From 26d174f054fbb1339bf62f8566760777195da8e4 Mon Sep 17 00:00:00 2001
From: markus <markus.holzer@fau.de>
Date: Fri, 10 Jul 2020 09:45:15 +0200
Subject: [PATCH] Removed OpenCL parallel Datahandling test case
---
lbmpy_tests/test_lbstep.py | 39 +++++++++++++++++++++-----------------
1 file changed, 22 insertions(+), 17 deletions(-)
diff --git a/lbmpy_tests/test_lbstep.py b/lbmpy_tests/test_lbstep.py
index eabbf262..02e3c44a 100644
--- a/lbmpy_tests/test_lbstep.py
+++ b/lbmpy_tests/test_lbstep.py
@@ -54,24 +54,29 @@ def test_data_handling_2d_opencl():
pystencils.opencl.opencljit.init_globally()
print("--- LDC 2D test ---")
results = []
- for parallel in [True, False] if parallel_available else [False]:
- for gpu in [True, False] if gpu_available else [False]:
- if parallel and gpu and not hasattr(wLB, 'cuda'):
- continue
- print("Testing parallel: %s\tgpu: %s" % (parallel, gpu))
- opt_params = {'target': 'opencl' if gpu else 'cpu',
- 'gpu_indexing_params': {'block_size': (8, 4, 2)}}
- if parallel:
- from pystencils.datahandling import ParallelDataHandling
- blocks = wLB.createUniformBlockGrid(blocks=(2, 3, 1), cellsPerBlock=(5, 5, 1),
- oneBlockPerProcess=False)
- dh = ParallelDataHandling(blocks, dim=2)
- rho = ldc_setup(data_handling=dh, optimization=opt_params)
- results.append(rho)
- else:
- rho = ldc_setup(domain_size=(10, 15), parallel=False, optimization=opt_params)
- results.append(rho)
+ # Since waLBerla has no OpenCL Backend yet, it is not possible to use the
+ # parallel Datahandling with OpenCL at the moment
+
+ # TODO: Activate parallel Datahandling if Backend is available
+ parallel = False
+ for gpu in [True, False] if gpu_available else [False]:
+ if parallel and gpu and not hasattr(wLB, 'cuda'):
+ continue
+
+ print("Testing parallel: %s\tgpu: %s" % (parallel, gpu))
+ opt_params = {'target': 'opencl' if gpu else 'cpu',
+ 'gpu_indexing_params': {'block_size': (8, 4, 2)}}
+ if parallel:
+ from pystencils.datahandling import ParallelDataHandling
+ blocks = wLB.createUniformBlockGrid(blocks=(2, 3, 1), cellsPerBlock=(5, 5, 1),
+ oneBlockPerProcess=False)
+ dh = ParallelDataHandling(blocks, dim=2)
+ rho = ldc_setup(data_handling=dh, optimization=opt_params)
+ results.append(rho)
+ else:
+ rho = ldc_setup(domain_size=(10, 15), parallel=False, optimization=opt_params)
+ results.append(rho)
for i, arr in enumerate(results[1:]):
print("Testing equivalence version 0 with version %d" % (i + 1,))
np.testing.assert_almost_equal(results[0], arr)
--
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