vela: Improve block configuration and weight buffering algorithm
- Update block config selection to take into account partial
IFM fetches at edge of non-whole OFM block data.
- Change to scheduler depth slicing for networks in MLBEDSW-4637
for improved buffering. This helps general performance by buffering
larger depth slices.
- Bug fix for opt_max_schedule always being fitted to SRAM which
prevented the optimisation step running in some cases.
Signed-off-by: Tim Hall <tim.hall@arm.com>
Change-Id: I97642c5adec3bb684b1daabf2b81574c27d4eef2
diff --git a/ethosu/vela/architecture_allocator.py b/ethosu/vela/architecture_allocator.py
index c308a4a..e43b841 100644
--- a/ethosu/vela/architecture_allocator.py
+++ b/ethosu/vela/architecture_allocator.py
@@ -279,25 +279,21 @@
)
if layout:
- # Calculate cost in terms of OFM pixels per IFM+Weights fetch
- ifm_fetch = ifm_block.elements_wh() * ifm_shape.depth
- weight_fetch = weight_fetch_wh * ifm_shape.depth * (1 if is_depthwise else ofm_block.depth)
- relative_fetch = (ifm_fetch * ifm_repeats + weight_fetch) / ofm_block.elements()
+ full_blocks = Shape4D.div_round_up(ofm_shape, ofm_block)
+ blocks = ofm_shape / ofm_block
- # Bias by the number of blocks we'd need to fill the OFM area (fewer, larger, blocks are better)
- block_bias = round_up_divide(ofm_shape.height, ofm_block.height)
- block_bias *= round_up_divide(ofm_shape.width, ofm_block.width)
- # Check waste on all axes (prefer depth, width then height)
- waste_ratio = 1 + (1.2 * ((ofm_shape.depth % ofm_block.depth) / ofm_block.depth))
- waste_ratio *= 1 + (1.1 * ((ofm_shape.width % ofm_block.width) / ofm_block.width))
- waste_ratio *= 1 + (1.0 * ((ofm_shape.height % ofm_block.height) / ofm_block.height))
+ # Weights fetching
+ weight_fetch = weight_fetch_wh * ifm_shape.depth * full_blocks.elements_wh()
+ if not is_depthwise:
+ weight_fetch *= ofm_block.depth * blocks.depth
- # Bias for larger area coverage (or volume if not depthwise)
- area_bias = 1 / (ofm_block.height * ofm_block.width)
- if not (is_depthwise or is_pooling):
- area_bias = area_bias / ofm_block.depth
+ # IFM fetching
+ ifm_fetch = ifm_block.elements_wh() * ifm_shape.depth * ifm_repeats * blocks.elements_wh()
+ if not is_equal_depth_op:
+ ifm_fetch *= full_blocks.depth
- relative_cost = relative_fetch * block_bias * waste_ratio * area_bias
+ # Scale relative to every output OFM element
+ relative_cost = (ifm_fetch + weight_fetch) / ofm_shape.elements()
# If the entire IFM can be encompassed by both buffers, bias to prefer this configuration
if ifm_shape.elements() < ifm_block.elements() * 2: