Comments (4)
DavidMChan
commented on June 3, 2024
1
All of the pre-built binaries are linked with MKL, however the code itself supports OpenBLAS and ATLAS. You should be able to build it from source following the instructions: https://github.com/CannyLab/tsne-cuda/wiki/Installation
You may also need to make modifications for the 4090/CUDA 12, given that it's not officially supported (we don't have a 4090 for testing). The if statement here will need to be adapted to add the compute architecture compute_89 and sm_89 for the 4090, and the options here will need to be adjusted for performance (the native setting will be fine, but will likely not make use of the device efficiently).
I'm not sure if there are any breaking changes for CUDA 12 (from 11), so you may run into this as well if any parts of the API were deprecated/removed.
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DavidMChan
commented on June 3, 2024
It looks like you don't have intel's MKL library linked into your environment. How did you install the code? If you installed from source, did you install MKL?
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apoorvagnihotri
commented on June 3, 2024
No, I haven't. I have previously read that MKL library doesn't play well
with AMG CPUs (slower).
Additionally, other Intel libraries like sklearn-intelex tend to give
incorrect results altogether on AMD systems.
scikit-learn/scikit-learn#23212
Given the problems of using Intel libraries on AMD CPUs, is there any
alternative to using MKL as a dependency?
…On Tue, Feb 21, 2023, 11:39 PM David Chan ***@***.***> wrote:
It looks like you don't have intel's MKL library linked into your
environment. How did you install the code? If you installed from source,
did you install MKL?
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Related Issues (20)
- Feature Request: Custom distance matrix input HOT 3
- CMake error during installation from source HOT 4
- 403 Error when downloading wheels HOT 1
- Failed to cudaFree pointer issue & Memory issue HOT 2
- tsnecuda equivalent for M1 chip HOT 1
- Warning gives a moving target number of training points that could not be satisfied HOT 1
- CUBLAS_STATUS_NOT_INITIALIZED
- CUDA error 209 no kernel image is available for execution on the device HOT 6
- Aborted (core dumped) without any other error messages HOT 1
- TSNE(n_components=1)
- CUBLAS_STATUS_INVALID_VALUE
- CUBLAS_STATUS_NOT_INITIALIZED when importing Datashader *before* running tsnecuda HOT 1
- stuck at Initializing cuda handles HOT 3
- Fail with CUDA error 9. HOT 3
- tsne.fit_transform() prematurely ends before function return in a function call
- Gradient problem HOT 1
- ImportError: libcudart.so.11.0: cannot open shared object file: No such file or directory HOT 1
- Is there any way to select the GPU ordinal for the tSNE execution? HOT 1
- random_seed does not seem to work HOT 1
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