nvfp8 with Hopper+ check

Signed-off-by: Masaki Kozuki <mkozuki@nvidia.com>

thunder/executors/nvfuserex_impl.py

@@ -101,6 +101,17 @@
 }
 
 
+_lcfp8_to_nvfp8_map: dict[dtypes.dtype, DataType] = {
+    dtypes.float8_e5m2: DataType.Float8_e5m2,
+    dtypes.float8_e5m2_: DataType.Float8_e5m2,
+    dtypes.float8_e4m3fn: DataType.Float8_e4m3fn,
+    dtypes.float8_e4m3fn_: DataType.Float8_e4m3fn,
+}
+
+
+_lcdtype_to_nvdtype_map.update(_lcfp8_to_nvfp8_map)
+
+
 def lcdtype_to_nvdtype(lcdtype: type | dtypes.dtype) -> DataType:
     return _lcdtype_to_nvdtype_map[lcdtype]
 
@@ -144,7 +155,14 @@ def is_supported_devicetype(devicetype: DeviceType) -> bool:
     return devicetype is DeviceType.CUDA
 
 
-_low_precision_floats = (dtypes.float16, dtypes.float16_, dtypes.bfloat16, dtypes.bfloat16_)
+_low_precision_floats = (dtypes.float16, dtypes.float16_, dtypes.bfloat16, dtypes.bfloat16_) + tuple(
+    _lcfp8_to_nvfp8_map.keys()
+)
+
+
+def device_supports_fp8() -> bool:
+    cuda_major, _ = torch.cuda.get_device_capability()
+    return cuda_major > 8
 
 
 def is_supported_dtype(dtype: type | dtypes.dtype, *, allow_low_precision_floats: bool = True) -> bool:
@@ -154,7 +172,7 @@ def is_supported_dtype(dtype: type | dtypes.dtype, *, allow_low_precision_floats
         if dtype in _low_precision_floats:
             return False
 
-    return dtype in _lcdtype_to_nvdtype_map
+    return dtype in _lcdtype_to_nvdtype_map and (device_supports_fp8() if dtype in _lcfp8_to_nvfp8_map else True)
 
 
 def is_supported_tensor(a: TensorProxy, *, allow_low_precision_floats: bool = True) -> bool: