## Bar Chart: Intermittent Fault Activation Across Training Steps ### Overview The top chart visualizes fault activation patterns during training steps for three fault types (r=1.0, r=0.7, r=0.15). Each fault type is represented by horizontal bars segmented into red (corruption) and gray (no corruption), with a legend clarifying fault permanence. ### Components/Axes - **Y-Axis (Fault Type)**: - Labels: `r = 1.0`, `r = 0.7`, `r = 0.15` - Legend: - Red: Corruption (Permanent faults for r=1.0; Intermittent for r=0.7/0.15) - Gray: No corruption - **X-Axis (Training Step)**: - Markers: `0`, `N/4`, `N/2`, `3N/4`, `N` - Scale: Discrete intervals representing training progress. ### Detailed Analysis - **r = 1.0 (Permanent Faults)**: - Entire bar is red, indicating continuous corruption across all training steps. - **r = 0.7 (Intermittent Faults)**: - Segments: Red (corruption) and gray (no corruption) alternate. - Example: At `N/2`, ~25% of the bar is gray (no corruption). - **r = 0.15 (Intermittent Faults)**: - Segments: Red dominates early steps (`0`, `N/4`), with increasing gray segments later (`N/2`, `3N/4`, `N`). ### Key Observations - Higher `r` values correlate with greater persistent corruption. - Lower `r` values show intermittent fault activation, with corruption decreasing as training progresses. ### Interpretation The chart demonstrates that fault permanence (`r=1.0`) leads to unmitigated corruption, while lower `r` values allow partial recovery during training. This suggests adaptive training mechanisms may reduce intermittent faults over time. --- ## Line Graph: Fault PDF vs. Injection Rate ### Overview The bottom graph plots fault probability density function (PDF) against injection rate (`r`), with shaded regions indicating defect categories. ### Components/Axes - **Y-Axis (Fault PDF f(r))**: - Range: 0.0 to 3.5 - **X-Axis (Injection Rate r)**: - Range: 0.0 to 1.0 - **Legend**: - Blue line: Fault PDF curve - Shaded regions: - Green: Latent/Early-Life Defects - Yellow: Marginal Defects - Pink: Silicon Aging Related Defects - Dark pink: Severe Aging ### Detailed Analysis - **Fault PDF Curve**: - Peaks at ~0.2 injection rate (~3.0 PDF value). - Declines sharply as `r` increases beyond 0.4. - **Shaded Regions**: - **Green (Latent/Early-Life Defects)**: Dominates low `r` (0.0–0.4). - **Yellow (Marginal Defects)**: Overlaps with green at mid `r` (0.4–0.6). - **Pink (Silicon Aging)**: Emerges at `r > 0.6`. - **Dark Pink (Severe Aging)**: Minimal contribution (<0.8 `r`). ### Key Observations - Highest fault probability occurs at low injection rates (`r ≈ 0.2`). - Severe aging defects are negligible except at very high `r` (>0.8). ### Interpretation The data implies that low injection rates exacerbate early-life defects, while higher rates shift failure modes toward silicon aging. This aligns with semiconductor reliability models where early stress dominates at low operational thresholds. --- ## Cross-Referenced Insights 1. **Top Chart + Bottom Graph**: - Permanent faults (`r=1.0`) in the top chart may correspond to "Severe Aging" in the bottom graph, as both represent unmitigated failure modes. - Intermittent faults (`r=0.7/0.15`) align with "Marginal Defects" and "Silicon Aging," suggesting partial recovery mechanisms. 2. **Training vs. Operational Context**: - The top chart focuses on training-phase fault dynamics, while the bottom graph models operational defect distributions. ## Final Notes - All legend colors match chart elements (e.g., red = corruption in both charts). - No textual data in non-English languages detected. - Spatial grounding: Legends are positioned at the bottom-left (top chart) and right (bottom graph), ensuring clarity without obscuring data.