1 files changed, 78 insertions, 5 deletions

diff --git a/README.md b/README.md
index f2be718..11ad153 100644
--- a/README.md
+++ b/README.md
@@ -13,16 +13,37 @@ Please cite this paper in any work which leverages our library. Here's the BibTe
   year={2023},
   month={May},
   pages={54--66},
+  doi={10.1109/RTAS58335.2023.00012},
   _series={RTAS}
 }
 ```
 
-Please see [the paper](https://www.cs.unc.edu/~jbakita/rtas23.pdf) and `libsmctrl.h` for details and examples of how to use this library.
+The ability for `libsmctrl` to work on unmodified tasks was developed as part of a follow-up paper:
+
+_J. Bakita and J. H. Anderson, "Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems", Proceedings of the 37th Euromicro Conference on Real-Time Systems, pp. 18:1-18:24, July 2025._
+
+Please cite this paper in any work which uses this for partitioning unmodified tasks. Here's the BibTeX entry:
+```
+@inproceedings{bakita2025hardware,
+  title={Hardware Compute Partitioning on {NVIDIA} {GPUs} for Composable Systems},
+  author={Bakita, Joshua and Anderson, James H},
+  booktitle={Proceedings of the 37th Euromicro Conference on Real-Time Systems},
+  year={2025},
+  month={July},
+  pages={18:1--18:24},
+  doi={10.1109/ECRTS.2025.18},
+  _series={ECRTS}
+}
+```
+
+Please see [the first paper](https://www.cs.unc.edu/~jbakita/rtas23.pdf), [the second paper](https://www.cs.unc.edu/~jbakita/ecrts25.pdf) and `libsmctrl.h` for details and examples of how to use this library.
 We strongly encourage consulting those resources first; the below comments serve merely as an appendum.
 
 ## Run-time Dependencies
 `libcuda.so`, which is automatically installed by the NVIDIA GPU driver.
 
+(Technically `libdl` is also required, but this should never need to be manually installed. This is a dependency of CUDA, and is also part of the GNU C Standard Library starting with version 2.34.)
+
 ## Building
 To build, ensure that you have `gcc` installed and access to the CUDA SDK including `nvcc`. Then run:
 ```
@@ -66,8 +87,52 @@ nvcc benchmark.cu -o benchmark -I/playpen/libsmctl -lsmctrl -lcuda -L/playpen/li
 ```
 The resultant `benchmark` binary should be portable to any system with an equivalent or newer version of the NVIDIA GPU driver installed.
 
+## Use Without Application Modification
+As an alternative to modifying your application, `libsmctrl` can be installed system-wide, and partitions for each application can be set via the `nvtaskset` tool.
+The `nvtaskset` tool works very similarly to the Linux CPU-affinity-setting tool `taskset`.
+
+To install `libsmctrl` system-wide, such that all CUDA-using applications automatically load it, ensure that `patchelf` is installed (`sudo apt install patchelf`), and run:
+```
+make libcuda.so.1 install
+```
+Or, if you do not want to modify any system-wide state, and only want `libsmctrl` loaded as part of anything run from this console:
+```
+make libcuda.so.1
+export LD_LIBRARY_PATH=$(pwd)
+```
+(This works because CUDA is always dynamically loaded from `libcuda.so.1`, and `lbsmctrl` creates a "fake" `libcuda.so.1` in this directory that wraps CUDA.
+ Setting `LD_LIBRARY_PATH` ensures that the wrapped version is the first one loaded.
+ The only difference with running `make install` is that it copies our "fake" `libcuda.so.1` to a location where the loader will automatically find it.)
+
+And then to start an application within a specific TPC partition, e.g., the first 10 TPCs:
+```
+./nvtaskset -t 0-9 my_program my_args
+```
+Note that this will automatically start NVIDIA MPS, which is a prerequisite to co-run tasks on NVIDIA GPUs without timeslicing.
+
+And to change the TPCs available for a process ID 1234 to to the first 10 TPCs:
+```
+./nvtaskset -tp 0-9 1234
+```
+
+Or, to change a process of ID 1234 to only run on GPC 3:
+```
+./nvtaskset -gp 3 1234
+```
+
+To remove the system-wide installation of `libsmctrl`, run:
+```
+make remove
+```
+
 ## Run Tests
-To test partitioning:
+
+To run them all:
+```
+make run_tests
+```
+
+If you prefer to run them individually, to test partitioning:
 ```
 make tests
 ./libsmctrl_test_global_mask
@@ -82,18 +147,26 @@ make tests
 ./libsmctrl_test_next_mask_override
 ```
 
-And if `nvdebug` has been installed:
+To test that `nvtaskset` can dynamically change the mask of a running program:
 ```
-make tests
+make libsmctrl_test_supreme_mask
+./libsmctrl_test_supreme_mask
+```
+
+To test that TPC to GPC mappings can be obtained (if `nvdebug` has been installed):
+```
+make libsmctrl_test_gpc_info
 ./libsmctrl_test_gpc_info
 ```
 
+The `CUDA_VISIBLE_DEVICES` environment variable can be set to run any of the partitioning tests on a different GPU.
+
 ## Supported GPUs
 
 #### Known Working
 
 - NVIDIA GPUs from compute capability 3.5 through 8.9, including embedded "Jetson" GPUs
-- CUDA 6.5 through 12.6
+- CUDA 6.5 through 12.8
 - `x86_64` and Jetson `aarch64` platforms
 
 #### Known Issues