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147 lines
4.0 KiB
Python
Executable File
147 lines
4.0 KiB
Python
Executable File
#!/usr/bin/env python3
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# Copyright Advanced Micro Devices, Inc., or its affiliates.
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# SPDX-License-Identifier: MIT
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"""Utility to render the output of 'trace_memory'."""
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import argparse
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from pathlib import Path
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import numpy as np
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import pandas as pd
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from PIL import Image
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def crop_to_bbox(img):
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"""Crop `img` to smallest bounding box."""
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flat = np.any(img, axis=2)
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rows = np.any(flat, axis=1)
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cols = np.any(flat, axis=0)
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rmin, rmax = np.nonzero(rows)[0][[0, -1]]
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cmin, cmax = np.nonzero(cols)[0][[0, -1]]
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return img[rmin : rmax + 1, cmin : cmax + 1, :]
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def trace_to_png(
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image_file, trace, m, n, element_size=4, instruction_width=16, crop=True, theme="wg"
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):
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"""Visualize memory access pattern from output of 'trace_memory'.
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The matrix size is M x N elements; and addressing is column-major.
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Colouring is based on the `theme`:
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- "wg", colour based on workgroup-x (red), workgroup-y (blue), workitem (green)
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- "wf", colour based on lane (red) and wavefront (blue)
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"""
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wgx_max = max(1, trace["WorkgroupX"].max())
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wgy_max = max(1, trace["WorkgroupY"].max())
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wi_max = max(1, trace["Workitem"].max())
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# we assume traced matrix is column-major (row-index is fastest
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# moving), and therefore we align bytes with the row-index.
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img = np.zeros([m * element_size, n, 3], dtype=np.uint8, order="F")
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for _, row in trace.iterrows():
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address, wgx, wgy, wi = (
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row["Address"],
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row["WorkgroupX"],
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row["WorkgroupY"],
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row["Workitem"],
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)
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i, j = address % (m * element_size), address // (m * element_size)
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if theme == "wg":
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img[i : (i + instruction_width), j, 0] = int((wgx / wgx_max) * 255)
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img[i : (i + instruction_width), j, 1] = int((wi / wi_max) * 255)
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img[i : (i + instruction_width), j, 2] = int((wgy / wgy_max) * 255)
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elif theme == "wf":
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img[i : (i + instruction_width), j, 0] = int((wi // 64) * 64 + 63)
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img[i : (i + instruction_width), j, 1] = 0
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img[i : (i + instruction_width), j, 2] = int((wi % 64) * 4 + 3)
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else:
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raise ValueError(f"Invalid theme '{theme}'. Choices are 'wg' and 'wf'.")
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if crop:
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img = crop_to_bbox(img)
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with Image.fromarray(img) as png:
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png.save(image_file)
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print(f"Wrote {image_file}")
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def main():
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parser = argparse.ArgumentParser(
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description="Convert CSV trace from trace_memory to a PNG."
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)
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parser.add_argument("filename")
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parser.add_argument(
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"-m",
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"--m",
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dest="M",
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type=int,
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required=True,
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help="Matrix M size (in elements)",
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)
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parser.add_argument(
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"-n",
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"--n",
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dest="N",
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type=int,
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required=True,
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help="Matrix N size (in elements)",
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)
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parser.add_argument(
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"-s",
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"--element_size",
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type=int,
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default=2,
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help="Number of bytes per matrix element",
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)
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parser.add_argument(
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"-w",
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"--instruction_width",
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type=int,
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default=16,
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help="Number of bytes per load/store instruction",
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)
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parser.add_argument(
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"-c",
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"--crop",
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default=False,
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action="store_true",
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help="Crop image to smalled bounding-box.",
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)
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parser.add_argument(
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"-t", "--theme", type=str, default="wg", help="Colour theme: 'wg' or 'wf'."
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)
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args = parser.parse_args()
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trace_fname = Path(args.filename)
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if not trace_fname.exists():
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print(f"Trace file {trace_fname} not found.")
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return
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png_fname = trace_fname.with_suffix(".png")
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trace = pd.read_csv(str(trace_fname))
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trace_to_png(
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str(png_fname),
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trace,
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args.M,
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args.N,
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element_size=args.element_size,
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instruction_width=args.instruction_width,
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crop=args.crop,
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theme=args.theme,
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)
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if __name__ == "__main__":
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main()
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