cburdick13
No user record in our sample, but cburdick13 has activity below (stories or comments). Likely we have partial data — the full bulk-load will fill profiles in.
No user record in our sample, but cburdick13 has activity below (stories or comments). Likely we have partial data — the full bulk-load will fill profiles in.
The sample is really designed to show the simplicity of the syntax, and the performance is just a side effect. Where you'll see a bigger performance difference with numPy/cuPy is when kernel fusion happens where MatX is…
Hi, if you don't mind opening an issue asking for this we can run these and put in the readme.
Hi, I looked into this and it seems that it is indeed using >= Depends: cuda-libraries-11-8 (>= 11.8.0), cuda-drivers (>= 520.61.05)
Hi, yes, the original development was started for radar users who did not know CUDA but needed to write in c++. Many of our examples and code are radar related for that reason.
We have benchmarks in the benchmarks directory, but these are for things like convolution, matrix multiples, etc. It's not for running a traditional benchmark set like resnet. Like most benchmarks it really depends on…
Hi, those libraries don't have a GPU counterpart, and for matrix multiplication we only support GPU right now.
I have to admit I'm only tangentially familiar with gnuradio, but matx should be able to integrate with any C++17 codebase. We have several examples of integration with our streaming sensor pipeline called holoscan. see…
That's a fair point. I'll look into it.
Hi, what specifically are you looking to benchmark on the K80? Users are free to contribute and we've had many external PRs. Contribution guide is here: https://github.com/NVIDIA/MatX/blob/main/CONTRIBUTING.md
If you use the run files rather than the package manager files it's always installed in completely separate folders inside /use/local/cuda. What you're describing with an "all" install can somewhat be accomplished with…
I agree we should update it given that it's also a very old comparison (2 years now). The cuPy comparison should be fair since it was the same GPU. I addressed it more here: https://news.ycombinator.com/item?id=37760120
Hi, you can choose not to install the driver with a CUDA install, and to download the driver separately.
The main difference is Jax is for python primarily, while MatX is c++. This might seem like a poor answer, but in many domains (quasi-real time, signal processing, etc) the language is important to give certainty…
The main difference is the GPU part. This is a large difference because the same lazy evaluated template type can be run on the CPU or GPU through what we call an executor. On the CPU it's likely very similar to how…
Good point, and agreed the landing page is a bit sensational. I mentioned it elsewhere but between MatX and cuPy we see a 3-4x performance difference on average. The gap tends to widen with more complex workflows where…
We typically support whatever the underlying library supports. For int8 the support would come from cuBLASLt currently. I don't believe that or Cutlass supports mixed precision inputs, but I can check.
We've tried our best to match python as well as we can, or falling back to matlab-style if Python doesn't have it. Many of our unit tests are verified against python, so the conversion is typically very easy. The one…
Hi, what matrix sizes and types are you working with and how many batches? In general it sounds be similar to eigen, but with GPU support. We have several svd methods for different scenarios, so if you give us the info…
That's right, we've tested down to pascal, but this should work on Kepler too since CUDA and the underlying libraries support it.
Hi, besides an (subjectively) easier syntax, the performance should be higher compared to libtorch. Every operator expression (think of it as an arithmetic expression) is evaluated at compile-time and is often fused…
Hi, having feature parity with cuPy is a daunting task, especially for a C++ library. At this point we feel we have a good foundation for all kinds of basic and advanced tensor manipulations, and have a growing number…
Hi, MatX currently has partial support for CPUs too. Please see this comment: https://news.ycombinator.com/item?id=37758635
Currently we support both CUDA and CPU to some extent. CPU is done through standard C++ (and soon stdpar). Obviously standard C++ is problematic since it doesn't include everything we support (FFTs, matrix multiplies,…
Hi all, I'm one of the maintainers of MatX. I didn't expect it to hit HN this soon, but happy to answer any questions.