sounds, or maybe go further and implement low latency real-time vocoding and such. I never did though. Too much work and too much math. :-D
Real programmers use butterflies
I used CUDA, after looking at OpenCL. Opinion: OpenCL was what AMD got IBM,HP et al to impose on NVidia, so that "the same code" could run on AMD's (ATI's) video chips too. Having written asm to do the latter, it's ridiculous; you need to use different *algorithms* when the underlying chipset is that much less powerful. CUDA was really straightforward; high-level but targeting a GPU built for GPGPU. That being said, have not used it in 10 years.
-
If so I was just wondering what sort of apps you've written or played with in order to use CUDA.
cheers Chris Maunder
I have used Cuda\C\C++ for simple pattern matching on fairly large data sets. Keep in mind that there are some performance limitations when using Cuda due to the time required to marshal data to and from GPU memory and when the algorithm requires multiple synchronizations but still the performance is impressive. Keep in mind that Cuda is not the solution for all problems; clever algorithm implemented on CPU only can match or even outperform GPU code in some scenarios. It is fun to play with good old C and different memory types of GPU. Debugging is more challenging and separate compilation that requires two compilers (NVCC and C/C++) is sometimes creating unexpected issues. Finding help on the web is more difficult than with more established technologies. I am using Visual Studio to do all of that on Windows.
-
If so I was just wondering what sort of apps you've written or played with in order to use CUDA.
cheers Chris Maunder
I used CUDA for parallelization of a Java program. The task was about accelerating a fairly simple algorithm for projecting bitmaps. It was fun and I made an [infographic](https://create.piktochart.com/output/25355418-java-parallelization-with-cuda) on my method. Found GPGPU quite exiting but lost it from sight, anyway... Regards, Jürgen.
-
If so I was just wondering what sort of apps you've written or played with in order to use CUDA.
cheers Chris Maunder
I tried out CUDA as a way of speeding up a raytracing graphics engine I was working on. My goal was to do raytracing without expensive (RTX) hardware. If I remember correctly, my program ran about as fast using most of the CUDA cores on a GTX 1050 Ti as it did using all the CPU cores on a Ryzen 7 1700X. I probably could have got it to run faster by optimizing it more for CUDA (I think I was using doubles), but the main problem for that project was my core algorithm being slow on anything. :sigh: