| Commit message (Collapse) | Author | Age |
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- Add an "all" build target
- Fix build if libcuda.so is not on linker search path
- Do not assume that nvcc is available on $PATH
- Allow specifying CFLAGS and LDFLAGS when running make
- Allow passing non-standard CUDA build locations to make
Suggested usage if CUDA is installed in a non-standard location,
say, /playpen/jbakita/CUDA/cuda-archive/cuda-12.2:
make CUDA=/playpen/jbakita/CUDA/cuda-archive/cuda-12.2
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The prefix "lib" should not be included, per the documentation.
This was not caught in local tests as the fallback was always used
locally.
Patch courtesy of Guanbin Xu <xugb@mail.ustc.edu.cn>.
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Make automatically provides CXX and CC, and these manual
definitions were being ignored.
Also fix a missing space in one of the messages from the tests.
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Use a different callback to intercept the TMD/QMD later in the
launch pipeline.
Major improvements:
- Fix bug with next mask not overriding stream mask on CUDA 11.0+
- Add CUDA 6.5-10.2 support for next- and global-granularity
partitioning masks on x86_64 and aarch64 Jetson
- Remove libdl dependency
- Partially support TMD/QMD Version 4 (Hopper)
Minor improvements:
- Check for sufficient CUDA version before before attempting to
apply a next-granularity partitioning mask
- Only check for sufficient CUDA version on the first call to
`libsmctrl_set_next_mask()` or `libsmctrl_set_global_mask()`,
rather than checking every time (lowers overheads)
- Check that TMD version is sufficient before modifying it
- Improve documentation
Issues:
- Partitioning mask bits have a different meaning in TMD/QMD
Version 4 and require floorsweeping and remapping information to
properly construct. This information will be forthcoming in
future releases of libsmctrl and nvdebug.
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Also test and note that stream masking on CUDA 6.5 seems impossible.
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Also update a comment
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Commit 3f9bda39 made an error by using the pre-CUDA-12 mask
structure layout on CUDA 12.6 on aarch64 Jetson. Switch to the
CUDA 12+ layout (as used on x86_64).
Tests work either way on the Jetson Orin, so this change is not
strictly required, but seems advisable to support potenital large
(PCIe-attached?) GPUs on Jetson/DRIVE platforms.
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Credit to Nordine Feddal for testing CUDA 12.4 on 550.544.14.
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Also allow building with an alternate version of g++ for backwards
compatibility.
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Stream-level masks should always override globally-set masks.
Next-kernel masks should always override both stream-level masks
and globally-set masks.
Tests reveal an issue with the next-kernel mask not overriding the
stream mask on CUDA 11.0+. CUDA appears to apply the per-stream
mask to the QMD/TMD after `launchCallback()` is triggered, making
it impossible to override as currently implemented.
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Also rewrite the global masking test to be much more thorough.
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Previously did not delineate between aarch64 and x86_64 stream
offsets, causing incorrect offsets to be used in many circumstances.
This has now been fixed.
A new function, libsmctrl_set_stream_mask_ext() has also been added
which supports masking up to 128 TPCs (rather than just 64).
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nvcc links against a stub version of libcuda.so by default which is
missing a required symbol starting around CUDA 11.8. Use libdl to
resolve the symbol at runtime instead.
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Also use static linking for tests, to avoid a need to set
LD_LIBRARY_PATH to include the libsmctrl directory.
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Also improve documentation and abort with an error message if
attempting to set a global SM mask on an unsupported CUDA version.
(Would crash/corrupt state before.)
Also uncomment a line which errantly disabled global masking on
CUDA 10.2 on aarch64.
Tested with CUDA 10.2 on:
- x86_64 (GTX 1060 3GB, driver 440.100, jbakita-old.cs.unc.edu)
- aarch64 (Jetson TX2, driver r32.5, grizzly.cs.unc.edu)
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Necessary for declarations of included functions. Absence would
result in a compilation error for programs omitting this include.
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This function was previously unreliable when using CUDA 9.0 on the
Jetson TX2.
Also update some version comments and remove `set_sm_mask()`---a
legacy partitioning function that's no longer used.
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Initially supports the GPU information functions via:
- pysmctrl.get_gpc_info(dev_id)
- pysmctrl.get_tpc_info(dev_id)
- pysmctrl.get_tpc_info_cuda(cuda_dev_id)
All functions are extensively documented. See pysmctrl/__init__.py
for details.
Device partitioning functions have yet to be mapped into Python, as
these will require more testing.
As part of this:
- libsmctrl_get_*_info() functions have been modified to consistently
return positive error codes.
- libsmctrl_get_tpc_info() now uses nvdebug-style device numbering and
uses libsmctrl_get_gpc_info() under the covers. This should be more
reliable.
- libsmctrl_get_tpc_info_cuda() has been introduced as an improved
version of the old libsmctrl_get_tpc_info() function. This continues
to use CUDA-style device numbering, but is now resiliant to CUDA
failures.
- Various minor style improvements in libsmctrl.c
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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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