MLBEDSW-2567: CLI option to specify allocation alignment
Added the CLI option. Only applies to CPU tensors. Added an
AllocationError which is raised when Allocation fails.
Signed-off-by: Jacob Bohlin <jacob.bohlin@arm.com>
Change-Id: I89164dea3ac7b7add7bc40aec2ce8fe50600105d
diff --git a/ethosu/vela/tensor_allocation.py b/ethosu/vela/tensor_allocation.py
index bb91145..2d464ee 100644
--- a/ethosu/vela/tensor_allocation.py
+++ b/ethosu/vela/tensor_allocation.py
@@ -22,14 +22,16 @@
from . import live_range
from . import numeric_util
+from .errors import AllocationError
from .greedy_allocation import allocate_live_ranges as greedy_allocate_live_ranges
from .nn_graph import TensorAllocator
from .tensor import MemArea
from .tensor import MemType
+from .tensor import Tensor
from .tensor import TensorPurpose
-def linear_allocate_live_ranges(live_ranges, alloc_granularity=16):
+def linear_allocate_live_ranges(live_ranges, alloc_granularity=Tensor.AllocationQuantum):
# Allocates using increasing addresses. Duplicate constant tensors will be allocated to the same address
total_sz = 0
allocated_tensors = []
@@ -55,9 +57,19 @@
if address == total_sz:
total_sz += numeric_util.round_up(int(math.ceil(lr.size)), alloc_granularity)
+ verify_alignment(live_ranges, alloc_granularity)
return total_sz
+def verify_alignment(live_ranges, alignment):
+ for lr in live_ranges.ranges.values():
+ for tens in lr.tensors:
+ if not all(op and op.run_on_npu for op in tens.ops + tens.consumer_list):
+ # This is a CPU tensor, verify alignment
+ if tens.address % alignment != 0:
+ raise AllocationError("Tensor {} not aligned to {} bytes".format(tens.name, alignment))
+
+
def mark_sram_used_for_cascaded_passes(sg, lrs):
end_pos = max(ps.time for ps in sg.cascaded_passes) + 2
mem_usage = np.zeros(end_pos, dtype=np.int64)
@@ -113,6 +125,7 @@
verbose_allocation=False,
show_minimum_possible_allocation=False,
lr_graph=None,
+ allocation_alignment=Tensor.AllocationQuantum,
):
ignore_subgraph_input_output_tensors = False
lrs = live_range.extract_live_ranges_from_cascaded_passes(
@@ -123,14 +136,15 @@
use_ifm_ofm_overlap=use_ifm_ofm_overlap,
ignore_subgraph_input_output_tensors=ignore_subgraph_input_output_tensors,
lr_graph=lr_graph,
+ allocation_alignment=allocation_alignment,
)
if lrs.ranges:
tens_alloc = tensor_allocator
if tens_alloc == TensorAllocator.Greedy:
- total_sz = greedy_allocate_live_ranges(sg, arch, lrs, mem_area, verbose_allocation)
+ total_sz = greedy_allocate_live_ranges(sg, arch, lrs, mem_area, allocation_alignment, verbose_allocation)
elif tens_alloc == TensorAllocator.LinearAlloc:
- total_sz = linear_allocate_live_ranges(lrs, 16)
+ total_sz = linear_allocate_live_ranges(lrs, allocation_alignment)
else:
assert 0