kernel row alignment correction (#1789)

Summary:
Pull Request resolved: #1789

* sharder can help inject tbe row alignment via extra params from fused params.

Reviewed By: tissue3

Differential Revision: D54842984

fbshipit-source-id: df52030274fefe3eec271b87fdbb61923eafaa66

torchrec/distributed/fused_params.py

@@ -20,6 +20,7 @@
 FUSED_PARAM_QUANT_STATE_DICT_SPLIT_SCALE_BIAS: str = (
     "__register_quant_state_dict_split_scale_bias"
 )
+FUSED_PARAM_TBE_ROW_ALIGNMENT: str = "__register_tbe_row_alignment"
 
 
 class TBEToRegisterMixIn:
@@ -47,6 +48,15 @@ def is_fused_param_register_tbe(fused_params: Optional[Dict[str, Any]]) -> bool:
     )
 
 
+def get_fused_param_tbe_row_alignment(
+    fused_params: Optional[Dict[str, Any]]
+) -> Optional[int]:
+    if fused_params is None or FUSED_PARAM_TBE_ROW_ALIGNMENT not in fused_params:
+        return None
+    else:
+        return fused_params[FUSED_PARAM_TBE_ROW_ALIGNMENT]
+
+
 def is_fused_param_quant_state_dict_split_scale_bias(
     fused_params: Optional[Dict[str, Any]]
 ) -> bool:
@@ -68,5 +78,7 @@ def tbe_fused_params(
         fused_params_for_tbe.pop(FUSED_PARAM_REGISTER_TBE_BOOL)
     if FUSED_PARAM_QUANT_STATE_DICT_SPLIT_SCALE_BIAS in fused_params_for_tbe:
         fused_params_for_tbe.pop(FUSED_PARAM_QUANT_STATE_DICT_SPLIT_SCALE_BIAS)
+    if FUSED_PARAM_TBE_ROW_ALIGNMENT in fused_params_for_tbe:
+        fused_params_for_tbe.pop(FUSED_PARAM_TBE_ROW_ALIGNMENT)
 
     return fused_params_for_tbe

torchrec/distributed/quant_embedding_kernel.py

@@ -32,6 +32,7 @@
     GroupedEmbeddingConfig,
 )
 from torchrec.distributed.fused_params import (
+    get_fused_param_tbe_row_alignment,
     is_fused_param_quant_state_dict_split_scale_bias,
     is_fused_param_register_tbe,
     tbe_fused_params,
@@ -318,6 +319,9 @@ def __init__(
         self._quant_state_dict_split_scale_bias: bool = (
             is_fused_param_quant_state_dict_split_scale_bias(fused_params)
         )
+        self._tbe_row_alignment: Optional[int] = get_fused_param_tbe_row_alignment(
+            fused_params
+        )
         self._emb_module: IntNBitTableBatchedEmbeddingBagsCodegen = (
             IntNBitTableBatchedEmbeddingBagsCodegen(
                 embedding_specs=[
@@ -342,7 +346,11 @@ def __init__(
                 device=device,
                 pooling_mode=PoolingMode.NONE,
                 feature_table_map=self._feature_table_map,
-                row_alignment=16,
+                row_alignment=(
+                    self._tbe_row_alignment
+                    if self._tbe_row_alignment is not None
+                    else 16
+                ),
                 uvm_host_mapped=True,  # Use cudaHostAlloc for UVM CACHING to fix imbalance numa memory issue
                 **(tbe_fused_params(fused_params) or {}),
             )