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Diffstat (limited to 'README.md')
| -rw-r--r-- | README.md | 17 |
1 files changed, 10 insertions, 7 deletions
@@ -4,6 +4,8 @@ ZLUDA is a drop-in replacement for CUDA on non-NVIDIA GPU. ZLUDA allows to run unmodified CUDA applications using non-NVIDIA GPUs with near-native performance. + + ZLUDA is work in progress. Follow development here and say hi on [Discord](https://discord.gg/sg6BNzXuc7). For more details see the announcement: https://vosen.github.io/ZLUDA/blog/zludas-third-life/ ## Usage @@ -12,8 +14,8 @@ ZLUDA is work in progress. Follow development here and say hi on [Discord](https ### Windows You should have recent AMD GPU driver ("AMD Software: Adrenalin Edition") installed.\ To run your application you should etiher: -* (Recommended approach) Copy ZLUDA-provided `nvcuda.dll` and `nvml.dll` into a path which your application uses to load CUDA. Paths vary application to application, but usually it's the directory where the .exe file is located -* Use ZLUDA launcher like below. ZLUDA launcher is known to be buggy and unfinished +* (Recommended approach) Copy ZLUDA-provided `nvcuda.dll` and `nvml.dll` from `target\release` (if built from sources) or `zluda` (if downloaded a zip package) into a path which your application uses to load CUDA. Paths vary application to application, but usually it's the directory where the .exe file is located +* Use ZLUDA launcher like below. ZLUDA launcher is known to be buggy and incomplete: ``` <ZLUDA_DIRECTORY>\zluda_with.exe -- <APPLICATION> <APPLICATIONS_ARGUMENTS> ``` @@ -25,7 +27,7 @@ Run your application like this: LD_LIBRARY_PATH=<ZLUDA_DIRECTORY> <APPLICATION> <APPLICATIONS_ARGUMENTS> ``` -where `<ZLUDA_DIRECTORY>` is the directory which contains ZLUDA-provided `libcuda.so`: `target\release` if you built from sources or `zluda` if you downloaded prebuilt package. +where `<ZLUDA_DIRECTORY>` is the directory which contains ZLUDA-provided `libcuda.so`: `target/release` if you built from sources or `zluda` if you downloaded prebuilt package. ### MacOS @@ -54,9 +56,10 @@ Not supported If you are building on Linux you must also symlink the ZLUDA output binaries after ZLUDA build finishes: ``` cd target/release -ln -s libnvcuda.so target/release/libcuda.so -ln -s libnvcuda.so target/release/libcuda.so.1 -ln -s libnvml.so target/release/libnvidia-ml.so +ln -s libnvcuda.so libcuda.so +ln -s libnvcuda.so libcuda.so.1 +ln -s libnvml.so libnvidia-ml.so +ln -s libnvml.so libnvidia-ml.so.1 ``` ## Contributing @@ -70,7 +73,7 @@ If you want to contribute a code fix or documentation update feel free to open a There's no architecture document (yet). Two most important crates in ZLUDA are `ptx` (PTX compiler) and `zluda` (AMD GPU runtime). A good starting point to tinkering the project is to run one of the `ptx` unit tests under a debugger and understand what it is doing. `cargo test -p ptx -- ::add_hip` is a simple test that adds two numbers. -Github issues tagged with ["help wanted"](https://github.com/vosen/ZLUDA/issues?q=is%3Aissue+is%3Aopen+label%3A%22help+wanted%22) are tasks that are self-containted. Their level of difficulty varies, they are not always great starting points, but they have a relatively clear definition of "done". +Github issues tagged with ["help wanted"](https://github.com/vosen/ZLUDA/issues?q=is%3Aissue+is%3Aopen+label%3A%22help+wanted%22) are tasks that are self-containted. Their level of difficulty varies, they are not always good beginner tasks, but they defined unambiguously. If you have questions feel free to ask on [#devtalk channel on Discord](https://discord.com/channels/1273316903783497778/1303329281409159270). |