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Yunsong Wang
2025-09-29 12:38:12 -07:00
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docs/best_practices.md
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@@ -127,16 +127,9 @@ Pass: Cold: 0.007819ms GPU, 0.013864ms CPU, 0.50s total GPU, 3.59s total wall, 6
| 63952x | 13.864 us | 432.95% | 7.819 us | 447.95% |
```
By default, NVBench runs benchmarks on all available GPUs unless specified otherwise. On multi-GPU systems, this can unnecessarily increase runtime and resource usage. To target a specific GPU, saving both time and resources, you can set the `CUDA_VISIBLE_DEVICES` environment variable. In our case, we target the **RTX8000**:
By default, NVBench executes benchmarks on all available GPUs unless instructed otherwise. On multi-GPU systems, this can lead to longer runtimes and higher resource usage. To focus on a specific GPU and optimize both time and resources, users can use the `-d` CLI option to select the target GPU. In our example, we target the **RTX8000**:
```bash
user@nvbench-test:~/nvbench/build/bin$ export CUDA_VISIBLE_DEVICES=0
```
Now, if we rerun:
```bash
user@nvbench-test:~/nvbench/build/bin$ ./sequence_bench
user@nvbench-test:~/nvbench/build/bin$ ./sequence_bench -d 0
# Devices
## [0] `Quadro RTX 8000`