`b_asic.schedule`¶

B-ASIC Schedule Module.

Contains the schedule class for scheduling operations in an SFG.

class b_asic.schedule.Schedule(sfg: SFG, scheduler: Scheduler | None = None, schedule_time: int | None = None, cyclic: bool = False, start_times: dict[GraphID, int] | None = None, laps: dict[GraphID, int] | None = None)¶

Bases: object

Schedule of an SFG with scheduled Operations.

Parameters:

sfgSFG: The signal flow graph to schedule.
schedulerScheduler, default: None: The automatic scheduler to be used.
schedule_timeint, optional: The schedule time. If not provided, it will be determined by the scheduling algorithm.
cyclicbool, default: False: If the schedule is cyclic.
start_timesdict, optional: Dictionary with GraphIDs as keys and start times as values. Used when algorithm is ‘provided’.
lapsdict, optional: Dictionary with GraphIDs as keys and laps as values. Used when algorithm is ‘provided’.

backward_slack(graph_id: GraphID) → int¶

Return how much an operation can be moved backward in time.

Parameters:

graph_idGraphID: The graph id of the operation.

Returns:

int: The number of time steps the operation with graph_id can be moved backward in time.

Note

The backward slack is positive, but a call to move_operation() should be negative to move the operation backward.

See also

forward_slack
slacks

property cyclic: bool¶: If the current schedule is cyclic.

decrease_time_resolution(factor: int) → Schedule¶

Decrease time resolution for a schedule.

Parameters:

factorint: The time resolution decrement.

See also

get_possible_time_resolution_decrements

edit(inplace=False) → Schedule¶

Edit schedule in GUI and return new schedule.

Parameters:

inplacebool, default: False: If True, replace the current schedule.

forward_slack(graph_id: GraphID) → int¶

Return how much an operation can be moved forward in time.

Parameters:

graph_idGraphID: The graph id of the operation.

Returns:

int: The number of time steps the operation with graph_id can be moved forward in time.

See also

backward_slack
slacks

get_max_end_time() → int¶: Return the current maximum end time among all operations.

get_max_non_io_end_time() → int¶: Return the current maximum end time among all non-IO operations.

get_memory_variables() → ProcessCollection¶

Return a ProcessCollection containing all memory variables.

Returns:

ProcessCollection

get_operations() → ProcessCollection¶

Return a ProcessCollection containing all operations.

Returns:

ProcessCollection

get_possible_time_resolution_decrements() → list[int]¶: Return a list with possible factors to reduce time resolution.

get_used_type_names() → list[TypeName]¶: Get a list of all TypeNames used in the Schedule.

get_y_location(graph_id: GraphID) → int¶

Get the y-location of the Operation with GraphID graph_id.

Parameters:

graph_idGraphID: The GraphID of the operation.

Returns:

int: The y-location of the operation.

increase_time_resolution(factor: int) → Schedule¶

Increase time resolution for a schedule.

Parameters:

factorint: The time resolution increment.

property laps: dict[GraphID, int]¶: The number of laps for the start times of the operations in the schedule.

move_operation(graph_id: GraphID, time: int) → Schedule¶

Move an operation in the schedule.

Parameters:

graph_idGraphID: The graph id of the operation to move.
timeint: The time to move. If positive move forward, if negative move backward.

move_operation_alap(graph_id: GraphID) → Schedule¶

Move an operation as late as possible in the schedule.

This is basically the same as:

schedule.move_operation(graph_id, schedule.forward_slack(graph_id))

but operations with no succeeding operation (Outputs) will only move to the end of the schedule.

Parameters:

graph_idGraphID: The graph id of the operation to move.

move_operation_asap(graph_id: GraphID) → Schedule¶

Move an operation as soon as possible in the schedule.

This is basically the same as:

schedule.move_operation(graph_id, -schedule.backward_slack(graph_id))

but operations that do not have a preceding operation (Inputs and Constants) will only move to the start of the schedule.

Parameters:

graph_idGraphID: The graph id of the operation to move.

move_y_location(graph_id: GraphID, new_y: int, insert: bool = False) → None¶

Move operation in y-direction and remove any empty rows.

Parameters:

graph_idGraphID: The GraphID of the operation to move.
new_yint: The new y-location of the operation.
insertbool, optional: If True, all operations on that y-location will be moved one position. The default is False.

place_operation(op: Operation, time: int, op_laps: dict[GraphID, int]) → None¶

Schedule op at time.

Parameters:

opOperation: Operation to schedule.
timeint: Time slot to schedule the operation in. If time > schedule_time -> schedule cyclically.
op_lapsdict[GraphID, int]: Laps of all scheduled operations.

plot(ax: Axes, operation_gap: float = 0.5) → None¶

Plot the schedule in a matplotlib.axes.Axes or subclass.

Parameters:

axAxes: The matplotlib.axes.Axes to plot in.
operation_gapfloat, optional: The vertical distance between operations in the schedule. The height of the operation is always 1.

print_slacks(order: int = 0, type_name: TypeName | None = None) → None¶

Print the slack times for all operations in the schedule.

Parameters:

orderint, default: 0

Sorting order.

0: alphabetical on Graph ID
1: backward slack
2: forward slack

type_nameTypeName, optional

If given, only the slack times for operations of this type will be printed.

remove_delays() → None¶: Remove delay elements and update laps. Used after scheduling algorithm.

reset_y_locations() → None¶: Reset all the y-locations in the schedule to None.

property schedule_time: int¶: The schedule time of the current schedule.

set_execution_time_of_type_name(type_name: TypeName, execution_time: int) → None¶

Set the execution time of all operations with the given type name.

Parameters:

type_nameTypeName: The type name of the operation. For example, obtained as Addition.type_name().
execution_timeint: The execution time of the operation.

set_latency_of_type_name(type_name: TypeName | GraphID, latency: int) → None¶

Set the latency of all operations with the given type name.

Parameters:

type_nameTypeName or GraphID: The type name of the operation, e.g., obtained as Addition.type_name() or a specific GraphID of an operation.
latencyint: The latency of the operation.

set_schedule_time(time: int) → Schedule¶

Set a new schedule time.

Parameters:

timeint: The new schedule time. If it is too short, a ValueError will be raised.

See also

get_max_time

set_y_location(graph_id: GraphID, y_location: int) → None¶

Set the y-location of the Operation with GraphID graph_id to y_location.

Parameters:

graph_idGraphID: The GraphID of the operation to move.
y_locationint: The new y-location of the operation.

property sfg: SFG¶: The SFG corresponding to the current schedule.

show(operation_gap: float = 0.5, title: str | None = None) → None¶

Show the schedule. Will display based on the current Matplotlib backend.

Parameters:

operation_gapfloat, optional: The vertical distance between operations in the schedule. The height of the operation is always 1.
titlestr, optional: Figure title.

slacks(graph_id: GraphID) → tuple[int, int]¶

Return the backward and forward slacks of operation graph_id.

That is, how much the operation can be moved backward and forward in time.

Parameters:

graph_idGraphID: The graph id of the operation.

Returns:

tuple(int, int): The backward and forward slacks, respectively.

Note

The backward slack is positive, but a call to move_operation() should be negative to move the operation backward.

See also

backward_slack
forward_slack

sort_y_locations_on_start_times() → None¶

Sort the y-locations of the schedule based on start times of the operations.

Inputs, outputs, dontcares, and sinks are located adjacent to the operations that they are connected to.

See also

move_y_location
set_y_location

start_time_of_operation(graph_id: GraphID) → int¶

Return the start time of the operation with the specified by graph_id.

Parameters:

graph_idGraphID: The graph id of the operation to get the start time for.

property start_times: dict[GraphID, int]¶: The start times of the operations in the schedule.

swap_io_of_operation(operation_id: GraphID) → None¶

Swap the inputs (and outputs) of operation.

Parameters:

operation_idGraphID: The GraphID of the operation to swap.

b_asic.schedule¶

`b_asic.schedule`¶