Block config optimisation for 256/512 configurations
- 256 and 512 configuration variants execute 1D convolutions
in an optimised manner compared to their 2x2 microblock
dimensions. This commit takes this into account to improve
Conv1D throughput on these configurations.
Signed-off-by: Tim Hall <tim.hall@arm.com>
Change-Id: I6ecdf6e4a219e356327b22f8393f50ee8817af23
diff --git a/ethosu/vela/architecture_allocator.py b/ethosu/vela/architecture_allocator.py
index e43b841..86410cf 100644
--- a/ethosu/vela/architecture_allocator.py
+++ b/ethosu/vela/architecture_allocator.py
@@ -196,6 +196,15 @@
return Shape4D(1, height, width, ofm_block.depth)
+def fit_block_for_ofm(arch: ArchitectureFeatures, ofm_shape: Shape4D, kernel: Kernel, block: Shape4D):
+ # 256/512 Conv1D optimisation (ratio of IFM:Accumulators changes) This is a specific
+ # interpretation of a more general constraint that can't be applied because the
+ # find_block_config function must return block configs that can be applied to any OFM shape.
+ if (ofm_shape.height == 1) and (kernel.height == 1) and (arch.ofm_ublock.height == 2):
+ return Shape4D(1, min(block.height, ofm_shape.height), block.width, block.depth)
+ return block
+
+
def find_block_config(
arch: ArchitectureFeatures,
npu_op_type: NpuBlockType,
@@ -274,6 +283,7 @@
ifm_block = ifm_block.with_depth(ifm_blockdepth)
# Test if the IFM/OFM blocks fit into SHRAM
+ ofm_block = fit_block_for_ofm(arch, ofm_shape, kernel, ofm_block)
layout = _try_block_config(
arch.shram, ew_usage, ofm_block, ifm_block, ifm_bits, ifm_granule, acc_bits, acc_granule, lut_banks
)
@@ -304,7 +314,7 @@
config.layout = layout
config.bank_size = arch.shram_bank_size
config.ifm_block = ifm_block
- config.ofm_block = ofm_block
+ config.ofm_block = Shape4D(1, height, width, depth)
else:
wont_fit[(width, height)] = True
@@ -322,6 +332,7 @@
block_config: Block,
arch: ArchitectureFeatures,
npu_op_type: NpuBlockType,
+ ofm_shape: Block,
ifm_shape: Block,
ifm2_shape: Optional[Block],
uses_scalar: bool,
@@ -374,6 +385,9 @@
if not is_equal_depth_op:
ifm_block = ifm_block.with_depth(ifm_blockdepth)
+ # 256/512 Conv1D optimisation (ratio of IFM:Accumulators changes)
+ block_config = fit_block_for_ofm(arch, ofm_shape, kernel, block_config)
+
layout = _try_block_config(
arch.shram, ew_usage, block_config, ifm_block, ifm_bits, ifm_granule, acc_bits, acc_granule, lut_banks
)