Changeset 1103

Timestamp:

03/22/12 00:07:45 (14 months ago)

Author:

pierre

Message:

Use the PoissonSource? with spikes generated by the GPU, should be more efficient. Trying to make Nemo backend as fast as possible for further benchmarks

Location:

trunk/src/nemo

Files:

• __init__.py (modified) (3 diffs)
• simulator.py (modified) (2 diffs)

trunk/src/nemo/__init__.py

@@ -125 +125 @@
             cell.parent = self
         if isinstance(celltype, SpikeSourcePoisson):    
-            simulator.spikes_array_list += self.all_cells.tolist()
-            params['precision'] = simulator.state.dt
-            ntype = simulator.state.net.add_neuron_type('Input')
-            for idx in self.all_cells:
-                player = SpikeSourcePoisson.spike_player(**params)
-                setattr(idx, 'player', player)                
-            simulator.state.net.add_neuron(ntype, list(self.all_cells))
+            ntype = simulator.state.net.add_neuron_type('PoissonSource')
+            simulator.state.net.add_neuron(ntype, list(self.all_cells), [params['rate']]*n)
         elif isinstance(celltype, SpikeSourceArray):
-            ### For the moment, we model spike_source_array and spike_source_poisson
-            ### as hyperpolarized neurons that are forced to fire, but this could be
-            ### enhanced. A local copy of these devices is kept on the CPU, to send the
+            ### For the moment, we model spike_source_array as neurons that are forced to fire, 
+            ### but this could be enhanced. A local copy of these devices is kept on the CPU, to send the
             ### spikes
             simulator.spikes_array_list += self.all_cells.tolist()
             params['precision'] = simulator.state.dt
-            ntype = simulator.state.net.add_neuron_type('Input')
+            ntype = simulator.state.net.add_neuron_type('Input')
             for idx in self.all_cells:
                 player = SpikeSourceArray.spike_player(**params)
@@ -146 +140 @@
         elif isinstance(celltype, cells.IF_curr_exp):
             init = celltype.default_initial_values
-            ntype = simulator.state.net.add_neuron_type('IF_curr_exp')   
+            ntype = simulator.state.net.add_neuron_type('IF_curr_exp')   
             simulator.state.net.add_neuron(ntype, list(self.all_cells),
                         [params['v_rest']]*n,
@@ -158 +152 @@
                         [params['i_offset']]*n,                        
                         [init['v']]*n, [0.]*n, [0.]*n, [1000.]*n)
-        else:            
+        elif isinstance(celltype, cells.Izikevich):            
             init  = celltype.default_initial_values
             ntype = simulator.state.net.add_neuron_type('Izhikevich')

trunk/src/nemo/simulator.py

@@ -144 +144 @@
         if isinstance(self.celltype, SpikeSourceArray):
             return {'spike_times' : self.player.spike_times}
-        elif isinstance(self.celltype, SpikeSourcePoisson):
-            return {'rate' : self.player.rate, 'duration' : self.player.duration, 
-                    'start' : self.player.start}
         else:
             params = {}
@@ -160 +157 @@
             parameters['precision'] = state.dt
             self.player.reset(**parameters)
-        elif isinstance(self.celltype, SpikeSourcePoisson):
-            parameters['precision'] = state.dt
-            self.player.reset(**parameters)    
         else:
             indices = self.celltype.indices