Additional tests for packinfo generation & fast approximation for div and sqrt

pystencils_tests/test_cudagpu.py

@@ -4,7 +4,7 @@ from pystencils import Field, Assignment
 from pystencils.simp import sympy_cse_on_assignment_list
 from pystencils.gpucuda.indexing import LineIndexing
 from pystencils.slicing import remove_ghost_layers, add_ghost_layers, make_slice
-from pystencils.gpucuda import make_python_function, create_cuda_kernel
+from pystencils.gpucuda import make_python_function, create_cuda_kernel, BlockIndexing
 import pycuda.gpuarray as gpuarray
 from scipy.ndimage import convolve
 
@@ -145,3 +145,8 @@ def test_periodicity():
     periodic_gpu_kernel(pdfs=arr_gpu)
     arr_gpu.get(gpu_result)
     np.testing.assert_equal(cpu_result, gpu_result)
+
+
+def test_block_size_limiting():
+    res = BlockIndexing.limit_block_size_to_device_maximum((4096, 4096, 4096))
+    assert all(r < 4096 for r in res)

pystencils_tests/test_fast_approximation.py

@@ -10,11 +10,18 @@ def test_fast_sqrt():
 
     assert len(insert_fast_sqrts(expr).atoms(fast_sqrt)) == 1
     assert len(insert_fast_sqrts([expr])[0].atoms(fast_sqrt)) == 1
+    ast = ps.create_kernel(ps.Assignment(g[0, 0], insert_fast_sqrts(expr)), target='gpu')
+    code_str = str(ps.show_code(ast))
+    assert '__fsqrt_rn' in code_str
 
-    expr = 3 / sp.sqrt(f[0, 0] + f[1, 0])
+    expr = ps.Assignment(sp.Symbol("tmp"), 3 / sp.sqrt(f[0, 0] + f[1, 0]))
     assert len(insert_fast_sqrts(expr).atoms(fast_inv_sqrt)) == 1
+
     ac = ps.AssignmentCollection([expr], [])
     assert len(insert_fast_sqrts(ac).main_assignments[0].atoms(fast_inv_sqrt)) == 1
+    ast = ps.create_kernel(insert_fast_sqrts(ac), target='gpu')
+    code_str = str(ps.show_code(ast))
+    assert '__frsqrt_rn' in code_str
 
 
 def test_fast_divisions():