def node(host):
"""Select a node"""
if host == 'all':
for node in lib.get_nodes():
env.hosts.append(node['littlechef']['nodename'])
if not len(env.hosts):
abort('No nodes found')
else:
env.hosts = [host]
def node(host):
"""Select a node"""
if host == 'all':
for node in lib.get_nodes():
env.hosts.append(node['littlechef']['nodename'])
if not len(env.hosts):
abort('No nodes found')
else:
env.hosts = [host]
def list_nodes_with_recipe(recipe):
"""Show all nodes which have asigned a given recipe"""
for node in lib.get_nodes():
if recipe in lib.get_recipes_in_node(node):
lib.print_node(node)
else:
for role in lib.get_roles_in_node(node):
with open('roles/' + role + '.json', 'r') as f:
roles = json.loads(f.read())
# Reuse _get_recipes_in_node to extract recipes in a role
if recipe in lib.get_recipes_in_node(roles):
lib.print_node(node)
break
def list_nodes_with_recipe(recipe):
"""Show all nodes which have asigned a given recipe"""
for node in lib.get_nodes():
if recipe in lib.get_recipes_in_node(node):
lib.print_node(node)
else:
for role in lib.get_roles_in_node(node):
with open('roles/' + role + '.json', 'r') as f:
roles = json.loads(f.read())
# Reuse _get_recipes_in_node to extract recipes in a role
if recipe in lib.get_recipes_in_node(roles):
lib.print_node(node)
break
def benchmark_MNA(df):
components = get_components(df)
nodes = get_nodes(components)
# get unknown ivs
voltage_sources = get_vs(components)
num_nodes = len(nodes)
# generate b matrix, and initialize zero-filled A-matrix
b = construct_b(voltage_sources, num_nodes)
A = construct_A(b, components, voltage_sources, num_nodes)
start_cuda = timer()
mid_cuda = -1
try:
cupy_A = cp_sparse.csr_matrix(A)
cupy_b = cp.asarray(b)
mid_cuda = timer()
cupy_x = cp_sparse.linalg.lsqr(cupy_A, cupy_b)[0]
except:
print('failed to solve on gpu')
mid_cuda = -1
end_cuda = timer()
start_cpu = timer()
A = csr_matrix(A)
mid_cpu = timer()
x = lsqr(A, b)
end_cpu = timer()
if mid_cuda == -1:
cuda_trans_diff = ""
cuda_solve_diff = ""
else:
cuda_trans_diff = mid_cuda - start_cuda
cuda_solve_diff = end_cuda - mid_cuda
return {
'matrix_size': A.shape,
'num_components': len(components),
'cpu': {
'total': end_cpu - start_cpu,
'data transfer': mid_cpu - start_cpu,
'linear solve': end_cpu - mid_cpu
},
'cuda': {
'total': end_cuda - start_cuda,
'data transfer': cuda_trans_diff,
'linear solve': cuda_solve_diff
}
}
def compute_MNA(df, print_eqs=False):
components = get_components(df)
nodes = get_nodes(components)
# get unknown ivs
voltage_sources = get_vs(components)
num_nodes = len(nodes)
# generate b matrix, and initialize zero-filled A-matrix
b = construct_b(voltage_sources, num_nodes)
A = construct_A(b, components, voltage_sources, num_nodes)
cupy_A = cp_sparse.csr_matrix(A)
cupy_b = cp.asarray(b)
cupy_x = cp_sparse.linalg.lsqr(cupy_A, cupy_b)[0]
if print_eqs:
print("---" * A.shape[0], "\n", cupy_A, "\n", "---" * A.shape[0])
print(cupy_x)
print(cupy_b)
return cp.asnumpy(cupy_x)
def list_nodes_with_role(role):
"""Show all nodes which have asigned a given role"""
for node in lib.get_nodes():
recipename = 'role[' + role + ']'
if recipename in node.get('run_list'):
lib.print_node(node)
def list_nodes():
"""List all nodes"""
for node in lib.get_nodes():
lib.print_node(node)
def test_list_nodes(self):
"""Should list all configured nodes"""
expected = [{'name': 'testnode', 'run_list': ['recipe[subversion]']}]
self.assertEquals(lib.get_nodes(), expected)
def test_list_nodes(self):
"""Should list all configured nodes"""
expected = [{'name': 'testnode', 'run_list': ['recipe[subversion]']}]
self.assertEquals(lib.get_nodes(), expected)
def list_nodes_detailed():
"""Show a detailed list of all nodes"""
for node in lib.get_nodes():
lib.print_node(node, detailed=True)
def list_nodes():
"""List all configured nodes"""
for node in lib.get_nodes():
lib.print_node(node)
def list_nodes_with_role(role):
"""Show all nodes which have asigned a given role"""
for node in lib.get_nodes():
recipename = 'role[' + role + ']'
if recipename in node.get('run_list'):
lib.print_node(node)
def list_nodes():
"""List all nodes"""
for node in lib.get_nodes():
lib.print_node(node)
