def _census_memory_requirement(self): """ Guesstimate the memory required for this simulator. Guesstimate is based on a census of the dominant arrays after the simulator has been configured. NOTE: Assumes returned/yeilded data is in some sense "taken care of" in the world outside the simulator, and so doesn't consider it, making the simulator's history, and surface if present, the dominant memory pigs... """ magic_number = 2.42 # Current guesstimate is low by about a factor of 2, seems safer to over estimate... #magic_number = 8.0 # Bytes memreq = self.history.nbytes #LOG.info("Memory required by this simulatin will be approximately %s Bytes" % (memreq)) try: memreq += self.surface.triangles.nbytes * 2 # normals memreq += self.surface.vertices.nbytes * 2 # normals memreq += self.surface.vertex_mapping.nbytes * 4 #vertex_mapping, region_average, region_sum memreq += self.surface.eeg_projection.nbytes memreq += self.surface.local_connectivity.matrix.nnz * 8 except AttributeError: pass for monitor in self.monitors: memreq += monitor._stock.nbytes if isinstance(monitor, monitors_module.Bold): memreq += monitor._interim_stock.nbytes if psutil and memreq > psutil.virtual_memory().total: LOG.error("This is gonna get ugly...") self._memory_requirement_census = magic_number * memreq #import pdb; pdb.set_trace() msg = "Memory requirement census: simulation will need about %.1f MB" LOG.info(msg % (self._memory_requirement_census / 1048576.0))
def _guesstimate_memory_requirement(self): """ Guestimate the memroy required for this simulator. Guesstimate is based on the shape of the dominant arrays, and as such can operate before configuration. NOTE: Assumes returned/yeilded data is in some sense "taken care of" in the world outside the simulator, and so doesn't consider it, making the simulator's history, and surface if present, the dominant memory pigs... """ if self.surface: number_of_nodes = self.surface.number_of_vertices else: number_of_nodes = self.connectivity.number_of_regions number_of_regions = self.connectivity.number_of_regions magic_number = 2.42 # Current guesstimate is low by about a factor of 2, seems safer to over estimate... bits_64 = 8.0 # Bytes bits_32 = 4.0 # Bytes #NOTE: The speed hack for getting the first element of hist shape should # partially resolves calling of this method with a non-configured # connectivity, there remains the less common issue if no tract_lengths... hist_shape = (self.connectivity.tract_lengths.max() / (self.conduction_speed or self.connectivity.speed or 3.0) / self.integrator.dt, #self.connectivity.delays.max() self.model.nvar, number_of_nodes, self.model.number_of_modes) memreq = numpy.prod(hist_shape) * bits_64 if self.surface: memreq += self.surface.number_of_triangles * 3 * bits_32 * 2 # normals memreq += self.surface.number_of_vertices * 3 * bits_64 * 2 # normals memreq += number_of_nodes * number_of_regions * bits_64 * 4 #vertex_mapping, region_average, region_sum #???memreq += self.surface.local_connectivity.matrix.nnz * 8 if not isinstance(self.monitors, (list, tuple)): monitors = [self.monitors] else: monitors = self.monitors for monitor in monitors: if not isinstance(monitor, monitors_module.Bold): stock_shape = (monitor.period / self.integrator.dt, self.model.variables_of_interest.shape[0], number_of_nodes, self.model.number_of_modes) memreq += numpy.prod(stock_shape) * bits_64 if hasattr(monitor, "sensors"): try: memreq += number_of_nodes * monitor.sensors.number_of_sensors * bits_64 #projection_matrix except AttributeError: LOG.debug("No sensors specified, guessing memory based on default EEG.") memreq += number_of_nodes * 62.0 * bits_64 else: stock_shape = (monitor.hrf_length * monitor._stock_sample_rate, self.model.variables_of_interest.shape[0], number_of_nodes, self.model.number_of_modes) interim_stock_shape = (1.0 / (2.0**-2 * self.integrator.dt), self.model.variables_of_interest.shape[0], number_of_nodes, self.model.number_of_modes) memreq += numpy.prod(stock_shape) * bits_64 memreq += numpy.prod(interim_stock_shape) * bits_64 #available_memory = 25769803776 #TODO: (this is for my machine) if psutil and memreq > psutil.virtual_memory().total: LOG.error("This is gonna get ugly...") self._memory_requirement_guess = magic_number * memreq #import pdb; pdb.set_trace() msg = "Memory requirement guesstimate: simulation will need about %.1f MB" LOG.info(msg % (self._memory_requirement_guess / 1048576.0))
def _guesstimate_memory_requirement(self): """ guesstimate the memory required for this simulator. Guesstimate is based on the shape of the dominant arrays, and as such can operate before configuration. NOTE: Assumes returned/yeilded data is in some sense "taken care of" in the world outside the simulator, and so doesn't consider it, making the simulator's history, and surface if present, the dominant memory pigs... """ if self.surface: number_of_nodes = self.surface.number_of_vertices else: number_of_nodes = self.connectivity.number_of_regions number_of_regions = self.connectivity.number_of_regions magic_number = 2.42 # Current guesstimate is low by about a factor of 2, seems safer to over estimate... bits_64 = 8.0 # Bytes bits_32 = 4.0 # Bytes #NOTE: The speed hack for getting the first element of hist shape should # partially resolves calling of this method with a non-configured # connectivity, there remains the less common issue if no tract_lengths... hist_shape = ( self.connectivity.tract_lengths.max() / (self.conduction_speed or self.connectivity.speed or 3.0) / self.integrator.dt, self.model.nvar, number_of_nodes, self.model.number_of_modes) memreq = numpy.prod(hist_shape) * bits_64 if self.surface: memreq += self.surface.number_of_triangles * 3 * bits_32 * 2 # normals memreq += self.surface.number_of_vertices * 3 * bits_64 * 2 # normals memreq += number_of_nodes * number_of_regions * bits_64 * 4 # vertex_mapping, region_average, region_sum #???memreq += self.surface.local_connectivity.matrix.nnz * 8 if not isinstance(self.monitors, (list, tuple)): monitors = [self.monitors] else: monitors = self.monitors for monitor in monitors: if not isinstance(monitor, monitors_module.Bold): stock_shape = (monitor.period / self.integrator.dt, self.model.variables_of_interest.shape[0], number_of_nodes, self.model.number_of_modes) memreq += numpy.prod(stock_shape) * bits_64 if hasattr(monitor, "sensors"): try: memreq += number_of_nodes * monitor.sensors.number_of_sensors * bits_64 # projection_matrix except AttributeError: LOG.debug( "No sensors specified, guessing memory based on default EEG." ) memreq += number_of_nodes * 62.0 * bits_64 else: stock_shape = (monitor.hrf_length * monitor._stock_sample_rate, self.model.variables_of_interest.shape[0], number_of_nodes, self.model.number_of_modes) interim_stock_shape = ( 1.0 / (2.0**-2 * self.integrator.dt), self.model.variables_of_interest.shape[0], number_of_nodes, self.model.number_of_modes) memreq += numpy.prod(stock_shape) * bits_64 memreq += numpy.prod(interim_stock_shape) * bits_64 if psutil and memreq > psutil.virtual_memory().total: LOG.error("This is gonna get ugly...") self._memory_requirement_guess = magic_number * memreq msg = "Memory requirement guesstimate: simulation will need about %.1f MB" LOG.info(msg % (self._memory_requirement_guess / 1048576.0))