## Line Graph: Computation Time vs. Sequence Length for Flash Attention and MoBA Algorithms ### Overview The graph compares the computation time (in milliseconds) of two algorithms—Flash Attention and MoBA—across varying sequence lengths (32K to 1M). Flash Attention exhibits a steeply increasing trend, while MoBA shows a linear increase. Both algorithms start with negligible computation time at 32K sequence length. ### Components/Axes - **X-axis (Sequence Length)**: Labeled "Sequence Length" with markers at 32K, 128K, 256K, 512K, and 1M. - **Y-axis (Computation Time)**: Labeled "Computation Time (ms)" with a range from 0 to 800 ms. - **Legend**: Located in the top-left corner. - Flash Attention: Dashed light blue line with circular markers. - MoBA: Solid dark blue line with circular markers. ### Detailed Analysis - **Flash Attention**: - 32K: ~0 ms - 128K: ~10 ms - 256K: ~50 ms - 512K: ~230 ms - 1M: ~900 ms - **MoBA**: - 32K: ~0 ms - 128K: ~10 ms - 256K: ~20 ms - 512K: ~50 ms - 1M: ~140 ms ### Key Observations 1. **Exponential Growth for Flash Attention**: Computation time increases sharply after 512K, reaching ~900 ms at 1M. 2. **Linear Scaling for MoBA**: Time rises steadily, with a ~140 ms increase at 1M. 3. **Divergence at Scale**: The gap between the two algorithms widens significantly at 1M sequence length. 4. **Baseline Consistency**: Both algorithms start at ~0 ms for 32K sequence length. ### Interpretation - **Algorithmic Efficiency**: Flash Attention’s steep growth suggests higher computational complexity for longer sequences, potentially due to memory or parallelism constraints. MoBA’s linear scaling indicates better optimization for large-scale tasks. - **Practical Implications**: For applications requiring processing of very long sequences (e.g., 1M), MoBA is more efficient. Flash Attention may be preferable for shorter sequences where its initial performance is competitive. - **Uncertainty**: Values are approximate, with potential variability in real-world implementations (e.g., hardware differences, implementation optimizations). ### Spatial Grounding - Legend: Top-left corner, clearly associating colors/styles with algorithms. - Data Points: Aligned with x-axis markers, confirming sequence length correspondence. - Line Trends: Flash Attention’s dashed line slopes upward steeply; MoBA’s solid line has a gentle incline.