Add test for gfx942 number of xcds. (#674)
* Add test for 9fx942 number of xcds. * Improve the structure of mi gpu specs, add num_xcds_spec_class test. * Add to ctest. --------- Signed-off-by: xuchen-amd <xuchen@amd.com>
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xuchen-amd
GitHub
+173
-142
@@ -1,4 +1,5 @@
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import os
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from dataclasses import dataclass, field
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from typing import Any, Dict
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import yaml
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@@ -21,175 +22,205 @@ MI_CONSTANS = {
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MI350: "mi350",
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}
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gpu_series_dict = {} # key: gpu arch
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gpu_model_dict = {} # key: gpu_arch
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num_xcds_dict = {} # key: gpu model
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chip_id_dict = {} # key: chip id (int)
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# ----------------------------
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# YAML Parsing and Data Handling
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# Data Class handling to preserve the hierarchical gpu information
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# ----------------------------
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def load_yaml(file_path: str) -> Dict[str, Any]:
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"""
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Loads MI GPU YAML data /util into a Python dictionary.
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@dataclass
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class MIGPUSpecs:
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_instance = None
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Args:
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file_path (str): The path to the YAML file.
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_gpu_series_dict = {} # key: gpu arch
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_gpu_model_dict = {} # key: gpu_arch
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_num_xcds_dict = {} # key: gpu model
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_chip_id_dict = {} # key: chip id (int)
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Returns:
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Dict[str, Any]: Parsed YAML data as a nested dictionary.
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Exit with console error if an error occurs.
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"""
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console_debug("[load_yaml]")
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try:
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with open(file_path, "r") as file:
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data = yaml.safe_load(file)
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return data
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except FileNotFoundError:
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console_error(f"Error: The file '{file_path}' was not found.")
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except yaml.YAMLError as exc:
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console_error(f"Error parsing YAML file '{file_path}': {exc}")
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except Exception as e:
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console_error(
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f"An unexpected error occurred while loading YAML file '{file_path}': {e}"
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)
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_initialized = False
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def __new__(cls):
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if cls._instance is None:
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cls._instance = super().__new__(cls)
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cls._initialize()
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return cls._instance
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def parse_mi_gpu_spec():
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"""
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Parse out mi gpu data from yaml file and store in memory.
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MI GPUs
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|-- series
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|-- architecture (list)
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|-- gpu model
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|-- chip_ids
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|-- partition_mode
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"""
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@classmethod
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def _initialize(cls):
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if not cls._initialized:
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cls._parse_mi_gpu_spec()
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cls._initialized = True
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current_dir = os.path.dirname(__file__)
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yaml_file_path = os.path.join(current_dir, "mi_gpu_spec.yaml")
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# ----------------------------
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# YAML Parsing and Data Handling
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# ----------------------------
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# Load the YAML data
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yaml_data = load_yaml(yaml_file_path)
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@classmethod
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def _load_yaml(cls, file_path: str) -> Dict[str, Any]:
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"""
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Loads MI GPU YAML data /util into a Python dictionary.
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for series in yaml_data["mi_gpu_spec"]:
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curr_gpu_series = series["gpu_series"]
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console_debug("[parse_mi_gpu_spec] Processing series: %s" % curr_gpu_series)
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for archs in series["gpu_archs"]:
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curr_gpu_arch = archs["gpu_arch"]
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gpu_series_dict[curr_gpu_arch] = curr_gpu_series
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gpu_model_dict[curr_gpu_arch] = []
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for models in archs["models"]:
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curr_gpu_model = models["gpu_model"]
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gpu_model_dict[curr_gpu_arch].append(curr_gpu_model)
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num_xcds_dict[curr_gpu_model] = (
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models.get("partition_mode", {})
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.get("compute_partition_mode", {})
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.get("num_xcds", {})
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)
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if "chip_ids" in models and "physical" in models["chip_ids"]:
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chip_id_dict[models["chip_ids"]["physical"]] = curr_gpu_model
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if "chip_ids" in models and "virtual" in models["chip_ids"]:
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chip_id_dict[models["chip_ids"]["virtual"]] = curr_gpu_model
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Args:
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file_path (str): The path to the YAML file.
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Returns:
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Dict[str, Any]: Parsed YAML data as a nested dictionary.
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Exit with console error if an error occurs.
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"""
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console_debug("[load_yaml]")
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try:
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with open(file_path, "r") as file:
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data = yaml.safe_load(file)
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return data
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except FileNotFoundError:
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console_error(f"Error: The file '{file_path}' was not found.")
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except yaml.YAMLError as exc:
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console_error(f"Error parsing YAML file '{file_path}': {exc}")
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except Exception as e:
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console_error(
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f"An unexpected error occurred while loading YAML file '{file_path}': {e}"
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)
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def get_gpu_series_dict():
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if not gpu_series_dict:
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console_error(
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"gpu_series_dict not yet populated, did you run parse_mi_gpu_spec()?"
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)
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return None
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return gpu_series_dict
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@classmethod
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def _parse_mi_gpu_spec(cls):
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"""
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Parse out mi gpu data from yaml file and store in memory.
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MI GPUs
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|-- series
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|-- architecture (list)
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|-- gpu model
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|-- chip_ids
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|-- partition_mode
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"""
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current_dir = os.path.dirname(__file__)
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yaml_file_path = os.path.join(current_dir, "mi_gpu_spec.yaml")
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def get_gpu_series(gpu_arch_):
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if not gpu_series_dict:
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console_error(
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"gpu_series_dict not yet populated, did you run parse_mi_gpu_spec()?"
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)
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return None
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# Load the YAML data
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yaml_data = cls._load_yaml(yaml_file_path)
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# Normalize the key by checking both the raw and lowercase versions
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gpu_series = gpu_series_dict.get(gpu_arch_) or gpu_series_dict.get(gpu_arch_.lower())
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if gpu_series:
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return gpu_series.upper()
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for series in yaml_data["mi_gpu_spec"]:
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curr_gpu_series = series["gpu_series"]
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console_debug("[parse_mi_gpu_spec] Processing series: %s" % curr_gpu_series)
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for archs in series["gpu_archs"]:
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curr_gpu_arch = archs["gpu_arch"]
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cls._gpu_series_dict[curr_gpu_arch] = curr_gpu_series
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cls._gpu_model_dict[curr_gpu_arch] = []
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for models in archs["models"]:
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curr_gpu_model = models["gpu_model"]
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cls._gpu_model_dict[curr_gpu_arch].append(curr_gpu_model)
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cls._num_xcds_dict[curr_gpu_model] = (
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models.get("partition_mode", {})
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.get("compute_partition_mode", {})
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.get("num_xcds", {})
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)
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if "chip_ids" in models and "physical" in models["chip_ids"]:
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cls._chip_id_dict[models["chip_ids"]["physical"]] = curr_gpu_model
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if "chip_ids" in models and "virtual" in models["chip_ids"]:
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cls._chip_id_dict[models["chip_ids"]["virtual"]] = curr_gpu_model
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console_warning(f"No matching gpu series found for gpu arch: {gpu_arch_}")
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return None
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@classmethod
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def get_gpu_series_dict(cls):
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if not cls._gpu_series_dict:
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console_error(
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"gpu_series_dict not yet populated, did you run parse_mi_gpu_spec()?"
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)
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return None
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return cls._gpu_series_dict
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def get_gpu_model(gpu_arch_, chip_id_):
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# Check that gpu_model_dict is populated first
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if not gpu_model_dict:
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console_error(
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"gpu_model_dict not yet populated. Did you run parse_mi_gpu_spec()?"
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)
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return None
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gpu_arch_lower = gpu_arch_.lower()
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# Handle gfx942 with chip_id mapping
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if gpu_arch_lower not in ("gfx906", "gfx908", "gfx90a"):
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if chip_id_ and int(chip_id_) in chip_id_dict:
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gpu_model = chip_id_dict.get(int(chip_id_))
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else:
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console_warning(f"No gpu model found for chip id: {chip_id_}")
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@classmethod
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def get_gpu_series(cls, gpu_arch_):
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if not cls._gpu_series_dict:
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console_error(
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"gpu_series_dict not yet populated, did you run parse_mi_gpu_spec()?"
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)
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return None
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# Otherwise use gpu_model_dict mapping for other mi architectures
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elif gpu_arch_lower in gpu_model_dict:
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# NOTE: take the first element works for now
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gpu_model = gpu_model_dict[gpu_arch_lower][0]
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else:
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console_warning(f"No gpu model found for gpu arch: {gpu_arch_lower}")
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return None
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if not gpu_model:
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console_warning(f"No gpu model found for gpu arch: {gpu_arch_lower}")
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return None
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return gpu_model.upper()
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def get_num_xcds(gpu_model_, compute_partition_):
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# Only gpu in and above mi 300 series have more than one XCDs
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if gpu_model_.lower() in ("mi50", "mi60", "mi100", "mi210", "mi250", "mi250x"):
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return 1
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if not num_xcds_dict:
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console_error(
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"mi300_num_xcds_dict not yet populated, did you run parse_mi_gpu_spec()?"
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# Normalize the key by checking both the raw and lowercase versions
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gpu_series = cls._gpu_series_dict.get(gpu_arch_) or cls._gpu_series_dict.get(
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gpu_arch_.lower()
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)
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if gpu_series:
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return gpu_series.upper()
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console_warning(f"No matching gpu series found for gpu arch: {gpu_arch_}")
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return None
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gpu_model_lower = gpu_model_.lower()
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partition_lower = compute_partition_.lower()
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@classmethod
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def get_gpu_model(cls, gpu_arch_, chip_id_):
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# Check that gpu_model_dict is populated first
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if not cls._gpu_model_dict:
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console_error(
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"gpu_model_dict not yet populated. Did you run parse_mi_gpu_spec()?"
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)
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return None
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if gpu_model_lower not in num_xcds_dict:
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return None
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gpu_arch_lower = gpu_arch_.lower()
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model_dict = num_xcds_dict[gpu_model_lower]
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if partition_lower not in model_dict:
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console_log(f"Unknown compute partition: {compute_partition_}")
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return None
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# Handle gfx942 with chip_id mapping
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if gpu_arch_lower not in ("gfx906", "gfx908", "gfx90a"):
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if chip_id_ and int(chip_id_) in cls._chip_id_dict:
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gpu_model = cls._chip_id_dict.get(int(chip_id_))
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else:
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console_warning(f"No gpu model found for chip id: {chip_id_}")
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return None
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num_xcds = model_dict[partition_lower]
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if not num_xcds:
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console_warning(
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"Unknown compute partition found for %s / %s", compute_partition_, gpu_model_
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)
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return None
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# Otherwise use gpu_model_dict mapping for other mi architectures
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elif gpu_arch_lower in cls._gpu_model_dict:
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# NOTE: take the first element works for now
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gpu_model = cls._gpu_model_dict[gpu_arch_lower][0]
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else:
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console_warning(f"No gpu model found for gpu arch: {gpu_arch_lower}")
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return None
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return num_xcds
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if not gpu_model:
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console_warning(f"No gpu model found for gpu arch: {gpu_arch_lower}")
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return None
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return gpu_model.upper()
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@classmethod
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def get_num_xcds(cls, gpu_model_, compute_partition_):
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# Only gpu in and above mi 300 series have more than one XCDs
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if gpu_model_.lower() in ("mi50", "mi60", "mi100", "mi210", "mi250", "mi250x"):
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return 1
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if not cls._num_xcds_dict:
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console_error(
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"mi300_num_xcds_dict not yet populated, did you run parse_mi_gpu_spec()?"
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)
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return None
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gpu_model_lower = gpu_model_.lower()
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partition_lower = compute_partition_.lower()
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if gpu_model_lower not in cls._num_xcds_dict:
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return None
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model_dict = cls._num_xcds_dict[gpu_model_lower]
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if partition_lower not in model_dict:
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console_log(f"Unknown compute partition: {compute_partition_}")
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return None
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num_xcds = model_dict[partition_lower]
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if not num_xcds:
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console_warning(
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"Unknown compute partition found for %s / %s",
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compute_partition_,
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gpu_model_,
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)
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return None
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return num_xcds
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@classmethod
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def get_chip_id_dict(cls):
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if cls._chip_id_dict:
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return cls._chip_id_dict
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else:
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console_error()
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def get_chip_id_dict():
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if chip_id_dict:
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return chip_id_dict
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else:
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console_error(
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"mi300_chip_id_dict not yet populated, did you run parse_mi_gpu_spec()?"
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)
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# pre-initialize the instance when module loads
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mi_gpu_specs = MIGPUSpecs()
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