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This is huge. Anyone who was considering AMD + ROCm as an alternative to NVIDIA in the AI space isn’t anymore. I’m one of those people who can’t (won’t) learn C++ to the extent required to effectively write code for GPU execution…. But to have a direct pipeline to the GPU via Python. Wow. The efficiency implications are huge, not just for Python libraries like PyTorch, but also anything we write that runs on an NVIDI…
Rust support next? RN I am manually [de]serializing my data structures as byte arrays to/from the kernels. It would be nice to have truly shared data structures like CUDA gives you in C++!
I'm no GPU programmer, but seems easy to use even for someone like me. I pulled together a quick demo of using the GPU vs the CPU, based on what I could find ( https://gist.github.com/victorb/452a55dbcf59b3cbf84efd8c3097... ) which gave these results (after downloading 2.6GB of dependencies of course): Creating 100 random matrices of size 5000x5000 on CPU... Adding matrices using CPU... CPU matrix addition completed…
Curious what the timing would be if it included the memory transfer time, e.g. matricies = [np.random(...) for _ in range] time_start = time.time() cp_matricies = [cp.array(m) for m in matrices] add_(cp_matricies) sync time_end = time.time()
print("Adding matrices using GPU...")
start_time = time.time()
gpu_result = add_matrices(gpu_matrices)
cp.cuda.get_current_stream().synchronize() # Not 100% sure what this does
elapsed_time = time.time() - start_time
>In 2024, Python became the most popular programming language in the world — overtaking JavaScript — according to GitHub’s 2024 open source survey. I wonder why Python take over the world? Of course, it's easy to learn, it might be easy to read and understand. But it also has a few downsides: low performance, single threaded, lack of static typing.
My guess: it's the community.
I'm no GPU programmer, but seems easy to use even for someone like me. I pulled together a quick demo of using the GPU vs the CPU, based on what I could find ( https://gist.github.com/victorb/452a55dbcf59b3cbf84efd8c3097... ) which gave these results (after downloading 2.6GB of dependencies of course): Creating 100 random matrices of size 5000x5000 on CPU... Adding matrices using CPU... CPU matrix addition completed…
Thank you. I scrolled up and down the article hoping they included a code sample.
>In 2024, Python became the most popular programming language in the world — overtaking JavaScript — according to GitHub’s 2024 open source survey. I wonder why Python take over the world? Of course, it's easy to learn, it might be easy to read and understand. But it also has a few downsides: low performance, single threaded, lack of static typing.
>In 2024, Python became the most popular programming language in the world — overtaking JavaScript — according to GitHub’s 2024 open source survey. I wonder why Python take over the world? Of course, it's easy to learn, it might be easy to read and understand. But it also has a few downsides: low performance, single threaded, lack of static typing.
Rust support next? RN I am manually [de]serializing my data structures as byte arrays to/from the kernels. It would be nice to have truly shared data structures like CUDA gives you in C++!
The Rust-CUDA project just recently started up again [0], I've started digging into it a little bit and am hoping to contribute to it since the summers are a little slower for me. [0] https://github.com/rust-gpu/rust-cuda
>In 2024, Python became the most popular programming language in the world — overtaking JavaScript — according to GitHub’s 2024 open source survey. I wonder why Python take over the world? Of course, it's easy to learn, it might be easy to read and understand. But it also has a few downsides: low performance, single threaded, lack of static typing.
Perhaps performance, multi threading, and static typing are not the #1 things that make a language great. My guess: it's the community.
>In 2024, Python became the most popular programming language in the world — overtaking JavaScript — according to GitHub’s 2024 open source survey. I wonder why Python take over the world? Of course, it's easy to learn, it might be easy to read and understand. But it also has a few downsides: low performance, single threaded, lack of static typing.
Not sure what "most popular programming language in the world" even means, in terms of existing projects? In terms of developers who consider it their main language? In terms of existing actually active projects? According to new projects created on GitHub that are also public?
My guess is that it's the last one, which probably isn't what one would expect when hearing "the most popular language in the world", so worth keeping in mind.
But considering that AI/ML is the hype today, and everyone want to get their piece of the pie, it makes sense that there is more public Python projects created on GitHub today compared to other languages, as most AI/ML is Python.