def completeConfiguration(self, props):
self.num_java_threads = props.getValue(self.p_num_java_threads)
self.num_sim_GPU = props.getValue(self.p_num_sim_GPU)
self.use_GPU_for_creation = props.getValue(self.p_use_GPU_for_creation)
NodeThreadPool.setNumJavaThreads(self.num_java_threads)
NEFGPUInterface.setRequestedNumDevices(self.num_sim_GPU)
WeightedCostApproximator.setUseGPU(self.use_GPU_for_creation)
def completeConfiguration(self,props):
self.num_java_threads=props.getValue(self.p_num_java_threads)
self.num_sim_GPU=props.getValue(self.p_num_sim_GPU)
self.use_GPU_for_creation=props.getValue(self.p_use_GPU_for_creation)
NodeThreadPool.setNumJavaThreads(self.num_java_threads)
NEFGPUInterface.setRequestedNumDevices(self.num_sim_GPU)
WeightedCostApproximator.setUseGPU(self.use_GPU_for_creation)
def __init__(self,network):
self.nodes=[]
self.projections=[]
self.tasks=[]
self.network=network
self.initialize(network)
if NodeThreadPool.getNumJavaThreads() > 0:
NEFGPUInterface.requireAllOutputsOnCPU(True);
self.thread_pool=NodeThreadPool(network,[]);
else:
self.thread_pool=None;
def initPanel(self):
IntegerPanel.initPanel(self)
num_avail_devices = NEFGPUInterface.getNumAvailableDevices()
if num_avail_devices < 1:
self.tf.setEnabled(False)
self.tf.setEditable(False)
error_message = " %s" % (NEFGPUInterface.getErrorMessage())
error_message_label = JLabel(error_message)
error_message_label.setForeground(Color.red)
self.add(error_message_label)
def initPanel(self):
IntegerPanel.initPanel(self)
num_avail_devices = NEFGPUInterface.getNumAvailableDevices()
if num_avail_devices < 1:
self.tf.setEnabled(False)
self.tf.setEditable(False)
error_message = " %s" % (NEFGPUInterface.getErrorMessage())
error_message_label = JLabel(error_message)
error_message_label.setForeground(Color.red)
self.add(error_message_label)
class ParallelizationConfiguration(IConfigurable):
num_java_threads = NodeThreadPool.getNumJavaThreads()
num_sim_GPU = NEFGPUInterface.getRequestedNumDevices()
use_GPU_for_creation = WeightedCostApproximator.getUseGPU()
p_num_java_threads = PInt('Number of Java Threads', num_java_threads, 1,
NodeThreadPool.getMaxNumJavaThreads())
p_num_sim_GPU = PGpuCount('Number of GPU\'s for Simulation')
p_use_GPU_for_creation = PGpuUse('Use GPU for Ensemble Creation')
properties = [p_num_java_threads, p_num_sim_GPU, p_use_GPU_for_creation]
def __init__(self):
self.button = make_button('parallelization', self.do_configure,
'Configure Parallelization')
self.button.enabled = True
def do_configure(self, event):
self.p_num_java_threads.setDefaultValue(
NodeThreadPool.getNumJavaThreads())
self.p_num_sim_GPU.setDefaultValue(
NEFGPUInterface.getRequestedNumDevices())
self.p_use_GPU_for_creation.setDefaultValue(
WeightedCostApproximator.getUseGPU())
uc = ca.nengo.ui.configurable.managers.UserTemplateConfigurer(self)
try:
uc.configureAndWait()
except ConfigException, e:
e.defaultHandleBehavior()
def do_configure(self, event):
self.p_num_java_threads.setDefaultValue(NodeThreadPool.getNumJavaThreads())
self.p_num_sim_GPU.setDefaultValue(NEFGPUInterface.getRequestedNumDevices())
self.p_use_GPU_for_creation.setDefaultValue(WeightedCostApproximator.getUseGPU())
uc=ca.nengo.ui.configurable.managers.UserTemplateConfigurer(self)
try:
uc.configureAndWait()
except ConfigException, e:
e.defaultHandleBehavior()
def do_configure(self, event):
self.p_num_java_threads.setDefaultValue(
NodeThreadPool.getNumJavaThreads())
self.p_num_sim_GPU.setDefaultValue(
NEFGPUInterface.getRequestedNumDevices())
self.p_use_GPU_for_creation.setDefaultValue(
WeightedCostApproximator.getUseGPU())
uc = ca.nengo.ui.configurable.managers.UserTemplateConfigurer(self)
try:
uc.configureAndWait()
except ConfigException, e:
e.defaultHandleBehavior()
def __init__(self,network):
self.nodes=[]
self.projections=[]
self.network=network
self.initialize(network)
if NEFGPUInterface.getUseGPU():
gpuNodes = LocalSimulator.collectNodes(self.nodes)
gpuNetworkArrays = LocalSimulator.collectNetworkArraysForGPU(self.nodes)
gpuProjections = LocalSimulator.collectProjections(self.nodes, self.projections)
self.thread_pool=NEFGPUInterface(gpuNodes, gpuProjections, gpuNetworkArrays)
elif NodeThreadPool.isMultithreading():
multithread_nodes = LocalSimulator.collectNodes(self.nodes)
multithread_projs = LocalSimulator.collectProjections(self.nodes, self.projections)
self.thread_pool=NodeThreadPool(multithread_nodes, multithread_projs)
else:
self.thread_pool=None
def __init__(self, name):
default = NEFGPUInterface.getRequestedNumDevices()
maximum = NEFGPUInterface.getNumAvailableDevices()
PInt.__init__(self, name, default, 0, maximum)
def __init__(self, name):
default = NEFGPUInterface.getRequestedNumDevices()
maximum = NEFGPUInterface.getNumAvailableDevices()
PInt.__init__(self, name, default, 0, maximum)
def __init__(self, name):
default = NEFGPUInterface.getNumDevices()
maximum = NEFGPUInterface.getNumDetectedDevices()
PInt.__init__(self, name, default, 0, maximum)
def kill(self):
if self.thread_pool is not None:
NEFGPUInterface.requireAllOutputsOnCPU(False);
self.thread_pool.kill()
self.thread_pool = None
def __init__(self, name):
default = NEFGPUInterface.getNumDevices()
maximum = NEFGPUInterface.getNumDetectedDevices()
PInt.__init__(self, name, default, 0, maximum)
