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composable_kernel/dispatcher/python/dispatcher_common.py
Vidyasagar Ananthan 86591de476 [rocm-libraries] ROCm/rocm-libraries#5260 (commit a1834d2)
[CK] [CK_Tile] Add FMHA scaffolding to CK kernel dispatcher
 (#5260)
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## Motivation

The CK Tile dispatcher currently supports GEMM and Grouped Convolution
but has no support for Fused Multi-Head Attention (FMHA). The
example/ck_tile/01_fmha folder contains a comprehensive FMHA
implementation with forward, backward, split-KV, paged-KV, append-KV,
and batch-prefill kernels across multiple GPU architectures — but there
is no unified dispatch layer for it. This PR ports the FMHA stack into
the dispatcher, following the same architectural patterns established by
GEMM and Grouped Convolution, enabling runtime kernel selection, JIT
compilation from Python, and a declarative C++ example flow. Autotuning
heuristics to follow.

## Technical Details

This PR adds FMHA scaffolding to the CK dispatcher framework, mirroring
GEMM's layered architecture. Seven new C++ runtime headers provide type
definitions (coexisting with upstream headers via __has_include,
requiring zero modifications to example/ck_tile/01_fmha/), a problem
builder with 18+ setters, Signature + Algorithm kernel key matching, a
virtual kernel instance, a DECL_FMHA_KERNEL_SET macro with wildcard
support and named tile/wave/warp setters, arch-aware registry with JSON
export, and a dispatcher with seqtune-aware selection, configurable
timing, and multi-stage execution plans for split-KV (two-stage) and
backward (three-stage). The codegen pipeline is driven by a
fmha_arch_specs.json capturing per-arch tile tables and pipeline
constraints for five architectures (gfx90a/942/950/1100/1201), migrated
from hardcoded logic in 01_fmha/codegen/, with supporting modules for
C++ symbol mappings, validation rules, and named receipt profiles
(ck_default, flash, pytorch, aiter, fp32, fp8). Python integration
(fmha_utils.py) mirrors the C++ layer with JIT compilation, parallel
multi-kernel builds, HIP memory management via ctypes, tolerance-based
validation, and a NumPy CPU reference with GQA support. Twenty-seven C++
and thirty-two Python examples cover the full feature surface — forward,
split-KV, masks, bias, dropout, GQA, backward, append-KV, batch prefill,
fp8, logits soft cap, sink tokens, and parameter sweeps — all
JIT-compiled on the fly.

## Test Plan

Seven test files cover the runtime types, codegen, and end-to-end
correctness. C++ unit tests validate the problem builder, dispatcher
planning (single-stage for forward/paged-KV/append-KV; multi-stage for
split-KV and backward), registry operations, and the kernel-set
declaration macro. Python unit tests verify codegen emission, profile
filtering, and 15 validation rules for masks, hdim constraints, and
pipeline requirements. GPU execution validation in 01_basic_fmha
--validate reports zero errors across 65,536 elements with max absolute
error of 7.29e-05. A gold-standard parity suite (test_fmha_parity.py)
runs 14 configurations through both the upstream tile_example_fmha_fwd
and the dispatcher, comparing exit codes to confirm behavioral parity —
all 14 match.

## Test Result

The C++ smoke test builds and passes all 9 compiled examples, and a
Python JIT sweep (29_sweep_seqlen.py) passes 7/7 configurations reaching
up to 375 TFLOPS at seqlen 2048.

## Submission Checklist

- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
2026-05-17 07:30:33 +00:00

389 lines
12 KiB
Python

#!/usr/bin/env python3
# Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
# SPDX-License-Identifier: MIT
"""
Shared Python dispatcher utilities for GEMM and grouped convolution.
Extracted from ctypes_utils.py (GEMM) + compile_grouped_conv_examples.py (grouped conv).
Both ctypes_utils.py and grouped_conv_utils.py import from here to
eliminate duplication.
Best-of-both:
- Validation and auto-correction return typed objects (GEMM pattern)
- Colors class with cross-platform ANSI handling (conv pattern)
- Phased output helpers (conv pattern)
- logging module instead of bare print() (shared improvement)
"""
import logging
import shutil
import sys
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple
log = logging.getLogger(__name__)
# ============================================================================
# Path Configuration
# ============================================================================
def get_dispatcher_root() -> Path:
"""Get the dispatcher root directory (parent of python/)."""
return Path(__file__).parent.parent
def get_ck_root() -> Path:
"""Get the CK root directory (parent of dispatcher/)."""
return get_dispatcher_root().parent
def get_build_dir() -> Path:
"""Get the build directory."""
return get_dispatcher_root() / "build"
def get_generated_kernels_dir() -> Path:
"""Get the generated kernels directory."""
return get_build_dir() / "generated_kernels"
def get_codegen_dir() -> Path:
"""Get the codegen scripts directory."""
return get_dispatcher_root() / "codegen"
def detect_gpu_arch(fallback: str = "gfx942") -> str:
"""Detect the GPU architecture from rocminfo. Falls back to the given default."""
import subprocess
try:
out = subprocess.check_output(
["rocminfo"], text=True, stderr=subprocess.DEVNULL
)
for line in out.splitlines():
if "Name:" in line and "gfx" in line:
return line.split()[-1].strip()
except Exception:
pass
return fallback
# ============================================================================
# Architecture Filter Data
# ============================================================================
_arch_data_cache: Optional[Dict[str, Any]] = None
def detect_gpu_arch(fallback: str = "gfx942") -> str:
"""Detect the GPU architecture from rocminfo. Falls back to the given default."""
import subprocess
try:
out = subprocess.check_output(
["rocminfo"], text=True, stderr=subprocess.DEVNULL
)
for line in out.splitlines():
if "Name:" in line and "gfx" in line:
return line.split()[-1].strip()
except Exception:
pass
return fallback
def get_arch_filter_data() -> Dict[str, Any]:
"""Load arch filter data from arch_specs_generated if available.
Returns dict with keys: trait_unsupported, warp_combos,
warp_tile_combos, supported_archs.
"""
global _arch_data_cache
if _arch_data_cache is not None:
return _arch_data_cache
codegen_dir = get_dispatcher_root() / "codegen"
sys.path.insert(0, str(codegen_dir))
try:
from arch_specs_generated import (
TRAIT_UNSUPPORTED_COMBINATIONS,
WARP_SUPPORTED_COMBINATIONS,
WARP_TILE_SUPPORTED_COMBINATIONS,
get_supported_archs,
)
_arch_data_cache = {
"trait_unsupported": TRAIT_UNSUPPORTED_COMBINATIONS,
"warp_combos": WARP_SUPPORTED_COMBINATIONS,
"warp_tile_combos": WARP_TILE_SUPPORTED_COMBINATIONS,
"supported_archs": get_supported_archs(),
}
except ImportError:
_arch_data_cache = {
"trait_unsupported": {
("compv3", "cshuffle", "interwave"),
("compv3", "default", "interwave"),
("compv4", "cshuffle", "interwave"),
("compv4", "default", "interwave"),
},
"warp_combos": {
"gfx942": [[1, 4, 1], [2, 2, 1], [4, 1, 1]],
"gfx90a": [[1, 4, 1], [2, 2, 1], [4, 1, 1]],
},
"warp_tile_combos": {
"gfx942": {"fp16_fp16_fp32": [[16, 16, 16], [32, 32, 16]]},
"gfx90a": {"fp16_fp16_fp32": [[16, 16, 16], [32, 32, 16]]},
},
"supported_archs": ["gfx90a", "gfx942", "gfx950"],
}
return _arch_data_cache
# ============================================================================
# Validation Result
# ============================================================================
@dataclass
class ValidationResultBase:
"""Result of kernel config validation (shared base for GEMM and conv)."""
is_valid: bool
errors: List[str] = field(default_factory=list)
warnings: List[str] = field(default_factory=list)
suggested_fixes: Dict[str, Any] = field(default_factory=dict)
def print_result(self, indent: str = " "):
if self.is_valid:
print(f"{indent}OK Configuration valid")
else:
print(f"{indent}WARNING Configuration has issues:")
for err in self.errors:
print(f"{indent} - {err}")
if self.warnings:
for warn in self.warnings:
print(f"{indent} Warning: {warn}")
if self.suggested_fixes:
print(f"{indent} Suggested fixes:")
for key, val in self.suggested_fixes.items():
print(f"{indent} {key}: {val}")
# ============================================================================
# Validation Helpers
# ============================================================================
def validate_wave_config(wave_cfg: List[int], arch: str) -> Tuple[bool, str]:
"""Validate a [wave_m, wave_n, wave_k] config for *arch*.
Returns (is_valid, error_message). Empty string on success.
"""
data = get_arch_filter_data()
valid_waves = data["warp_combos"].get(arch, [[2, 2, 1]])
if wave_cfg in valid_waves:
return True, ""
valid_str = ", ".join(f"[{c[0]},{c[1]},{c[2]}]" for c in valid_waves)
return (
False,
f"Unsupported wave configuration {wave_cfg} for {arch}. "
f"Valid wave configs: {valid_str}",
)
def validate_warp_tile_config(
warp_cfg: List[int], arch: str, dtype: str
) -> Tuple[bool, str]:
"""Validate a [warp_m, warp_n, warp_k] config for *arch*/*dtype*.
Returns (is_valid, error_message). Empty string on success.
"""
data = get_arch_filter_data()
acc = "int32" if dtype == "int8" else "fp32"
dtype_key = f"{dtype}_{dtype}_{acc}"
valid_tiles = (
data["warp_tile_combos"]
.get(arch, {})
.get(dtype_key, [[32, 32, 16], [16, 16, 16]])
)
if warp_cfg in valid_tiles:
return True, ""
valid_str = ", ".join(f"[{c[0]},{c[1]},{c[2]}]" for c in valid_tiles[:5])
return (
False,
f"Unsupported warp tile {warp_cfg} for {arch}/{dtype}. "
f"Valid warp tiles: {valid_str}",
)
def validate_trait_combo(
pipeline: str, epilogue: str, scheduler: str
) -> Tuple[bool, str]:
"""Validate a (pipeline, epilogue, scheduler) combination.
Returns (is_valid, error_message). Empty string on success.
"""
data = get_arch_filter_data()
combo = (pipeline, epilogue, scheduler)
if combo in data["trait_unsupported"]:
return (
False,
f"Unsupported trait combination: pipeline={pipeline}, "
f"epilogue={epilogue}, scheduler={scheduler}",
)
return True, ""
# ============================================================================
# Auto-Correction Helpers
# ============================================================================
def auto_correct_wave(wave_cfg: List[int], arch: str) -> List[int]:
"""Return the first valid wave config for *arch*.
If *wave_cfg* is already valid, returns it unchanged.
"""
data = get_arch_filter_data()
valid_waves = data["warp_combos"].get(arch, [[2, 2, 1]])
if wave_cfg in valid_waves:
return wave_cfg
return valid_waves[0] if valid_waves else [2, 2, 1]
def auto_correct_trait(pipeline: str, scheduler: str) -> Tuple[str, str]:
"""Return a corrected (pipeline, scheduler) pair.
If the compute pipeline doesn't support interwave, switch to intrawave.
"""
data = get_arch_filter_data()
for epilogue in ("cshuffle", "default"):
if (pipeline, epilogue, scheduler) in data["trait_unsupported"]:
return pipeline, "intrawave"
return pipeline, scheduler
# ============================================================================
# Colors (adopted from compile_grouped_conv_examples.py -- cross-platform)
# ============================================================================
class Colors:
"""Cross-platform ANSI color support.
Respects sys.platform (no ANSI on Windows) and isatty() check so
piped/redirected output stays clean.
"""
_GREEN = "\033[0;32m"
_YELLOW = "\033[1;33m"
_RED = "\033[0;31m"
_CYAN = "\033[0;36m"
_BOLD = "\033[1m"
_NC = "\033[0m"
@classmethod
def _use_color(cls) -> bool:
return (
sys.platform != "win32"
and hasattr(sys.stdout, "isatty")
and sys.stdout.isatty()
)
@classmethod
def green(cls, text: str) -> str:
if cls._use_color():
return f"{cls._GREEN}{text}{cls._NC}"
return text
@classmethod
def red(cls, text: str) -> str:
if cls._use_color():
return f"{cls._RED}{text}{cls._NC}"
return text
@classmethod
def yellow(cls, text: str) -> str:
if cls._use_color():
return f"{cls._YELLOW}{text}{cls._NC}"
return text
@classmethod
def cyan(cls, text: str) -> str:
if cls._use_color():
return f"{cls._CYAN}{text}{cls._NC}"
return text
@classmethod
def bold(cls, text: str) -> str:
if cls._use_color():
return f"{cls._BOLD}{text}{cls._NC}"
return text
# ============================================================================
# Phased Output Helpers
# ============================================================================
def print_phase(number: int, description: str) -> None:
"""Print a phase header (e.g. 'Phase 1: Codegen')."""
print(f"\n{'=' * 60}")
print(f" Phase {number}: {description}")
print(f"{'=' * 60}")
def print_success(message: str) -> None:
"""Print a success message."""
print(f" OK {Colors.green(message)}")
def print_error(message: str) -> None:
"""Print an error message."""
print(f" FAIL {Colors.red(message)}")
def print_info(message: str) -> None:
"""Print an info message."""
print(f" {Colors.cyan(message)}")
# ============================================================================
# Cleanup Helpers
# ============================================================================
def cleanup_generated_kernels(gen_dir: Optional[Path] = None) -> None:
"""Remove generated kernel directory if it exists."""
if gen_dir is None:
gen_dir = get_generated_kernels_dir()
if gen_dir.exists():
shutil.rmtree(gen_dir, ignore_errors=True)
log.info("Cleaned up generated kernels at %s", gen_dir)
# ============================================================================
# Tool Helpers
# ============================================================================
def find_hipcc() -> Optional[str]:
"""Find the hipcc compiler."""
import os
candidates = [
os.environ.get("HIPCC"),
"/opt/rocm/bin/hipcc",
shutil.which("hipcc"),
]
for path in candidates:
if path and os.path.isfile(path):
return path
return None