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ldlt_matrix_inverse.py 3.79 KiB
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  • """
    =========================================
    LDLT Matrix Inversion Algorithm
    =========================================
    
    """
    
    from b_asic.architecture import Architecture, Memory, ProcessingElement
    
    from b_asic.core_operations import MADS, DontCare, Reciprocal
    
    from b_asic.core_schedulers import (
        ALAPScheduler,
        ASAPScheduler,
        EarliestDeadlineScheduler,
        HybridScheduler,
        LeastSlackTimeScheduler,
        MaxFanOutScheduler,
    )
    from b_asic.schedule import Schedule
    from b_asic.sfg_generators import ldlt_matrix_inverse
    
    from b_asic.special_operations import Input, Output
    
    sfg = ldlt_matrix_inverse(N=3)
    
    sfg.set_latency_of_type(DontCare.type_name(), 0)  # REMOVE!!!
    
    sfg.set_latency_of_type(MADS.type_name(), 3)
    sfg.set_latency_of_type(Reciprocal.type_name(), 2)
    
    sfg.set_execution_time_of_type(DontCare.type_name(), 0)  # REMOVE!!!
    
    sfg.set_execution_time_of_type(MADS.type_name(), 1)
    sfg.set_execution_time_of_type(Reciprocal.type_name(), 1)
    
    # %%
    # Create an ASAP schedule.
    schedule = Schedule(sfg, scheduler=ASAPScheduler())
    print("Scheduling time:", schedule.schedule_time)
    
    
    # %%
    # Create an ALAP schedule.
    schedule = Schedule(sfg, scheduler=ALAPScheduler())
    print("Scheduling time:", schedule.schedule_time)
    
    
    # %%
    # Create an EarliestDeadline schedule that satisfies the resource constraints.
    resources = {MADS.type_name(): 1, Reciprocal.type_name(): 1}
    schedule = Schedule(sfg, scheduler=EarliestDeadlineScheduler(resources))
    print("Scheduling time:", schedule.schedule_time)
    
    
    # %%
    # Create a LeastSlackTime schedule that satisfies the resource constraints.
    schedule = Schedule(sfg, scheduler=LeastSlackTimeScheduler(resources))
    print("Scheduling time:", schedule.schedule_time)
    
    
    # %%
    # Create a MaxFanOutScheduler schedule that satisfies the resource constraints.
    schedule = Schedule(sfg, scheduler=MaxFanOutScheduler(resources))
    print("Scheduling time:", schedule.schedule_time)
    
    
    # %%
    # Create a HybridScheduler schedule that satisfies the resource constraints.
    schedule = Schedule(sfg, scheduler=HybridScheduler(resources))
    print("Scheduling time:", schedule.schedule_time)
    
    mads = operations.get_by_type_name(MADS.type_name())
    
    reciprocals = operations.get_by_type_name(Reciprocal.type_name())
    
    dont_cares = operations.get_by_type_name(DontCare.type_name())
    dont_cares.show(title="Dont-care executions")
    inputs = operations.get_by_type_name(Input.type_name())
    
    outputs = operations.get_by_type_name(Output.type_name())
    
    outputs.show(title="Output executions")
    
    mads_pe = ProcessingElement(mads, entity_name="mad")
    reciprocal_pe = ProcessingElement(reciprocals, entity_name="rec")
    
    
    dont_care_pe = ProcessingElement(dont_cares, entity_name="dc")
    
    
    pe_in = ProcessingElement(inputs, entity_name='input')
    pe_out = ProcessingElement(outputs, entity_name='output')
    
    mem_vars = schedule.get_memory_variables()
    mem_vars.show(title="All memory variables")
    direct, mem_vars = mem_vars.split_on_length()
    mem_vars.show(title="Non-zero time memory variables")
    mem_vars_set = mem_vars.split_on_ports(read_ports=1, write_ports=1, total_ports=2)
    
    # %%
    memories = []
    for i, mem in enumerate(mem_vars_set):
        memory = Memory(mem, memory_type="RAM", entity_name=f"memory{i}")
        memories.append(memory)
        mem.show(title=f"{memory.entity_name}")
        memory.assign("left_edge")
        memory.show_content(title=f"Assigned {memory.entity_name}")
    
    direct.show(title="Direct interconnects")
    
    # %%
    arch = Architecture(
    
        {mads_pe, reciprocal_pe, dont_care_pe, pe_in, pe_out},