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Rather than requiring libsmctrl.so to be preloaded, we now wrap
libcuda.so.1. All CUDA-using applications will load libcuda.so.1,
ensuring that our wrapper will always be dynamically loaded, no
matter if LD_PRELOAD is enabled, or if a program has been staticly
linked. All that needs to be done is that the location of our
"fake" libcuda.so.1 need to be put within the loader search path.
This can be done by setting LD_LIBRARY_PATH, or by installing
our wrapper into /lib/x86_64-linux-gnu.
The mask can still be set via the LIBSMCTRL_MASK environment
variable, but the easier-to-use nvtaskset tool is now the
recommended way to view or change the supreme TPC mask for any
CUDA-using application. This allows launching a program on the
first two GPCs via a command as simple as:
./nvtaskset -g 0-1 ./a_program a_program_args
(Note that use of the -g option requires the nvdebug kernel module
to first be loaded.)
These changes support the final version of the ECRTS'25 paper.
Note that nvtaskset does not yet fully support multi-GPU systems.
Bugfixes:
- Fix crash that would occur if both libsmctrl.so and libsmctrl.a
were built into an application.
- Correctly use GPU ID when initializing a context in
`libsmctrl_test_gpc_info`.
- Include `nvtaskset` as a prerequisite for
`libsmctrl_test_supreme_mask`.
- Fix malfunction of `libsmctrl_test_gpc_info` if
CUDA_VISIBLE_DEVICES is set.
Other minor changes:
- Adds make target to run all the tests.
- Fixes typos in comments.
- Enables -Wall build option.
- Upgrades supreme mask from 64 to 128 bits.
- Removes `detect_parker_soc()` from the global namespace.
- Adjusts test messages to be more succinct.
- Updates README with overview of how to partition unmodified
applications, more details on the tests, and information on the
new ECRTS'25 paper.
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These updates are featured in the 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 (ECRTS), to appear,
Jul 2025.
They:
1. Fix reported GPC to TPC mappings (requires nvdebug update).
2. Add support for a "supreme" mask, which overrides all others and
can be set on a per-process basis via an environment variable,
and optionally modified at runtime via the nvtaskset utility.
3. Add test for the supreme mask.
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This function would previously would yield invalid results for
GPUs with more than 31 TPCs.
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- Tested working with cuda_scheduling_examiner
- Supports everything described in the accepted RTAS'23 paper
- Can be used as either a shared or staticly-linked library
- Documented in libsmctrl.h
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