llama: only gemm + fa custom kernel (#16180)

* llama: tie store to grad directly * llama: set mp flags * llama: non fused grad fp8 quantize path
2026-05-12 21:03:49 -07:00
parent 38d407fd58
commit e97f2c1114
7 changed files with 31 additions and 8 deletions
@@ -18,6 +18,7 @@ export FP8=${FP8:-1}
 export ALLREDUCE_CAST=${ALLREDUCE_CAST:-1}
 export FAST_CE=${FAST_CE:-1}
 export FUSED_INPUT_QUANTIZE=${FUSED_INPUT_QUANTIZE:-1}
+export FUSED_GRAD_QUANTIZE=${FUSED_GRAD_QUANTIZE:-1}
 export FUSED_ADD_NORM_MUL_QUANTIZE=${FUSED_ADD_NORM_MUL_QUANTIZE:-1}
 export FUSED_SILU_W13=${FUSED_SILU_W13:-1}
 export FUSED_PAD_GRAD_ACCUM=${FUSED_PAD_GRAD_ACCUM:-1}
@@ -16,7 +16,8 @@ export MASTER_WEIGHTS=${MASTER_WEIGHTS:-1}
 export FP8=${FP8:-1}
 export ALLREDUCE_CAST=${ALLREDUCE_CAST:-1}
 export FAST_CE=${FAST_CE:-0}
-export FUSED_INPUT_QUANTIZE=${FUSED_INPUT_QUANTIZE:-1}
+export FUSED_INPUT_QUANTIZE=${FUSED_INPUT_QUANTIZE:-0}
+export FUSED_GRAD_QUANTIZE=${FUSED_GRAD_QUANTIZE:-0}
 export FUSED_ADD_NORM_MUL_QUANTIZE=${FUSED_ADD_NORM_MUL_QUANTIZE:-0}
 export FUSED_SILU_W13=${FUSED_SILU_W13:-0}
 export FUSED_PAD_GRAD_ACCUM=${FUSED_PAD_GRAD_ACCUM:-0}
@@ -18,6 +18,7 @@ export FP8=${FP8:-1}
 export ALLREDUCE_CAST=${ALLREDUCE_CAST:-1}
 export FAST_CE=${FAST_CE:-1}
 export FUSED_INPUT_QUANTIZE=${FUSED_INPUT_QUANTIZE:-1}
+export FUSED_GRAD_QUANTIZE=${FUSED_GRAD_QUANTIZE:-1}
 export FUSED_ADD_NORM_MUL_QUANTIZE=${FUSED_ADD_NORM_MUL_QUANTIZE:-1}
 export FUSED_SILU_W13=${FUSED_SILU_W13:-1}
 export FUSED_PAD_GRAD_ACCUM=${FUSED_PAD_GRAD_ACCUM:-1}
@@ -10,9 +10,19 @@ export DEVICE_IN_FUNCTION_BUG=1
 export DEBUG=${DEBUG:-0}
 export HK_FLASH_ATTENTION=${HK_FLASH_ATTENTION:-1}
 export ALL2ALL=${ALL2ALL:-1}
-export USE_ATOMICS=${USE_ATOMICS:-0}
+export USE_ATOMICS=${USE_ATOMICS:-1}
 export ASM_GEMM=${ASM_GEMM:-1}
 export WQKV=${WQKV:-1}
+export MASTER_WEIGHTS=${MASTER_WEIGHTS:-1}
+export FP8=${FP8:-1}
+export ALLREDUCE_CAST=${ALLREDUCE_CAST:-1}
+export FAST_CE=${FAST_CE:-0}
+export FUSED_INPUT_QUANTIZE=${FUSED_INPUT_QUANTIZE:-0}
+export FUSED_GRAD_QUANTIZE=${FUSED_GRAD_QUANTIZE:-0}
+export FUSED_ADD_NORM_MUL_QUANTIZE=${FUSED_ADD_NORM_MUL_QUANTIZE:-0}
+export FUSED_SILU_W13=${FUSED_SILU_W13:-0}
+export FUSED_PAD_GRAD_ACCUM=${FUSED_PAD_GRAD_ACCUM:-0}
+export SPLIT_W13=${SPLIT_W13:-1}
 export OFFLOAD_OPTIM=${OFFLOAD_OPTIM:-1}

 export DEFAULT_FLOAT="bfloat16" OPTIM_DTYPE="bfloat16"
@@ -19,6 +19,7 @@ export FP8=1
 export ALLREDUCE_CAST=1
 export FAST_CE=1
 export FUSED_INPUT_QUANTIZE=1
+export FUSED_GRAD_QUANTIZE=1
 export FUSED_ADD_NORM_MUL_QUANTIZE=1
 export FUSED_SILU_W13=1
 export FUSED_PAD_GRAD_ACCUM=1
@@ -2713,12 +2713,20 @@ def custom_gemm_bw(gradient:UOp, kernel:UOp):
    gbase = gradient.base if hasattr(gradient, "base") else gradient
    mailbox_entry = _grad_fp8_mailbox.pop(gbase, None) or _grad_fp8_mailbox.pop(gradient, None)
    if mailbox_entry is not None:
-      g_fp8_u, inv_scale_u, _new_amax_u, store_effect = mailbox_entry
+      g_fp8_u, inv_scale_u = mailbox_entry
      g_fp8 = Tensor(g_fp8_u, device=a.device)[:a.shape[0]]
      g_scale = Tensor(inv_scale_u, device=a.device)
    else:
      assert grad_amax_state is not None, "fp8 matmul bwd needs either a mailbox entry or a grad_amax_state"
-      g_fp8, g_scale, _, store_effect = quantize_fp8_delayed(g_t, Tensor(grad_amax_state, device=a.device))
+      if getenv("FUSED_GRAD_QUANTIZE", 0):
+        g_fp8, g_scale, _, store_effect = quantize_fp8_delayed(g_t, Tensor(grad_amax_state, device=a.device))
+        assert g_fp8.uop.op is Ops.AFTER, f"expected AFTER, got {g_fp8.uop.op}"
+        g_fp8 = Tensor(g_fp8.uop.replace(src=g_fp8.uop.src + (store_effect,)), device=a.device)
+      else:
+        grad_amax_t = Tensor(grad_amax_state, device=a.device)
+        g_fp8, g_scale, new_grad_amax = quantize_fp8(g_t, amax_state=grad_amax_t)
+        store_effect = grad_amax_state.store(new_grad_amax.uop)
+        g_fp8 = Tensor(g_fp8.contiguous().uop.after(store_effect), device=a.device)
    # dgrad: uses g_scale * x_scale * w_scale
    grad_a = asm_gemm(g_fp8, b_t, x_scale=g_scale * s_x_t, w_scale=s_w_t)
    # wgrad: no w_scale
@@ -2729,8 +2737,7 @@ def custom_gemm_bw(gradient:UOp, kernel:UOp):
    else:
      g_fp8_T = g_fp8.permute(2, 0, 1).reshape(g_t.shape[-1], -1)
    grad_b = asm_gemm(g_fp8_T, a_t.reshape(-1, a_t.shape[-1]), x_scale=g_scale * s_x_t)
-    # Attach the delayed-amax store effect (if any) to grad_a so realizing grads commits the amax update.
-    ret = (None, grad_a.uop.after(store_effect), grad_b.uop, None, None)
+    ret = (None, grad_a.uop, grad_b.uop, None, None)
    if len(inputs) == 6: ret = ret + (None,)
    return ret
  else:
@@ -53,8 +53,10 @@ def _fused_quantize_bwd_w13(gradient:UOp, kernel:UOp):
  inv_scale = (grad_amax_state_t.float() + 1e-8) / FP8_MAX
  new_grad_amax = scalar_amax(grad_amax_buf)
  store_effect = grad_amax_state_t.uop.store(new_grad_amax.uop)
-  # Stash fp8 companion + amax store for cdna_asm_gemm's bwd to attach to grad_a.
-  _grad_fp8_mailbox[grad_xw13.uop] = (grad_xw13_fp8.uop, inv_scale.uop, new_grad_amax.uop, store_effect)
+  assert grad_xw13_fp8.uop.op is Ops.AFTER, f"expected AFTER, got {grad_xw13_fp8.uop.op}"
+  grad_xw13_fp8_uop = grad_xw13_fp8.uop.replace(src=grad_xw13_fp8.uop.src + (store_effect,))
+  # Stash fp8 companion for cdna_asm_gemm's bwd to attach to grad_a.
+  _grad_fp8_mailbox[grad_xw13.uop] = (grad_xw13_fp8_uop, inv_scale.uop)
  return (None, None, grad_xw13.uop, None, None)

 def fused_quantize_fp8_w13(xw13:Tensor, amax_state:Tensor, fp8_dtype, grad_amax_state:Tensor) -> tuple[Tensor, Tensor, Tensor]: