# Technical Document Extraction: GPU Throughput Analysis ## Chart Overview The image presents a line chart comparing the computational throughput (in TFLOPs/s) of two GPU architectures (A100 and V100) across varying hidden sizes. The chart emphasizes performance scaling behavior relative to model complexity (hidden size). --- ## Axis Labels & Scales - **X-axis (Hidden Size)**: - Range: 0 to 32,768 - Increment: Logarithmic scale (powers of 2: 2048, 4096, 8192, ..., 32768) - **Y-axis (Throughput (TFLOPs/s))**: - Range: 0 to 150 - Increment: Linear scale (0, 50, 100, 150) --- ## Legend & Data Series - **Legend Position**: Top-right quadrant - **Color Coding**: - **Blue (A100)**: Higher-end GPU architecture - **Orange (V100)**: Legacy GPU architecture --- ## Key Trends & Data Points ### A100 (Blue Line) - **Trend**: Consistent upward slope with minimal variance - **Performance Progression**: - 2048: ~10 TFLOPs/s - 4096: ~20 TFLOPs/s - 8192: ~35 TFLOPs/s - 16384: ~70 TFLOPs/s - 32768: ~120 TFLOPs/s - **Error Bars**: Small vertical error bars (≤5% of throughput value) ### V100 (Orange Line) - **Trend**: Bimodal pattern with peak at mid-range hidden sizes - **Performance Progression**: - 2048: ~20 TFLOPs/s - 4096: ~30 TFLOPs/s - 8192: ~50 TFLOPs/s - 16384: ~60 TFLOPs/s (peak) - 32768: ~40 TFLOPs/s (decline) - **Error Bars**: Larger variance at higher hidden sizes (10-15% of throughput) --- ## Critical Observations 1. **Scaling Efficiency**: - A100 maintains linear scaling up to 32,768 hidden size - V100 exhibits diminishing returns beyond 16,384 hidden size 2. **Performance Gap**: - At 32,768 hidden size: - A100: 120 TFLOPs/s - V100: 40 TFLOPs/s - **Gap**: 3x performance difference 3. **Practical Implications**: - A100 enables larger model training (e.g., 32k hidden size models) - V100 becomes throughput-limited at mid-range model sizes --- ## Data Integrity Verification - **Color Consistency**: All blue data points match A100 legend; all orange match V100 - **Axis Alignment**: All data points fall within axis ranges - **Trend Logic**: Visual slopes match numerical progression (e.g., A100's 10→120 TFLOPs/s over 2048→32768 hidden size) --- ## Missing Elements - No secondary y-axis or annotations - No gridlines or reference markers - No temporal or experimental condition metadata --- ## Conclusion The chart demonstrates A100's superior scaling efficiency compared to V100, with throughput increasing proportionally to hidden size up to 32,768. V100's performance plateaus at mid-range model complexities, making it unsuitable for modern large-scale AI workloads.