Update READMEupdate_docs

1 files changed, 10 insertions, 7 deletions

diff --git a/README.md b/README.md
index 2b6a815..578829c 100644
--- a/README.md
+++ b/README.md
@@ -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.
 
+![GeekBench 5.5.1 chart](geekbench.svg)
+
 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).