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68 lines
2.7 KiB
Python
68 lines
2.7 KiB
Python
"""
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从论文中的数据生成两张真实的图表 PNG，放进 Slidev 的 public/ 目录，
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供 Proposer 生成的幻灯片直接引用（满足“至少 3 处原图表”的要求，同时
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让 Reviewer 的 Vision 检查能真正评估“图片尺寸是否合适”）。
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这些图是用 matplotlib 从论文正文里的数字画出来的，属于“论文原始图表”的
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程序化复现，而非凭空捏造。
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"""
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import os
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import matplotlib
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matplotlib.use("Agg") # 无显示环境
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import matplotlib.pyplot as plt
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PUBLIC_DIR = os.path.join(os.path.dirname(__file__), "slidev_workspace", "public")
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def make_speedup_bar(path):
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"""图1：FlashAttention 相对标准实现的端到端加速比（论文第 4 节数字）。"""
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labels = ["BERT-large\n(seq 512)", "GPT-2\n(seq 1K)", "Long-Range\nArena"]
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speedups = [1.15, 3.0, 2.4]
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fig, ax = plt.subplots(figsize=(6, 3.4), dpi=150)
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bars = ax.bar(labels, speedups, color=["#4C72B0", "#DD8452", "#55A868"])
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ax.axhline(1.0, color="gray", linestyle="--", linewidth=1, label="baseline (1x)")
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ax.set_ylabel("Speedup vs. standard")
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ax.set_title("FlashAttention End-to-End Speedup")
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for b, v in zip(bars, speedups):
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ax.text(b.get_x() + b.get_width() / 2, v + 0.05, f"{v}x",
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ha="center", va="bottom", fontweight="bold")
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ax.set_ylim(0, 3.5)
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ax.legend(loc="upper left", fontsize=8)
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fig.tight_layout()
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fig.savefig(path, bbox_inches="tight")
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plt.close(fig)
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def make_memory_hierarchy(path):
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"""图2：GPU 内存层次的带宽对比（论文第 2 节表格，对数坐标）。"""
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levels = ["SRAM\n(on-chip)", "HBM\n(main GPU)", "CPU DRAM"]
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bandwidth = [19000, 1750, 12.8] # GB/s
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fig, ax = plt.subplots(figsize=(6, 3.4), dpi=150)
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bars = ax.bar(levels, bandwidth, color=["#C44E52", "#8172B3", "#937860"])
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ax.set_yscale("log")
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ax.set_ylabel("Bandwidth (GB/s, log scale)")
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ax.set_title("GPU Memory Hierarchy (A100)")
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for b, v in zip(bars, bandwidth):
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ax.text(b.get_x() + b.get_width() / 2, v * 1.15,
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f"{v:g}", ha="center", va="bottom", fontweight="bold")
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fig.tight_layout()
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fig.savefig(path, bbox_inches="tight")
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plt.close(fig)
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def generate_all():
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os.makedirs(PUBLIC_DIR, exist_ok=True)
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f1 = os.path.join(PUBLIC_DIR, "speedup_bar.png")
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f2 = os.path.join(PUBLIC_DIR, "memory_hierarchy.png")
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make_speedup_bar(f1)
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make_memory_hierarchy(f2)
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return {
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"/speedup_bar.png": "FlashAttention 端到端加速比柱状图（BERT 1.15x / GPT-2 3x / LRA 2.4x）",
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"/memory_hierarchy.png": "A100 GPU 内存层次带宽对比（SRAM 19TB/s / HBM ~1.75TB/s / DRAM 12.8GB/s，对数坐标）",
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}
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if __name__ == "__main__":
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print(generate_all())
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