From 3189fe94e27b33b7016cfdd31237a949921605ea Mon Sep 17 00:00:00 2001
From: Simon Bjurek <simbj106@student.liu.se>
Date: Wed, 26 Feb 2025 17:31:29 +0100
Subject: [PATCH] greatly improved speed of ListScheduler and added more tests
---
.gitlab-ci.yml | 2 +-
b_asic/core_operations.py | 6 +-
b_asic/schedule.py | 15 ++
b_asic/scheduler.py | 122 +++++----
b_asic/special_operations.py | 4 +-
test/unit/test_list_schedulers.py | 405 ++++++++++++++++++++++++++++++
6 files changed, 483 insertions(+), 71 deletions(-)
diff --git a/.gitlab-ci.yml b/.gitlab-ci.yml
index 7accae47..4a822db9 100644
--- a/.gitlab-ci.yml
+++ b/.gitlab-ci.yml
@@ -4,7 +4,7 @@ stages:
before_script:
- apt-get update --yes
- # - apt-get install --yes build-essential cmake graphviz xvfb xdg-utils lcov
+ # - apt-get install --yes build-essential cmake graphviz python3-pyqt5 xvfb xdg-utils lcov
- apt-get install --yes graphviz python3-pyqt5 xvfb xdg-utils
- apt-get install -y libxcb-cursor-dev
- python -m pip install --upgrade pip
diff --git a/b_asic/core_operations.py b/b_asic/core_operations.py
index 55421296..d09e0c62 100644
--- a/b_asic/core_operations.py
+++ b/b_asic/core_operations.py
@@ -69,7 +69,7 @@ class Constant(AbstractOperation):
@property
def latency(self) -> int:
- return self.latency_offsets["out0"]
+ return 0
def __repr__(self) -> str:
return f"Constant({self.value})"
@@ -1689,7 +1689,7 @@ class DontCare(AbstractOperation):
@property
def latency(self) -> int:
- return self.latency_offsets["out0"]
+ return 0
def __repr__(self) -> str:
return "DontCare()"
@@ -1766,7 +1766,7 @@ class Sink(AbstractOperation):
@property
def latency(self) -> int:
- return self.latency_offsets["in0"]
+ return 0
def __repr__(self) -> str:
return "Sink()"
diff --git a/b_asic/schedule.py b/b_asic/schedule.py
index 543e10af..c815fdb2 100644
--- a/b_asic/schedule.py
+++ b/b_asic/schedule.py
@@ -212,6 +212,21 @@ class Schedule:
)
return max_end_time
+ def get_max_non_io_end_time(self) -> int:
+ """Return the current maximum end time among all non-IO operations."""
+ max_end_time = 0
+ for graph_id, op_start_time in self._start_times.items():
+ operation = cast(Operation, self._sfg.find_by_id(graph_id))
+ if graph_id.startswith("out"):
+ continue
+ else:
+ for outport in operation.outputs:
+ max_end_time = max(
+ max_end_time,
+ op_start_time + cast(int, outport.latency_offset),
+ )
+ return max_end_time
+
def forward_slack(self, graph_id: GraphID) -> int:
"""
Return how much an operation can be moved forward in time.
diff --git a/b_asic/scheduler.py b/b_asic/scheduler.py
index 87708e75..6ae328f1 100644
--- a/b_asic/scheduler.py
+++ b/b_asic/scheduler.py
@@ -226,7 +226,7 @@ class ListScheduler(Scheduler, ABC):
if resource_amount < resource_lower_bound:
raise ValueError(
f"Amount of resource: {resource_type} is not enough to "
- f"realize schedule for scheduling time: {self._schedule.schedule_time}"
+ f"realize schedule for scheduling time: {self._schedule.schedule_time}."
)
alap_schedule = copy.copy(self._schedule)
@@ -245,8 +245,20 @@ class ListScheduler(Scheduler, ABC):
self._remaining_resources = self._max_resources.copy()
- remaining_ops = self._sfg.operations
- remaining_ops = [op.graph_id for op in remaining_ops]
+ self._remaining_ops = self._sfg.operations
+ self._remaining_ops = [op.graph_id for op in self._remaining_ops]
+
+ self._cached_latencies = {
+ op_id: self._sfg.find_by_id(op_id).latency for op_id in self._remaining_ops
+ }
+ self._cached_execution_times = {
+ op_id: self._sfg.find_by_id(op_id).execution_time
+ for op_id in self._remaining_ops
+ }
+
+ self._deadlines = self._calculate_deadlines(alap_start_times)
+ self._output_slacks = self._calculate_alap_output_slacks(alap_start_times)
+ self._fan_outs = self._calculate_fan_outs(alap_start_times)
self._schedule.start_times = {}
self.remaining_reads = self._max_concurrent_reads
@@ -260,23 +272,24 @@ class ListScheduler(Scheduler, ABC):
for input_id in self._input_times:
self._schedule.start_times[input_id] = self._input_times[input_id]
self._op_laps[input_id] = 0
- remaining_ops = [
- elem for elem in remaining_ops if not elem.startswith("in")
+ self._remaining_ops = [
+ elem for elem in self._remaining_ops if not elem.startswith("in")
]
- remaining_ops = [op for op in remaining_ops if not op.startswith("dontcare")]
- remaining_ops = [op for op in remaining_ops if not op.startswith("t")]
- remaining_ops = [
+ self._remaining_ops = [
+ op for op in self._remaining_ops if not op.startswith("dontcare")
+ ]
+ self._remaining_ops = [
+ op for op in self._remaining_ops if not op.startswith("t")
+ ]
+ self._remaining_ops = [
op
- for op in remaining_ops
+ for op in self._remaining_ops
if not (op.startswith("out") and op in self._output_delta_times)
]
- while remaining_ops:
- ready_ops_priority_table = self._get_ready_ops_priority_table(
- alap_start_times,
- remaining_ops,
- )
+ while self._remaining_ops:
+ ready_ops_priority_table = self._get_ready_ops_priority_table()
while ready_ops_priority_table:
next_op = self._sfg.find_by_id(
self._get_next_op_id(ready_ops_priority_table)
@@ -284,8 +297,8 @@ class ListScheduler(Scheduler, ABC):
self.remaining_reads -= next_op.input_count
- remaining_ops = [
- op_id for op_id in remaining_ops if op_id != next_op.graph_id
+ self._remaining_ops = [
+ op_id for op_id in self._remaining_ops if op_id != next_op.graph_id
]
self._time_out_counter = 0
@@ -295,25 +308,10 @@ class ListScheduler(Scheduler, ABC):
if self._schedule.schedule_time
else 0
)
- if not self._schedule.cyclic and self._schedule.schedule_time:
- if self._current_time > self._schedule.schedule_time:
- raise ValueError(
- f"Provided scheduling time {schedule.schedule_time} cannot be reached, "
- "try to enable the cyclic property or increase the time."
- )
- ready_ops_priority_table = self._get_ready_ops_priority_table(
- alap_start_times,
- remaining_ops,
- )
+ ready_ops_priority_table = self._get_ready_ops_priority_table()
self._go_to_next_time_step()
-
- ready_ops_priority_table = self._get_ready_ops_priority_table(
- alap_start_times,
- remaining_ops,
- )
-
self.remaining_reads = self._max_concurrent_reads
self._current_time -= 1
@@ -354,43 +352,35 @@ class ListScheduler(Scheduler, ABC):
sorted_table = sorted(ready_ops_priority_table, key=sort_key)
return sorted_table[0][0]
- def _get_ready_ops_priority_table(
- self,
- alap_start_times: dict["GraphID", int],
- remaining_ops: list["GraphID"],
- ) -> list[tuple["GraphID", int, int, int]]:
+ def _get_ready_ops_priority_table(self) -> list[tuple["GraphID", int, int, int]]:
ready_ops = [
op_id
- for op_id in remaining_ops
- if self._op_is_schedulable(self._sfg.find_by_id(op_id), remaining_ops)
+ for op_id in self._remaining_ops
+ if self._op_is_schedulable(self._sfg.find_by_id(op_id))
]
- deadlines = self._calculate_deadlines(alap_start_times)
- output_slacks = self._calculate_alap_output_slacks(alap_start_times)
- fan_outs = self._calculate_fan_outs(alap_start_times)
-
- ready_ops_priority_table = []
- for op_id in ready_ops:
- ready_ops_priority_table.append(
- (op_id, deadlines[op_id], output_slacks[op_id], fan_outs[op_id])
+ return [
+ (
+ op_id,
+ self._deadlines[op_id],
+ self._output_slacks[op_id],
+ self._fan_outs[op_id],
)
- return ready_ops_priority_table
+ for op_id in ready_ops
+ ]
def _calculate_deadlines(
self, alap_start_times: dict["GraphID", int]
) -> dict["GraphID", int]:
return {
- op_id: start_time + self._sfg.find_by_id(op_id).latency
+ op_id: start_time + self._cached_latencies[op_id]
for op_id, start_time in alap_start_times.items()
}
def _calculate_alap_output_slacks(
self, alap_start_times: dict["GraphID", int]
) -> dict["GraphID", int]:
- return {
- op_id: start_time - self._current_time
- for op_id, start_time in alap_start_times.items()
- }
+ return {op_id: start_time for op_id, start_time in alap_start_times.items()}
def _calculate_fan_outs(
self, alap_start_times: dict["GraphID", int]
@@ -412,26 +402,22 @@ class ListScheduler(Scheduler, ABC):
start_time = start_time % self._schedule.schedule_time
if time_slot >= start_time:
- if time_slot < start_time + max(
- self._sfg.find_by_id(op_id).execution_time, 1
- ):
+ if time_slot < start_time + max(self._cached_execution_times[op_id], 1):
if op_id.startswith(op.type_name()):
if op.graph_id != op_id:
count += 1
return count < self._remaining_resources[op.type_name()]
- def _op_is_schedulable(
- self, op: "Operation", remaining_ops: list["GraphID"]
- ) -> bool:
+ def _op_is_schedulable(self, op: "Operation") -> bool:
if not self._op_satisfies_resource_constraints(op):
return False
- op_finish_time = self._current_time + op.latency
+ op_finish_time = self._current_time + self._cached_latencies[op.graph_id]
future_ops = [
self._sfg.find_by_id(item[0])
for item in self._schedule.start_times.items()
- if item[1] + self._sfg.find_by_id(item[0]).latency == op_finish_time
+ if item[1] + self._cached_latencies[item[0]] == op_finish_time
]
future_ops_writes = sum([op.input_count for op in future_ops])
@@ -451,7 +437,7 @@ class ListScheduler(Scheduler, ABC):
source_op_graph_id = source_op.graph_id
- if source_op_graph_id in remaining_ops:
+ if source_op_graph_id in self._remaining_ops:
return False
if self._schedule.start_times[source_op_graph_id] != self._current_time - 1:
@@ -466,12 +452,18 @@ class ListScheduler(Scheduler, ABC):
self._schedule.start_times.get(source_op_graph_id)
+ self._op_laps[source_op.graph_id] * self._schedule.schedule_time
)
- proceeding_op_finish_time = proceeding_op_start_time + source_op.latency
+ proceeding_op_finish_time = (
+ proceeding_op_start_time
+ + self._cached_latencies[source_op.graph_id]
+ )
else:
proceeding_op_start_time = self._schedule.start_times.get(
source_op_graph_id
)
- proceeding_op_finish_time = proceeding_op_start_time + source_op.latency
+ proceeding_op_finish_time = (
+ proceeding_op_start_time
+ + self._cached_latencies[source_op.graph_id]
+ )
earliest_start_time = max(earliest_start_time, proceeding_op_finish_time)
return earliest_start_time <= self._current_time
@@ -502,7 +494,7 @@ class ListScheduler(Scheduler, ABC):
self._remaining_resources[Output.type_name()] -= count
self._current_time = new_time
- if not self._op_is_schedulable(output, {}):
+ if not self._op_is_schedulable(output):
raise ValueError(
"Cannot schedule outputs according to the provided output_delta_times. "
f"Failed output: {output.graph_id}, "
diff --git a/b_asic/special_operations.py b/b_asic/special_operations.py
index a67b55db..f6d0e84c 100644
--- a/b_asic/special_operations.py
+++ b/b_asic/special_operations.py
@@ -53,7 +53,7 @@ class Input(AbstractOperation):
@property
def latency(self) -> int:
- return self.latency_offsets["out0"]
+ return 0
@property
def value(self) -> Num:
@@ -157,7 +157,7 @@ class Output(AbstractOperation):
@property
def latency(self) -> int:
- return self.latency_offsets["in0"]
+ return 0
class Delay(AbstractOperation):
diff --git a/test/unit/test_list_schedulers.py b/test/unit/test_list_schedulers.py
index 098e20bd..252baa3d 100644
--- a/test/unit/test_list_schedulers.py
+++ b/test/unit/test_list_schedulers.py
@@ -906,3 +906,408 @@ class TestHybridScheduler:
max_concurrent_reads=2,
),
)
+
+ def test_32_point_fft_custom_io_times(self):
+ POINTS = 32
+ sfg = radix_2_dif_fft(POINTS)
+
+ sfg.set_latency_of_type(Butterfly.type_name(), 1)
+ sfg.set_latency_of_type(ConstantMultiplication.type_name(), 3)
+ sfg.set_execution_time_of_type(Butterfly.type_name(), 1)
+ sfg.set_execution_time_of_type(ConstantMultiplication.type_name(), 1)
+
+ resources = {Butterfly.type_name(): 1, ConstantMultiplication.type_name(): 1}
+ input_times = {f"in{i}": i for i in range(POINTS)}
+ output_delta_times = {f"out{i}": i for i in range(POINTS)}
+ schedule = Schedule(
+ sfg,
+ scheduler=HybridScheduler(
+ resources,
+ input_times=input_times,
+ output_delta_times=output_delta_times,
+ ),
+ )
+
+ for i in range(POINTS):
+ assert schedule.start_times[f"in{i}"] == i
+ assert (
+ schedule.start_times[f"out{i}"]
+ == schedule.get_max_non_io_end_time() + i
+ )
+
+ # Too slow for pipeline right now
+ # def test_64_point_fft_custom_io_times(self):
+ # POINTS = 64
+ # sfg = radix_2_dif_fft(POINTS)
+
+ # sfg.set_latency_of_type(Butterfly.type_name(), 1)
+ # sfg.set_latency_of_type(ConstantMultiplication.type_name(), 3)
+ # sfg.set_execution_time_of_type(Butterfly.type_name(), 1)
+ # sfg.set_execution_time_of_type(ConstantMultiplication.type_name(), 1)
+
+ # resources = {Butterfly.type_name(): 1, ConstantMultiplication.type_name(): 1}
+ # input_times = {f"in{i}": i for i in range(POINTS)}
+ # output_delta_times = {f"out{i}": i for i in range(POINTS)}
+ # schedule = Schedule(
+ # sfg,
+ # scheduler=HybridScheduler(
+ # resources,
+ # input_times=input_times,
+ # output_delta_times=output_delta_times,
+ # ),
+ # )
+
+ # for i in range(POINTS):
+ # assert schedule.start_times[f"in{i}"] == i
+ # assert (
+ # schedule.start_times[f"out{i}"]
+ # == schedule.get_max_non_io_end_time() + i
+ # )
+
+ def test_32_point_fft_custom_io_times_cyclic(self):
+ POINTS = 32
+ sfg = radix_2_dif_fft(POINTS)
+
+ sfg.set_latency_of_type(Butterfly.type_name(), 1)
+ sfg.set_latency_of_type(ConstantMultiplication.type_name(), 3)
+ sfg.set_execution_time_of_type(Butterfly.type_name(), 1)
+ sfg.set_execution_time_of_type(ConstantMultiplication.type_name(), 1)
+
+ resources = {Butterfly.type_name(): 1, ConstantMultiplication.type_name(): 1}
+ input_times = {f"in{i}": i for i in range(POINTS)}
+ output_delta_times = {f"out{i}": i for i in range(POINTS)}
+ schedule = Schedule(
+ sfg,
+ scheduler=HybridScheduler(
+ resources,
+ input_times=input_times,
+ output_delta_times=output_delta_times,
+ ),
+ schedule_time=96,
+ cyclic=True,
+ )
+
+ for i in range(POINTS):
+ assert schedule.start_times[f"in{i}"] == i
+ assert schedule.start_times[f"out{i}"] == 96 if i == 0 else i
+
+ def test_cyclic_scheduling(self):
+ sfg = radix_2_dif_fft(points=4)
+
+ sfg.set_latency_of_type(Butterfly.type_name(), 1)
+ sfg.set_latency_of_type(ConstantMultiplication.type_name(), 3)
+ sfg.set_execution_time_of_type(Butterfly.type_name(), 1)
+ sfg.set_execution_time_of_type(ConstantMultiplication.type_name(), 1)
+
+ resources = {
+ Butterfly.type_name(): 1,
+ ConstantMultiplication.type_name(): 1,
+ }
+ schedule_1 = Schedule(sfg, scheduler=HybridScheduler(resources))
+ schedule_2 = Schedule(
+ sfg, scheduler=HybridScheduler(resources), schedule_time=6, cyclic=True
+ )
+ schedule_3 = Schedule(
+ sfg, scheduler=HybridScheduler(resources), schedule_time=5, cyclic=True
+ )
+ schedule_4 = Schedule(
+ sfg, scheduler=HybridScheduler(resources), schedule_time=4, cyclic=True
+ )
+
+ assert schedule_1.start_times == {
+ "in1": 0,
+ "in3": 1,
+ "bfly3": 1,
+ "cmul0": 2,
+ "in0": 2,
+ "in2": 3,
+ "bfly0": 3,
+ "bfly1": 4,
+ "bfly2": 5,
+ "out0": 5,
+ "out1": 6,
+ "out3": 7,
+ "out2": 8,
+ }
+ assert schedule_1.laps == {
+ "s4": 0,
+ "s6": 0,
+ "s5": 0,
+ "s7": 0,
+ "s8": 0,
+ "s12": 0,
+ "s10": 0,
+ "s9": 0,
+ "s0": 0,
+ "s2": 0,
+ "s11": 0,
+ "s1": 0,
+ "s3": 0,
+ }
+ assert schedule_1.schedule_time == 8
+
+ assert schedule_2.start_times == {
+ "in1": 0,
+ "in3": 1,
+ "bfly3": 1,
+ "cmul0": 2,
+ "in0": 2,
+ "in2": 3,
+ "bfly0": 3,
+ "bfly1": 4,
+ "bfly2": 5,
+ "out0": 5,
+ "out1": 6,
+ "out3": 1,
+ "out2": 2,
+ }
+ assert schedule_2.laps == {
+ "s4": 0,
+ "s6": 1,
+ "s5": 0,
+ "s7": 1,
+ "s8": 0,
+ "s12": 0,
+ "s10": 0,
+ "s9": 0,
+ "s0": 0,
+ "s2": 0,
+ "s11": 0,
+ "s1": 0,
+ "s3": 0,
+ }
+ assert schedule_2.schedule_time == 6
+
+ assert schedule_3.start_times == {
+ "in1": 0,
+ "in3": 1,
+ "bfly3": 1,
+ "cmul0": 2,
+ "in0": 2,
+ "in2": 3,
+ "bfly0": 3,
+ "bfly1": 4,
+ "bfly2": 0,
+ "out0": 5,
+ "out1": 1,
+ "out3": 2,
+ "out2": 3,
+ }
+ assert schedule_3.laps == {
+ "s4": 0,
+ "s6": 1,
+ "s5": 0,
+ "s7": 0,
+ "s8": 0,
+ "s12": 0,
+ "s10": 1,
+ "s9": 1,
+ "s0": 0,
+ "s2": 0,
+ "s11": 0,
+ "s1": 0,
+ "s3": 0,
+ }
+ assert schedule_3.schedule_time == 5
+
+ assert schedule_4.start_times == {
+ "in1": 0,
+ "in3": 1,
+ "bfly3": 1,
+ "cmul0": 2,
+ "in0": 2,
+ "in2": 3,
+ "bfly0": 3,
+ "bfly1": 0,
+ "out0": 1,
+ "bfly2": 2,
+ "out2": 2,
+ "out1": 3,
+ "out3": 4,
+ }
+ assert schedule_4.laps == {
+ "s4": 0,
+ "s6": 0,
+ "s5": 0,
+ "s7": 0,
+ "s8": 1,
+ "s12": 1,
+ "s10": 0,
+ "s9": 1,
+ "s0": 0,
+ "s2": 0,
+ "s11": 0,
+ "s1": 0,
+ "s3": 0,
+ }
+ assert schedule_4.schedule_time == 4
+
+ def test_cyclic_scheduling_time_not_provided(self):
+ sfg = ldlt_matrix_inverse(N=2)
+
+ sfg.set_latency_of_type(MADS.type_name(), 3)
+ sfg.set_latency_of_type(Reciprocal.type_name(), 2)
+ sfg.set_execution_time_of_type(MADS.type_name(), 1)
+ sfg.set_execution_time_of_type(Reciprocal.type_name(), 1)
+
+ resources = {MADS.type_name(): 1, Reciprocal.type_name(): 1}
+ with pytest.raises(
+ ValueError,
+ match="Scheduling time must be provided when cyclic = True.",
+ ):
+ Schedule(
+ sfg,
+ scheduler=HybridScheduler(
+ max_resources=resources,
+ ),
+ cyclic=True,
+ )
+
+ def test_resources_not_enough(self):
+ sfg = ldlt_matrix_inverse(N=3)
+
+ sfg.set_latency_of_type(MADS.type_name(), 3)
+ sfg.set_latency_of_type(Reciprocal.type_name(), 2)
+ sfg.set_execution_time_of_type(MADS.type_name(), 1)
+ sfg.set_execution_time_of_type(Reciprocal.type_name(), 1)
+
+ resources = {MADS.type_name(): 1, Reciprocal.type_name(): 1}
+ with pytest.raises(
+ ValueError,
+ match="Amount of resource: mads is not enough to realize schedule for scheduling time: 5.",
+ ):
+ Schedule(
+ sfg,
+ scheduler=HybridScheduler(
+ max_resources=resources,
+ ),
+ schedule_time=5,
+ )
+
+ def test_scheduling_time_not_enough(self):
+ sfg = ldlt_matrix_inverse(N=3)
+
+ sfg.set_latency_of_type(MADS.type_name(), 3)
+ sfg.set_latency_of_type(Reciprocal.type_name(), 2)
+ sfg.set_execution_time_of_type(MADS.type_name(), 1)
+ sfg.set_execution_time_of_type(Reciprocal.type_name(), 1)
+
+ resources = {MADS.type_name(): 10, Reciprocal.type_name(): 10}
+ with pytest.raises(
+ ValueError,
+ match="Provided scheduling time 5 cannot be reached, try to enable the cyclic property or increase the time to at least 30.",
+ ):
+ Schedule(
+ sfg,
+ scheduler=HybridScheduler(
+ max_resources=resources,
+ ),
+ schedule_time=5,
+ )
+
+ def test_cyclic_scheduling_write_and_read_constrained(self):
+ sfg = radix_2_dif_fft(points=4)
+
+ sfg.set_latency_of_type(Butterfly.type_name(), 1)
+ sfg.set_latency_of_type(ConstantMultiplication.type_name(), 3)
+ sfg.set_execution_time_of_type(Butterfly.type_name(), 1)
+ sfg.set_execution_time_of_type(ConstantMultiplication.type_name(), 1)
+
+ resources = {
+ Butterfly.type_name(): 1,
+ ConstantMultiplication.type_name(): 1,
+ }
+ schedule = Schedule(
+ sfg,
+ scheduler=HybridScheduler(
+ resources, max_concurrent_reads=2, max_concurrent_writes=2
+ ),
+ schedule_time=6,
+ cyclic=True,
+ )
+
+ assert schedule.start_times == {
+ "in1": 0,
+ "in3": 1,
+ "bfly3": 1,
+ "cmul0": 2,
+ "in0": 3,
+ "in2": 4,
+ "bfly0": 4,
+ "bfly1": 5,
+ "bfly2": 0,
+ "out0": 6,
+ "out1": 1,
+ "out3": 2,
+ "out2": 3,
+ }
+ assert schedule.laps == {
+ "s4": 0,
+ "s6": 1,
+ "s5": 0,
+ "s7": 0,
+ "s8": 0,
+ "s12": 0,
+ "s10": 1,
+ "s9": 1,
+ "s0": 0,
+ "s2": 0,
+ "s11": 0,
+ "s1": 0,
+ "s3": 0,
+ }
+ assert schedule.schedule_time == 6
+
+ direct, mem_vars = schedule.get_memory_variables().split_on_length()
+ assert mem_vars.read_ports_bound() == 2
+ assert mem_vars.write_ports_bound() == 2
+
+ def test_cyclic_scheduling_several_inputs_and_outputs(self):
+ sfg = radix_2_dif_fft(points=4)
+
+ sfg.set_latency_of_type(Butterfly.type_name(), 1)
+ sfg.set_latency_of_type(ConstantMultiplication.type_name(), 3)
+ sfg.set_execution_time_of_type(Butterfly.type_name(), 1)
+ sfg.set_execution_time_of_type(ConstantMultiplication.type_name(), 1)
+
+ resources = {
+ Butterfly.type_name(): 1,
+ ConstantMultiplication.type_name(): 1,
+ Input.type_name(): 2,
+ Output.type_name(): 2,
+ }
+ schedule = Schedule(
+ sfg, scheduler=HybridScheduler(resources), schedule_time=4, cyclic=True
+ )
+
+ assert schedule.start_times == {
+ 'in1': 0,
+ 'in3': 0,
+ 'bfly3': 0,
+ 'cmul0': 1,
+ 'in0': 1,
+ "in2": 1,
+ 'bfly0': 1,
+ 'bfly1': 2,
+ 'out0': 3,
+ 'out2': 3,
+ 'bfly2': 3,
+ 'out1': 4,
+ 'out3': 4,
+ }
+ assert schedule.laps == {
+ 's4': 0,
+ 's6': 0,
+ 's5': 0,
+ 's7': 0,
+ 's8': 0,
+ 's12': 0,
+ 's10': 1,
+ 's9': 0,
+ 's0': 0,
+ 's2': 0,
+ 's11': 0,
+ 's1': 0,
+ 's3': 0,
+ }
+ assert schedule.schedule_time == 4
--
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