HN Academy

you can take this course

https://www.udacity.com/course/intro-to-parallel-programming...

John Owens is a good teacher. He helped me get started on CUDA.

CMU has a few lectures on this open to the public: http://15418.courses.cs.cmu.edu/fall2016/lectures Check out Lecture 7: GPU Architecture and CUDA Programming it starts 16mins in after some review.

Udacity also has a parallel image processing algorithms w/CUDA course though I haven't done it https://www.udacity.com/course/intro-to-parallel-programming...

Free udacity course: https://www.udacity.com/course/intro-to-parallel-programming...

⬐ fscherer

the beginning is slow but then it picks up pace, I liked it and they present the topic in a way that is easily understandable

⬐ hubatrix

I looked into it before, but thought its too slow and its more like for people having no idea about computers before, sorry these are purley my feeling alone.So asked for more advance tutorial here !?

⬐ yread

You can just skip the first lessons, the chapter "Squaring Numbers Using CUDA Part 1" has some code. Then the third lesson some more advanced techniques (actually they are really basic, but you might not have heard about them if you're not into parallel programming or networking hardware). I recommend it btw.

⬐ hubatrix

Thanks, sure will give it a try !!

I'm taking a free course in CUDA programming on Udacity at the moment that's co-taught by a guy from NVIDIA Research and a professor from UC Davis. If you're looking for something that starts from the basics and is really easy to follow, I highly recommend it.

https://www.udacity.com/course/intro-to-parallel-programming...

⬐ jkloosterman

I'm working on a Ph.D. working in GPU architecture, and this course is the real deal. It goes beyond how to run things on a GPU to analyzing the runtime and work efficiency of algorithms suited to the GPU.

Wen-mei Hwu's lectures on "Advanced Algorithmic Techiques for GPUs" (first lecture slides: http://iccs.lbl.gov/assets/docs/2011-01-24/lecture1_computat...) are a gold mine of GPU programming techniques. I believe he has published several books on the topic too, and released a benchmark suite (Parboil http://impact.crhc.illinois.edu/parboil/parboil.aspx) optimized with these techinques.

⬐ clw8

He runs a Coursera MOOC too, how useful is that? I gave up early on because the homework was very simple.

⬐ frozenport

The university course is also a joke, except for the project, which is "what you make of it".

⬐ oplav

I took the course at UIUC (ECE 408) 2 years ago. While the assignments weren't too challenging, I thought they were thorough in covering the material from class, and the material from class came straight from Professor Hwu's book.

Plus, the final exam was extremely harsh so I wouldn't have called it a joke.

⬐ frozenport

Compared to the physics classes or that algorithm class, I put my brain on auto-pilot. Sure, the final was hard but mostly because I didn't have time to write code in a word document, and people who went to the official exam area actually got significantly more time (I took it a few years before you).

Many things were missing from that class, including how to improve performance by ensuring that warp receives the optimal data size, for example by using float4.

I could have learned the same stuff by looking at his MOOC - which is what OP got bored of doing.

⬐ fiiiauuush

The material you find "easy" may be useful to others. You probably weren't the target audience.

I think for parallel computing, this udacity course is very nice too: https://www.udacity.com/course/intro-to-parallel-programming...