diff --git a/runs/frontier-fidelity-envelope-v1/assemble_qwen235_v020_profiles.py b/runs/frontier-fidelity-envelope-v1/assemble_qwen235_v020_profiles.py new file mode 100644 index 0000000..e9fdb96 --- /dev/null +++ b/runs/frontier-fidelity-envelope-v1/assemble_qwen235_v020_profiles.py @@ -0,0 +1,93 @@ +#!/usr/bin/env python3 +"""Assemble immutable flat profiles for the Qwen235 Frontier runner.""" + +from __future__ import annotations + +import argparse +import csv +import hashlib +import json +import shutil +from pathlib import Path + + +MODEL = "Qwen3-235B-A22B" + + +def parse_args(): + parser = argparse.ArgumentParser() + for name in ("cuda_common", "cuda_moe_tp4", "cuda_moe_ep8", "kernel_common", "kernel_moe_tp4", "kernel_moe_ep8"): + parser.add_argument(f"--{name.replace('_', '-')}", type=Path, required=True) + parser.add_argument("--output-root", type=Path, required=True) + return parser.parse_args() + + +def digest(path: Path) -> str: + value = hashlib.sha256() + value.update(path.read_bytes()) + return value.hexdigest() + + +def model_file(root: Path, name: str) -> Path: + path = root / "compute" / "h20" / MODEL / name + if not path.is_file(): + raise FileNotFoundError(path) + return path + + +def merge_csv(inputs: list[Path], output: Path) -> None: + fields = None + rows = [] + for path in inputs: + with path.open(newline="") as source: + reader = csv.DictReader(source) + if fields is None: + fields = reader.fieldnames + elif reader.fieldnames != fields: + raise ValueError(f"CSV schema mismatch: {path}") + rows.extend(reader) + if not fields or not rows: + raise ValueError("cannot merge empty profile CSV") + with output.open("w", newline="") as target: + writer = csv.DictWriter(target, fieldnames=fields, lineterminator="\n") + writer.writeheader() + writer.writerows(rows) + + +def main() -> None: + args = parse_args() + output = args.output_root.resolve() + if output.exists(): + raise FileExistsError(output) + output.mkdir(parents=True) + sources = { + "linear_op.csv": model_file(args.cuda_common, "linear_op.csv"), + "attention.csv": model_file(args.cuda_common, "attention.csv"), + "linear_op_kernel_only.csv": model_file(args.kernel_common, "linear_op_kernel_only.csv"), + "attention_kernel_only.csv": model_file(args.kernel_common, "attention_kernel_only.csv"), + } + for name, source in sources.items(): + shutil.copy2(source, output / name) + merge_csv( + [model_file(args.cuda_moe_tp4, "moe.csv"), model_file(args.cuda_moe_ep8, "moe.csv")], + output / "moe.csv", + ) + merge_csv( + [model_file(args.kernel_moe_tp4, "moe_kernel_only.csv"), model_file(args.kernel_moe_ep8, "moe_kernel_only.csv")], + output / "moe_kernel_only.csv", + ) + outputs = {path.name: digest(path) for path in sorted(output.glob("*.csv"))} + manifest = { + "schema": "qwen235-v020-frontier-profile-v1", + "model": MODEL, + "measurement_families": ["CUDA_EVENT", "KERNEL_ONLY"], + "moe_runtime_paths": {"tp4_ep1": "TRITON", "tp8_ep8": "FLASHINFER_CUTLASS"}, + "inputs": {name: str(getattr(args, name).resolve()) for name in ("cuda_common", "cuda_moe_tp4", "cuda_moe_ep8", "kernel_common", "kernel_moe_tp4", "kernel_moe_ep8")}, + "outputs": outputs, + } + (output / "manifest.json").write_text(json.dumps(manifest, indent=2, sort_keys=True) + "\n") + print(json.dumps(manifest, sort_keys=True)) + + +if __name__ == "__main__": + main() diff --git a/runs/frontier-fidelity-envelope-v1/run_qwen235_v020_profiles.sh b/runs/frontier-fidelity-envelope-v1/run_qwen235_v020_profiles.sh new file mode 100644 index 0000000..8e3d830 --- /dev/null +++ b/runs/frontier-fidelity-envelope-v1/run_qwen235_v020_profiles.sh @@ -0,0 +1,68 @@ +#!/usr/bin/env bash + +set -euo pipefail + +OUTPUT_ROOT="${OUTPUT_ROOT:?OUTPUT_ROOT is required}" +FRONTIER_SOURCE="${FRONTIER_SOURCE:-/home/admin/cpfs/wjh/aituner/frontier-q235-v020-5b953f5}" +VENV_ROOT="${VENV_ROOT:-/tmp/wjh/venvs/vllm-0.20.0-cu129-profiler-v1}" +RUNNER_DIR="${RUNNER_DIR:-$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)}" +MODEL=Qwen3-235B-A22B +TOKENS=(1 2 4 8 16 24 32 40 48 56 64 72 80 88 96 104 112 120 128 256 512 1024 2048 4096 8192) +BATCHES=(1 2 4 8 16 24 32 40 48 56 64 72 80 88 96 104 112 120 128) +KV=(128 1024 2048 4096 8192 16384 32768 40960) + +mkdir -p "${OUTPUT_ROOT}/logs" "${OUTPUT_ROOT}/provenance" +exec > >(tee -a "${OUTPUT_ROOT}/controller.log") 2>&1 + +echo "Q235_PROFILE_LAUNCH_ECHO host=dash0 model=${MODEL} vllm=0.20.0 frontier=$(git -C "${FRONTIER_SOURCE}" rev-parse HEAD) device=H20 methods={CUDA_EVENT,KERNEL_ONLY} attention_tp={4,8} moe_paths={TP4/EP1:Triton,TP1/EP8:FlashInfer-CUTLASS} token_points=${#TOKENS[@]} batch_points=${#BATCHES[@]} kv_points=${#KV[@]} parallel_gpus=6 expected_wall=20-75m expected_cost=2-7_H20-GPUh output=${OUTPUT_ROOT}" +date -u +START_UTC=%Y-%m-%dT%H:%M:%SZ +nvidia-smi --query-gpu=index,memory.used --format=csv,noheader,nounits \ + | awk '$2 > 16 {exit 1}' +git -C "${FRONTIER_SOURCE}" rev-parse HEAD > "${OUTPUT_ROOT}/provenance/frontier.commit" +"${VENV_ROOT}/bin/vllm" --version > "${OUTPUT_ROOT}/provenance/vllm.version" + +common_profile() { + local gpu="$1" method="$2" root="$3" + env CUDA_VISIBLE_DEVICES="${gpu}" PYTHONPATH="${FRONTIER_SOURCE}" \ + "${VENV_ROOT}/bin/python" -m frontier.profiling.linear_op.main \ + --disable_ray --num_gpus 1 --device h20 --output_dir "${root}" --models "${MODEL}" \ + --num_tensor_parallel_workers 1 4 8 --attn_tp 4 8 --ffn_tp 1 4 \ + --num_tokens_list "${TOKENS[@]}" --profile_method "${method}" --yes + env CUDA_VISIBLE_DEVICES="${gpu}" PYTHONPATH="${FRONTIER_SOURCE}" \ + "${VENV_ROOT}/bin/python" -m frontier.profiling.attention.main \ + --disable_ray --num_gpus 1 --device h20 --output_dir "${root}" --models "${MODEL}" \ + --num_tensor_parallel_workers 4 8 --max_model_len 40960 --max_seq_len 8192 \ + --batch_size_list "${BATCHES[@]}" --decode_kv_cache_size_list "${KV[@]}" \ + --fixed_chunked_prefill_size 8192 --attention_backend FLASHINFER \ + --profile_method "${method}" --yes +} + +moe_profile() { + local gpu="$1" method="$2" tp="$3" ep="$4" root="$5" + env CUDA_VISIBLE_DEVICES="${gpu}" PYTHONPATH="${FRONTIER_SOURCE}" \ + "${VENV_ROOT}/bin/python" -m frontier.profiling.moe.main \ + --disable_ray --num_gpus 1 --device h20 --output_dir "${root}" --models "${MODEL}" \ + --num_tensor_parallel_workers "${tp}" --expert_parallel_sizes "${ep}" \ + --num_tokens_list "${TOKENS[@]}" --load_distributions uniform \ + --num_samples_per_distribution 1 --profile_method "${method}" --yes +} + +declare -a pids=() +common_profile 0 cuda_event "${OUTPUT_ROOT}/cuda-common" > "${OUTPUT_ROOT}/logs/cuda-common.log" 2>&1 & pids+=("$!") +common_profile 1 record_function "${OUTPUT_ROOT}/kernel-common" > "${OUTPUT_ROOT}/logs/kernel-common.log" 2>&1 & pids+=("$!") +moe_profile 2 cuda_event 4 1 "${OUTPUT_ROOT}/cuda-moe-tp4" > "${OUTPUT_ROOT}/logs/cuda-moe-tp4.log" 2>&1 & pids+=("$!") +moe_profile 3 cuda_event 1 8 "${OUTPUT_ROOT}/cuda-moe-ep8" > "${OUTPUT_ROOT}/logs/cuda-moe-ep8.log" 2>&1 & pids+=("$!") +moe_profile 4 record_function 4 1 "${OUTPUT_ROOT}/kernel-moe-tp4" > "${OUTPUT_ROOT}/logs/kernel-moe-tp4.log" 2>&1 & pids+=("$!") +moe_profile 5 record_function 1 8 "${OUTPUT_ROOT}/kernel-moe-ep8" > "${OUTPUT_ROOT}/logs/kernel-moe-ep8.log" 2>&1 & pids+=("$!") +failed=0 +for pid in "${pids[@]}"; do wait "${pid}" || failed=1; done +[[ "${failed}" -eq 0 ]] || { tail -80 "${OUTPUT_ROOT}"/logs/*.log; exit 1; } + +"${VENV_ROOT}/bin/python" "${RUNNER_DIR}/assemble_qwen235_v020_profiles.py" \ + --cuda-common "${OUTPUT_ROOT}/cuda-common" \ + --cuda-moe-tp4 "${OUTPUT_ROOT}/cuda-moe-tp4" --cuda-moe-ep8 "${OUTPUT_ROOT}/cuda-moe-ep8" \ + --kernel-common "${OUTPUT_ROOT}/kernel-common" \ + --kernel-moe-tp4 "${OUTPUT_ROOT}/kernel-moe-tp4" --kernel-moe-ep8 "${OUTPUT_ROOT}/kernel-moe-ep8" \ + --output-root "${OUTPUT_ROOT}/frozen" +date -u +END_UTC=%Y-%m-%dT%H:%M:%SZ +echo Q235_V020_PROFILES_COMPLETE