## Bar Chart Comparison: ForkKV vs Prefix Caching Performance Metrics
### Overview
The image presents three side-by-side bar charts comparing two caching systems: ForkKV (green) and Prefix Caching (blue). Each chart measures different performance metrics across the same two implementations.
### Components/Axes
1. **Legend**:
- Position: Top center
- Labels:
- ForkKV (ours) - Green
- Prefix Caching (SGLang) - Blue
2. **Chart (a)**:
- Title: Not explicitly labeled
- Y-axis: "Avg Per-Agent Mem Usage (GB)" (0-4 scale)
- X-axis: Implicit categories (ForkKV vs Prefix Caching)
3. **Chart (b)**:
- Title: Not explicitly labeled
- Y-axis: "Cache Hit Rate" (0-1 scale)
- X-axis: Implicit categories (ForkKV vs Prefix Caching)
4. **Chart (c)**:
- Title: Not explicitly labeled
- Y-axis: "Avg Decode Batch Size" (0-60 scale)
- X-axis: Implicit categories (ForkKV vs Prefix Caching)
### Detailed Analysis
**Chart (a) - Memory Usage**
- ForkKV: ~0.3 GB (bottom bar)
- Prefix Caching: ~4.0 GB (top bar)
- Spatial grounding: Blue bar occupies 95% of vertical space
**Chart (b) - Cache Hit Rate**
- ForkKV: ~0.9 (top bar)
- Prefix Caching: ~0.1 (bottom bar)
- Spatial grounding: Green bar occupies 90% of vertical space
**Chart (c) - Decode Batch Size**
- ForkKV: ~60 (top bar)
- Prefix Caching: ~5 (bottom bar)
- Spatial grounding: Green bar occupies 100% of vertical space
### Key Observations
1. **Memory Efficiency**: ForkKV uses 97% less memory than Prefix Caching (0.3 vs 4.0 GB)
2. **Cache Performance**: ForkKV achieves 9x higher cache hit rate (0.9 vs 0.1)
3. **Processing Capacity**: ForkKV handles 12x larger decode batches (60 vs 5)
4. **Consistent Advantage**: ForkKV outperforms in all three metrics
### Interpretation
The data demonstrates ForkKV's superior performance across all measured dimensions:
- **Memory Efficiency**: Critical for resource-constrained environments
- **Cache Effectiveness**: Indicates better data locality management
- **Batch Processing**: Suggests more efficient parallelization
The stark contrast in memory usage versus performance gains implies ForkKV optimizes resource allocation more effectively. The consistent dominance across metrics suggests architectural advantages in ForkKV's design, particularly in cache management and parallel processing capabilities. These findings would be valuable for systems requiring high throughput with limited memory resources.
