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Ask HN: Best place to learn GPU programing?

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Re: Ask HN: Best place to learn GPU programing?

#51

Post by beagle3 »

gtani wrote: post #44
beagle3 wrote: post #41

I last did GPU programming around the transition from just-shaders to gpgpu... And I want to come back. However, I don't want to buy new hardware just yet. In addition to all the study materials posted, can anyone recommend a good hosted GPU setup for experiments? e.g. what kind of EC2/GCE instance would be a cost effective way to [re]learn GPU programming?

People commonly spend US$80+/month on training deep learning models on EC2, when you can now buy a brand new 980Ti for $440 from newegg, and the very capable 970 at $280. If you don't have a motherboard/PS that supports 2 video cards at 16 PCIe 3.0 lanes each, it's a worthy investment. There are wrinkles like if you're doing double precision arithmetic, consumer cards from nvidia since the Titan blacks are 12:1 fp32:…

Thanks. For sure, if I do anything serious I will buy my own hardware. But I'd like to play a little to get a feel - I'm sure a $20 over one month will pay back dividends in the understanding of how/what/whether comes next. I'm just asking for advice about those $20 (or $40 or $80 or however much they end up being)

Re: Ask HN: Best place to learn GPU programing?

#52

Post by fitzwatermellow »

If you want to dive in deep right away, an interesting summer project would be to create hybrid client / server gpu clusters using webgl and the browser!

Install node-opencl and CL.js and check out how Graphistry is using scalable distributed gpus for visualization of massive data sets ;)

CL.js:

https://github.com/graphistry/cljs

Node-OpenCL

https://github.com/mikeseven/node-opencl

Graphistry

https://www.graphistry.com/

Re: Ask HN: Best place to learn GPU programing?

#53

Post by joe_the_user »

saltcured wrote: post #49
valine wrote: post #31

Earlier quoted context omitted.

Would you recommend OpenGL? I was under the impression that OpenCL was the equivalent of Cuda and OpenGL was specifically for 2d / 3d rendering.

I imagine it was a typo, but... I personally have found PyOpenCL and the vispy.gloo OpenGL APIs to be very convenient together (along with Numpy and Scipy of course). If it fits your goals, a useful mental model is that you are programming Numpy ndarray data, and all these tools just fit together to let you manage the data elements, apply transforms, and view them. You should be thinking about the math that solves yo…

If you read the op, their reference to OpenGl isn't a typo, they are linking to books and articles on OpenGl and recommending learning this before Cuda.

Re: Ask HN: Best place to learn GPU programing?

#54

Post by gtani »

beagle3 wrote: post #51
gtani wrote: post #44

Earlier quoted context omitted.

People commonly spend US$80+/month on training deep learning models on EC2, when you can now buy a brand new 980Ti for $440 from newegg, and the very capable 970 at $280. If you don't have a motherboard/PS that supports 2 video cards at 16 PCIe 3.0 lanes each, it's a worthy investment. There are wrinkles like if you're doing double precision arithmetic, consumer cards from nvidia since the Titan blacks are 12:1 fp32:…

Thanks. For sure, if I do anything serious I will buy my own hardware. But I'd like to play a little to get a feel - I'm sure a $20 over one month will pay back dividends in the understanding of how/what/whether comes next. I'm just asking for advice about those $20 (or $40 or $80 or however much they end up being)

Well, there's not much price pressure from azure, you could try the others in nvidia's list: https://www.reddit.com/r/MachineLearning/comments/46ict5/bes...

Also watch spot price instances, go on weekends: https://ec2price.com/?product=Linux/UNIX&type=g2.2xlarge&reg...

Re: Ask HN: Best place to learn GPU programing?

#55

Post by mattkrause »

woodcut wrote: post #39
hubatrix wrote: post #35

Earlier quoted context omitted.

edit: thats not an issue I already have NVIDIA Corporation GM107 [GeForce GTX 750 Ti] (rev a2) to work on. but why OpenCL and not CUDA ?

OpenCL vs CUDA is pretty boring debate, both run on the same hardware and so have similar performance. Difference is in the tooling and ecosystems, you can run OpenCL on FPGA's for example.

Out of curiosity, has anyone successfully deployed some OpenCL code across very different platforms?

It seems neat that it'll compile and run on a GPU, CPU or FPGA, but it seems like code written for one style of architecture would be appallingly slow on the others.

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