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DGX-A100_GPU-Operator_testing/blogpost.md: use absolute links
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kpouget committed Jun 14, 2022
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14 changes: 7 additions & 7 deletions DGX-A100_GPU-Operator_testing/blogpost.md
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Expand Up @@ -402,7 +402,7 @@ Example of configuration:

### Requesting one GPUs per Pod in 8 Pods

- [Test artifacts](results/mlperf/dgx-test/20211209/gpu=7g.40gb_1gpu_x_8pod/run_20211209_1519.4e94)
- [Test artifacts](https://github.com/openshift-psap/blog-artifacts/blob/1f368b17f180c9ceaa5660eb32acb57256f4df0b/DGX-A100_GPU-Operator_testing/results/mlperf/dgx-test/20211209/gpu=7g.40gb_1gpu_x_8pod/run_20211209_1519.4e94)
- Job parallelism: `8`
- Container resources:
```
Expand All @@ -420,7 +420,7 @@ GPU 0: NVIDIA A100-SXM4-40GB (UUID: GPU-55b69871-247e-9b99-a60a-7daca59a4108)

### Requesting all the GPUs in one Pod

- [Test artifacts](results/mlperf/dgx-test/20211209/gpu=7g.40gb_8gpu_x_1pod/run_20211209_1519.57ea)
- [Test artifacts](https://github.com/openshift-psap/blog-artifacts/blob/1f368b17f180c9ceaa5660eb32acb57256f4df0b/DGX-A100_GPU-Operator_testing/results/mlperf/dgx-test/20211209/gpu=7g.40gb_8gpu_x_1pod/run_20211209_1519.57ea)
- Job parallelism: `1`
- Container resources:
```
Expand Down Expand Up @@ -458,7 +458,7 @@ that there are not enough GPU resources available to schedule the
second Pod, so it delays it until the resources are released. Hence,
the execution of the two Pods is sequential.

- [Test artifacts](results/mlperf/dgx-test/20211209/gpu=7g.40gb_5gpu_x_2pod/run_20211209_1519.e78a)
- [Test artifacts](https://github.com/openshift-psap/blog-artifacts/blob/1f368b17f180c9ceaa5660eb32acb57256f4df0b/DGX-A100_GPU-Operator_testing/results/mlperf/dgx-test/20211209/gpu=7g.40gb_5gpu_x_2pod/run_20211209_1519.e78a)
- Job parallelism: `2`
- Container resources:
```
Expand Down Expand Up @@ -514,7 +514,7 @@ Example of configuration:

### Requesting 1 `MIG-2g.10gb` GPUs in 24 Pods

- [Test artifacts](results/mlperf/dgx-test/20211209/gpu=2g.10gb_1gpu_x_24pod/run_20211210_1552.e1c8/)
- [Test artifacts](https://github.com/openshift-psap/blog-artifacts/blob/1f368b17f180c9ceaa5660eb32acb57256f4df0b/DGX-A100_GPU-Operator_testing/results/mlperf/dgx-test/20211209/gpu=2g.10gb_1gpu_x_24pod/run_20211210_1552.e1c8/)
- MIG configuration: `nvidia.com/mig.config=all-2g.10gb`
- Job parallelism: `24`
- Container resources:
Expand All @@ -533,7 +533,7 @@ GPU 0: NVIDIA A100-SXM4-40GB (UUID: GPU-55b69871-247e-9b99-a60a-7daca59a4108)

### Requesting 24 `MIG-2g.10gb` GPUs in 1 Pod

- [Test artifacts](results/mlperf/dgx-test/20211209/gpu=2g.10gb_24gpu_x_1pod/run_20211210_1552.517e)
- [Test artifacts](https://github.com/openshift-psap/blog-artifacts/blob/1f368b17f180c9ceaa5660eb32acb57256f4df0b/DGX-A100_GPU-Operator_testing/results/mlperf/dgx-test/20211209/gpu=2g.10gb_24gpu_x_1pod/run_20211210_1552.517e)
- MIG configuration: `nvidia.com/mig.config=all-2g.10gb`
- Job parallelism: `1`
- Container resources:
Expand Down Expand Up @@ -565,7 +565,7 @@ This test case creates two `Jobs` requesting 4 Pods. One of the `Job`
requests resources of type `nvidia.com/mig-3g.20gb` and the second one
requests resources of type `nvidia.com/mig-2g.10gb`.

- [Test artifacts](results/mlperf/dgx-test/20211209/gpu=2g.10gb,3g.20gb_1gpu_x_4pod/run_20211209_1519.334c)
- [Test artifacts](https://github.com/openshift-psap/blog-artifacts/blob/1f368b17f180c9ceaa5660eb32acb57256f4df0b/DGX-A100_GPU-Operator_testing/results/mlperf/dgx-test/20211209/gpu=2g.10gb,3g.20gb_1gpu_x_4pod/run_20211209_1519.334c)
- MIG configuration: `nvidia.com/mig.config=all-balanced`
- Job parallelism: `4`
- Container resources:
Expand Down Expand Up @@ -661,7 +661,7 @@ And to validate the proper slicing of all the GPUs, we launched a Pod
requesting 0 GPUs, meaning that we got access to all the GPUs of the
node:

- [Test artifacts](results/mlperf/dgx-test/20211209/gpu=2g.10gb_0gpu_x_1pod/run_20211217_1222.1e2f/)
- [Test artifacts](https://github.com/openshift-psap/blog-artifacts/blob/1f368b17f180c9ceaa5660eb32acb57256f4df0b/DGX-A100_GPU-Operator_testing/results/mlperf/dgx-test/20211209/gpu=2g.10gb_0gpu_x_1pod/run_20211217_1222.1e2f/)
- MIG configuration: `nvidia.com/mig.config=custom-config`
- Job parallelism: `1`
- Container resources:
Expand Down

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