809 self standard hwloc configs

experiments/raja-perf/experiment.py

@@ -55,8 +55,16 @@ def compute_applications_section(self):
                 f"Only one type of scaling per experiment is allowed for application package {self.name}"
             )
 
-        n_resources = {"n_ranks": 1}
-        problem_sizes = {"size": 1048576}
+        # n_resources = {"n_ranks": 1}
+        # problem_sizes = {"size": 1048576}
+
+        ######
+        factor = 6
+        scale = 4 * factor
+        init_problem_size = 536870912
+        n_resources = {"n_ranks": scale}
+        problem_sizes = {"size": init_problem_size // scale}
+        ######
 
         if self.spec.satisfies("+single_node"):
             for pk, pv in n_resources.items():

repo/raja-perf/application.py

@@ -18,7 +18,7 @@ class RajaPerf(ExecutableApplication):
             'mpi','network-point-to-point','network-latency-bound',
             'c++','raja','sycl','builtin-caliper']
 
-    executable('run', 'raja-perf.exe --size {size} -atsc ${CALI_CONFIG_MODE} -atcc ${OTHER_CALI_CONFIG}', use_mpi=True)
+    executable('run', 'raja-perf.exe --size {size} -v RAJA_HIP -t block_256 --kernels Polybench_JACOBI_1D --disable-warmup --npasses 5 -atsc ${CALI_CONFIG_MODE} -atcc ${OTHER_CALI_CONFIG}', use_mpi=True)
 
     workload('suite', executables=['run'])
 

repo/raja-perf/package.py

@@ -126,6 +126,7 @@ class RajaPerf(CachedCMakePackage, CudaPackage, ROCmPackage):
     homepage = "http://software.llnl.gov/RAJAPerf/"
     git      = "https://github.com/LLNL/RAJAPerf.git"
 
+    version("temp-add-outer-loop-for-kernel", branch="temp-add-outer-loop-for-kernel", submodules="True")
     version("develop", branch="develop", submodules="True")
     version("main",  branch="main",  submodules="True")
     version("2025.03.0", tag="v2025.03.0", submodules="True")