[Distributed] Rudimentary distributed Python API (#64)

* Add rudimentary non-production distributed Python API

* Distributed execution validation

Add functionality that validates distributed StableHLO
is producing the same results as non-distributed.

* Add execution time measurement

* Distributed Python API: add call_count to run_ranks

* Add setup script for distributed Python API

* Add JAX to install setup

---------

Co-authored-by: Boian Petkantchin <[email protected]>

runtime/bindings/python/CMakeLists.txt

@@ -147,6 +147,11 @@ iree_py_library(
     "iree/_runtime/scripts/iree_dump_parameters/__main__.py"
     "iree/_runtime/scripts/iree_run_module/__main__.py"
     "iree/_runtime/scripts/iree_tracy_capture/__main__.py"
+    "iree/runtime/distributed/__init__.py"
+    "iree/runtime/distributed/distributed.py"
+    "iree/runtime/distributed/run_rank.py"
+    "iree/runtime/distributed/sharding_pass_validation.py"
+    "iree/runtime/distributed/utils.py"
   PYEXT_DEPS
     iree_runtime_bindings_python_PyExtRt
 )

runtime/bindings/python/iree/runtime/__init__.py

@@ -65,4 +65,5 @@
 from .function import *
 from .io import *
 
+from . import distributed
 from . import flags

runtime/bindings/python/iree/runtime/distributed/__init__.py

@@ -0,0 +1,9 @@
+# Copyright 2023 The IREE Authors
+#
+# Licensed under the Apache License v2.0 with LLVM Exceptions.
+# See https://llvm.org/LICENSE.txt for license information.
+# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+
+from .distributed import prepare_shards_io_files, run_ranks
+
+__all__ = ["prepare_shards_io_files", "run_ranks"]

runtime/bindings/python/iree/runtime/distributed/distributed.py

@@ -0,0 +1,86 @@
+# Copyright 2023 The IREE Authors
+#
+# Licensed under the Apache License v2.0 with LLVM Exceptions.
+# See https://llvm.org/LICENSE.txt for license information.
+# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+
+import iree.compiler
+import sys
+import iree.runtime
+from iree.runtime.array_interop import DeviceArray
+import os
+from numpy.typing import ArrayLike
+from typing import List, Tuple
+import tempfile
+import subprocess
+from . import utils
+
+
+def prepare_shards_io_files(
+    inputs: List[List[ArrayLike]], out_dir: str
+) -> Tuple[List[str], List[str]]:
+    input_filepaths = []
+    output_filepaths = []
+    for i in range(len(inputs)):
+        input_filepath = os.path.join(out_dir, f"shard_{i}", "input.npy")
+        input_filepaths.append(input_filepath)
+        os.makedirs(os.path.dirname(input_filepath))
+        utils.write_numpy_arrays_to_file(filepath=input_filepath, arrays=inputs[i])
+        output_filepath = os.path.join(out_dir, f"shard_{i}", "output.npy")
+        output_filepaths.append(output_filepath)
+    return input_filepaths, output_filepaths
+
+
+def run_ranks(
+    num_ranks: int,
+    module_filepath: str,
+    function: str,
+    inputs: List[List[ArrayLike]],
+    driver: str,
+    call_count: int = 1,
+    measure_execution_time: bool = False,
+    warmup: int = 0,
+) -> List[List[ArrayLike]]:
+    """
+    Start all ranks with mpirun.
+    On all ranks run the function |function| from the given module.
+    Parameters
+    ----------
+    inputs : Function inputs for all ranks.
+    Axis 0 is ranks. Axis 1 is arguments per rank.
+    Returns
+    -------
+    The output of the function for all ranks.
+    Axis 0 is ranks. Axis 1 is arguments per rank.
+    """
+    with tempfile.TemporaryDirectory() as out_dir:
+        input_filepaths, output_filepaths = prepare_shards_io_files(
+            inputs=inputs, out_dir=out_dir
+        )
+        hal_driver = iree.runtime.get_driver(driver)
+        hal_driver.query_available_devices()
+        subprocess.check_call(
+            [
+                "mpirun",
+                "--oversubscribe",
+                "-n",
+                str(num_ranks),
+                sys.executable,
+                os.path.join(os.path.dirname(__file__), "run_rank.py"),
+                f"--driver={driver}",
+                f"--module_filepath={module_filepath}",
+                f"--function={function}",
+                f"--call_count={call_count}",
+            ]
+            + (["--measure_execution_time"] if measure_execution_time else [])
+            + [
+                f"--warmup={warmup}",
+                "--inputs",
+            ]
+            + input_filepaths
+            + ["--outputs"]
+            + output_filepaths
+        )
+        return [
+            utils.read_numpy_arrays_from_file(out_file) for out_file in output_filepaths
+        ]

runtime/bindings/python/iree/runtime/distributed/run_rank.py

@@ -0,0 +1,132 @@
+# Copyright 2023 The IREE Authors
+#
+# Licensed under the Apache License v2.0 with LLVM Exceptions.
+# See https://llvm.org/LICENSE.txt for license information.
+# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+
+import iree.compiler
+import argparse
+import iree.runtime
+from iree.runtime.array_interop import DeviceArray
+from mpi4py import MPI
+import utils
+import datetime
+import numpy as np
+
+
+def parse_args():
+    parser = argparse.ArgumentParser(description="Run 1 shard.")
+    parser.add_argument("--driver", type=str, default="local-task", help="Device URI.")
+    parser.add_argument(
+        "--module_filepath", type=str, required=True, help="Path to IREE module."
+    )
+    parser.add_argument(
+        "--function", type=str, required=True, help="Name of function to call."
+    )
+    parser.add_argument(
+        "--call_count",
+        type=int,
+        default=1,
+        help="How many times to call the function during time measurement.",
+    )
+    parser.add_argument(
+        "--measure_execution_time",
+        action="store_true",
+        default=False,
+        help="Measure execution time in seconds f64 and append to results.",
+    )
+    parser.add_argument(
+        "--warmup",
+        type=int,
+        default=0,
+        help="How many warmup calls to do before the actual call that generates the result.",
+    )
+    parser.add_argument(
+        "--inputs",
+        nargs="+",
+        type=str,
+        required=True,
+        help="Path to IREE module inputs for all ranks in npy format.",
+    )
+    parser.add_argument(
+        "--outputs",
+        nargs="+",
+        type=str,
+        required=True,
+        help="Path to IREE module outputs form all ranks in npy format.",
+    )
+    return parser.parse_args()
+
+
+def run_module(
+    device: iree.runtime.HalDevice,
+    module_filepath: str,
+    function: str,
+    call_count: int,
+    input_filepath: str,
+    output_filepath: str,
+    measure_execution_time: bool,
+    warmup: int,
+):
+    config = iree.runtime.Config(device=device)
+    with open(module_filepath, "rb") as f:
+        vm_flatbuffer = f.read()
+    vm_module = iree.runtime.VmModule.from_flatbuffer(config.vm_instance, vm_flatbuffer)
+    bound_module = iree.runtime.load_vm_module(vm_module, config)
+    input_args = utils.read_numpy_arrays_from_file(input_filepath)
+    input_args_on_device = [
+        iree.runtime.asdevicearray(device, arr) for arr in input_args
+    ]
+    for _ in range(warmup):
+        getattr(bound_module, function)(*input_args_on_device)
+    if measure_execution_time:
+        # Sync all ranks
+        MPI.COMM_WORLD.barrier()
+        start_time = datetime.datetime.now()
+    assert call_count > 0
+    for _ in range(call_count):
+        results = getattr(bound_module, function)(*input_args_on_device)
+    if measure_execution_time:
+        end_time = datetime.datetime.now()
+    if isinstance(results, DeviceArray):
+        results = [results]
+    if measure_execution_time:
+        if isinstance(results, tuple):
+            results = list(results)
+        results.append(
+            np.array((end_time - start_time).total_seconds() / call_count, dtype=float)
+        )
+    utils.write_numpy_arrays_to_file(filepath=output_filepath, arrays=results)
+
+
+def run_rank(
+    driver: str,
+    module_filepath: str,
+    function: str,
+    inputs: str,
+    outputs: str,
+    call_count: int,
+    measure_execution_time: bool,
+    warmup: int,
+):
+    rank = MPI.COMM_WORLD.Get_rank()
+    hal_driver = iree.runtime.get_driver(driver)
+    device_infos = hal_driver.query_available_devices()
+    device = hal_driver.create_device(
+        device_infos[rank % len(device_infos)]["device_id"]
+    )
+    run_module(
+        device=device,
+        module_filepath=module_filepath,
+        function=function,
+        call_count=call_count,
+        input_filepath=inputs[rank],
+        output_filepath=outputs[rank],
+        measure_execution_time=measure_execution_time,
+        warmup=warmup,
+    )
+
+
+if __name__ == "__main__":
+    args = parse_args()
+    run_rank(**vars(args))

runtime/bindings/python/iree/runtime/distributed/setup.sh

@@ -0,0 +1,15 @@
+#!/bin/bash
+
+set -e
+
+distribution=$(. /etc/os-release;echo $ID$VERSION_ID | sed -e 's/\.//g')
+wget -O /tmp/cuda-keyring_1.0-1_all.deb \
+  https://developer.download.nvidia.com/compute/cuda/repos/$distribution/x86_64/cuda-keyring_1.0-1_all.deb
+sudo dpkg -i /tmp/cuda-keyring_1.0-1_all.deb
+sudo apt update
+# For CMake to find CUDA when using LLD.
+sudo apt -y install lld
+
+sudo apt -y install libopenmpi-dev
+sudo apt -y install libnccl-dev=2.18.1-1+cuda12.1
+pip install mpi4py jax[cpu]