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Add Nsight Compute Profiling to the SGEMM Lab #15

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3 changes: 3 additions & 0 deletions labs/sgemm-regtiled-coarsened/README.md
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Expand Up @@ -41,3 +41,6 @@ Your last RAI submission will be used for grading. Be sure that it
passes all tests for full points (you may still lose points for bugs
not exposed during testing).

## Use Nsight Compute to Profile Your Code

Remove the `#` character in the last command in -rai_build.yml to enable profiling. Note that you have to submit to the rai_amd64_exclusive queue by adding `--queue=rai_amd64_exclusive` to your RAI invocation.
3 changes: 2 additions & 1 deletion labs/sgemm-regtiled-coarsened/rai_build.yml
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@@ -1,7 +1,7 @@
# lab: Sgemm
rai:
version: 0.2
image: raiproject/pumps2018:amd64-cuda100
image: tonywukun/pumps2018:amd64-cuda100-nsighttest
resources:
cpu:
architecture: amd64
Expand All @@ -14,4 +14,5 @@ commands:
- cmake /src
- make
- ./sgemm -a
# - /usr/local/NVIDIA-Nsight-Compute/ncu --export "sgemm" --force-overwrite --target-processes all --kernel-name-base function --kernel-name regex:mysgemm --launch-skip-before-match 0 --section ComputeWorkloadAnalysis --section InstructionStats --section LaunchStats --section MemoryWorkloadAnalysis --section MemoryWorkloadAnalysis_Chart --section MemoryWorkloadAnalysis_Tables --section Occupancy --section SchedulerStats --section SourceCounters --section SpeedOfLight --section SpeedOfLight_HierarchicalSingleRooflineChart --section WarpStateStats --sampling-interval auto --sampling-max-passes 5 --sampling-buffer-size 33554432 --profile-from-start 1 --cache-control all --clock-control base ./sgemm -a