## Bar Chart: Unused GPU Memory by Task and Configuration
### Overview
The chart compares unused GPU memory (%) across 10 computational tasks under four GPU configurations: 7x MIG 1g (green), 7x MPS 13% (green with 13% label), 7x timeslice (blue), and a reference configuration of 1 task using the full GPU (striped blue). The y-axis ranges from 0% to 100% unused memory.
### Components/Axes
- **X-axis**: Task names (e.g., `autodock_2vaa`, `qiskit_qv_30q`).
- **Y-axis**: Unused GPU memory (%) in 20% increments.
- **Legend**:
- Green: 7x MIG 1g
- Green with 13%: 7x MPS 13%
- Blue: 7x timeslice
- Striped blue: ref: 1 task, full GPU
### Detailed Analysis
1. **autodock_2vaa**:
- All configurations show ~95-100% unused memory.
- Striped blue (reference) slightly higher (~98%) than others.
2. **autodock_3er5**:
- Similar to `autodock_2vaa`, with ~95-100% unused memory.
3. **hotspot**:
- 7x MIG 1g and 7x MPS 13%: ~40% unused.
- 7x timeslice: ~35%.
- Reference: ~90%.
4. **lammps_reaxff**:
- 7x MIG 1g and 7x MPS 13%: ~40%.
- 7x timeslice: ~35%.
- Reference: ~90%.
5. **llama3**:
- 7x MIG 1g and 7x MPS 13%: ~40%.
- 7x timeslice: ~35%.
- Reference: ~90%.
6. **llmc_shakespeare**:
- 7x MIG 1g and 7x MPS 13%: ~40%.
- 7x timeslice: ~35%.
- Reference: ~90%.
7. **llmc_timestories_bf16**:
- 7x MIG 1g and 7x MPS 13%: ~65%.
- 7x timeslice: ~60%.
- Reference: ~90%.
8. **nekrs_turbpipeperiodic**:
- 7x MIG 1g and 7x MPS 13%: ~50%.
- 7x timeslice: ~45%.
- Reference: ~90%.
9. **faiss_sift1m**:
- 7x MIG 1g and 7x MPS 13%: ~80%.
- 7x timeslice: ~75%.
- Reference: ~90%.
10. **qiskit_qv_30q**:
- 7x MIG 1g and 7x MPS 13%: ~20%.
- 7x timeslice: ~15%.
- Reference: ~85%.
### Key Observations
- **High Unused Memory**: Tasks like `autodock_*` and `faiss_sift1m` consistently show >80% unused memory across configurations, suggesting low GPU utilization.
- **Low Unused Memory**: `qiskit_qv_30q` has the lowest unused memory (~15-20%), indicating high GPU utilization.
- **Reference Dominance**: The striped blue (full GPU) configuration consistently shows the highest unused memory (~85-98%), implying inefficiency in resource partitioning for most tasks.
- **MPS 13% Underperformance**: The 7x MPS 13% configuration (green with 13%) often performs worse than 7x MIG 1g and 7x timeslice, suggesting potential overhead or suboptimal memory allocation.
### Interpretation
The data highlights trade-offs between GPU partitioning strategies:
1. **MIG 1g vs. Timeslice**: Both configurations generally outperform MPS 13% and the full GPU reference, suggesting that partitioning into smaller instances (MIG 1g or timeslice) improves memory efficiency for most tasks.
2. **Task-Specific Behavior**:
- Memory-intensive tasks (`autodock_*`, `faiss_sift1m`) benefit less from partitioning, as they leave significant memory unused regardless of configuration.
- Compute-heavy tasks (`qiskit_qv_30q`) show minimal unused memory, indicating near-full utilization across all setups.
3. **MPS 13% Inefficiency**: The 7x MPS 13% configuration underperforms in most cases, possibly due to fixed memory allocation constraints or overhead from managing multiple partitions.
4. **Reference as Baseline**: The full GPU configuration (striped blue) serves as a baseline for maximum unused memory, emphasizing that partitioning reduces waste but may not always optimize performance.
This analysis underscores the importance of aligning GPU configuration with task requirements to balance memory efficiency and computational throughput.
