-
Notifications
You must be signed in to change notification settings - Fork 23
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Merge pull request #132 from Project-MONAI/perf-results
Added performance results file
- Loading branch information
Showing
2 changed files
with
155 additions
and
37 deletions.
There are no files selected for viewing
This file was deleted.
Oops, something went wrong.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,155 @@ | ||
| # Introduction # | ||
| This report documents the baseline and load tests against the AIDE. It shows comparisons of baseline and load tests across an AWS cloud environment (SIT) and performant on-premise Pre Prod environment. It also lists any conclusions and identifies any necessary follow-up actions. | ||
|
|
||
| # Environment Details # | ||
|
|
||
| ## AWS Cloud (SIT) Specification ## | ||
|
|
||
| | Node | Specification | | ||
| |-----------|----------------------------| | ||
| | SIT-Head1 | 4 vCPU, 16GB ram, 0 GPUs | | ||
| | SIT-Head2 | 4 vCPU, 16GB ram, 0 GPUs | | ||
| | SIT-DGX | 8 vCPUs, 32GB ram, 1 GPU's | | ||
|
|
||
| ## On-premise Pre Prod Environment ## | ||
|
|
||
| | Node | Specification | | ||
| |-----------|----------------------------| | ||
| | PreProd-Head1 | 48 vCPU, 252GB ram, 1 GPUs | | ||
| | PreProd-Head2 | 48 vCPU, 252GB ram, 0 GPUs | | ||
| | PreProd-Head3 | 48 vCPUs, 252GB ram, 1 GPU's | | ||
|
|
||
|
|
||
| # Data # | ||
| | Modality | Details | | ||
| | -------- | ------------------------- | | ||
| | RF | \- 1 slice<br>\- 1MB | | ||
| | US | \- 7 slices<br>\- 17MB | | ||
| | MR | \- 5 slices<br>\- 1MB | | ||
| | CT | \- 324 slices<br>\- 167MB | | ||
|
|
||
| # Applications # | ||
| The following dummy applications were published to stress the GPU and CPU. These were written using [stress](https://linux.die.net/man/1/stress) and [gpu-burn](https://github.com/wilicc/gpu-burn) | ||
|
|
||
| | Application Name | Specification | Modality | | ||
| | ---------------- | ------------------------------------------------------------------------ | --------- | | ||
| | Small | CPU: 2<br>GPU: Access to all<br>RAM: 1GB<br>Execution time: 10 seconds | RF | | ||
| | Medium | CPU: 8<br>GPU: Access to all<br>RAM: 10GB<br>Execution time: 30 seconds | US and MR | | ||
| | Large | CPU: 12<br>GPU: Access to all<br>RAM: 16GB<br>Execution time: 60 seconds | CT | | ||
|
|
||
| # Test Types # | ||
|
|
||
| ## Baseline ## | ||
| Single transactions to performance reference point which can be used as a basis for performance comparison | ||
|
|
||
| ## Load Average ## | ||
| Realistic expected usage levels to determine its response time, resource usage, and reliability using GSTT imaging throughput data in an average 1 hour period. | ||
|
|
||
| ## Load Peak ## | ||
| Realistic expected usage levels to determine its response time, resource usage, and reliability using GSTT imaging throughput data in an peak 1 hour period. | ||
|
|
||
| ## Stress ## | ||
| Uplift of peak load by 25% | ||
|
|
||
| # Throughput # | ||
|
|
||
| ## Peak 1 Hour ## | ||
|
|
||
| | Modality | Transactions | Model executions | | ||
| | ---------- | ------------ | ---------------- | | ||
| | X-ray | 120 | 120 | | ||
| | Ultrasound | 50 | 5 | | ||
| | CT | 30 | 21 | | ||
| | MRI | 25 | 17.5 | | ||
|
|
||
| ## Avg 1 Hour ## | ||
|
|
||
| | Modality | Transactions | Model executions | | ||
| | ---------- | ------------ | ---------------- | | ||
| | X-ray | 60 | 60 | | ||
| | Ultrasound | 28 | 2.8 | | ||
| | CT | 10 | 7 | | ||
| | MRI | 13 | 9.1 | | ||
|
|
||
| ## Stress 1 Hour ## | ||
|
|
||
| | Modality | Transactions | Model executions | | ||
| | ---------- | ------------ | ---------------- | | ||
| | X-ray | 180 | 180 | | ||
| | Ultrasound | 75 | 7.5 | | ||
| | CT | 45 | 31.5 | | ||
| | MRI | 37.5 | 26.25 | | ||
|
|
||
|
|
||
| # KPI and Measurements # | ||
|
|
||
| | KPI | Details | Query Params | | ||
| | ----------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------- | | ||
| | DICOM Payload Processed | How long it took between an association being made to Informatics Gateway, the instances being saved to MinIO and a WorkflowRequestEvent being generated | ServiceName: Monai.Deploy.InformaticsGateway AND "Payload took" | | ||
| | Task Dispatched | How long it took for the WorkflowRequestEvent to be consumed by the WorkflowManager, a workflow to be triggered and a TaskDispatchEvent to be generated | ServiceName: Monai.Deploy.WorkflowManager AND messageDescription: WorkflowRequestEvent AND durationMilliseconds > 0 | | ||
| | Task Created | How long it took for the TaskDispatchEvent to be consumed by the TaskManager and create a Task | ServiceName: Monai.Deploy.WorkflowManager.TaskManager AND messageType: TaskDispatchEvent AND durationMilliseconds > 0 | | ||
| | Task Update | How long it took for the TaskManager to publish a TaskUpdateEvent, the WorkflowManager to consume the event and update the WorkflowInstance | ServiceName: Monai.Deploy.WorkflowManager AND messageDescription: TaskUpdateEvent AND durationMilliseconds > 0 | | ||
| | Argo | How long it took for Argo to run the application requested. This includes time from the pod being scheduled and then a TaskCallbackEvent being published | Taken from Argo | | ||
| | End To End | Indicative time of the end to end processing of a workflow from dicom association to workflow completion. | Time from Task Update timestamp - (DICOM Payload Process timestamp - processed time) | | ||
|
|
||
| # Cloud Execution # | ||
|
|
||
| ## Details ## | ||
| Baseline tests were executed on SIT to validate the cloud environment to compare pre-prod tests against to understand the performance improvements based on specifications. | ||
|
|
||
| ## Results ## | ||
| ### Baseline ### | ||
| #### Description #### | ||
| Send through the same study 5 times, with a 90 second gap to get average metric for a known study, environment and MAP (liver-seg) set up. | ||
|
|
||
| #### Metrics #### | ||
| | | DICOM Payload Processed | DICOM Payload Processed | Task Dispatched | Task Dispatched | Task Created | Task Created | Task Update | Argo | Argo | Argo | End to End | | ||
| | -------- | ----------------------- | ----------------------- | --------------- | --------------- | ------------- | ------------ | ------------- | --------- | ------------- | --------- | ---------- | | ||
| | Modality | Average | Max | Average | Max | Average | Max | Average | Max | Average (min) | Max (min) | Indicative | | ||
| | CT | 01:11 | 01:24 | 14.5 | 20.4 | 2.3 | 2.9 | 0.8 | 1.7 | 01:57 | 02:04 | 03:21 | | ||
| | MR | 13.6 | 34.5 | 6.7 | 13.6 | 4.9 | 10 | 1 | 1.5 | 01:24 | 01:32 | 01:23 | | ||
| | US | 6.2 | 6.8 | 2.6 | 3.3 | 2.8 | 3.9 | 0.7 | 1.5 | 01:14 | 01:15 | 01:25 | | ||
| | RF | 5.8 | 9.5 | 11.3 | 23.6 | 30 | 107.7 | 1.1 | 2.9 | 01:06 | 01:37 | 00:58 | | ||
|
|
||
| # On-Premise Execution # | ||
|
|
||
| ## Details ## | ||
| Baseline, Load and Stress tests were executed on on-premise to understand the performance of MONAI-Deploy and AIDE on target production hardware and validate against throughput and metrics. | ||
|
|
||
| ## Results ## | ||
| ### Baseline 1 ### | ||
| #### Description #### | ||
| Send through the same study 5 times, with a 90 second gap to get average metric for a known study, environment and MAP (liver-seg) set up. | ||
|
|
||
| #### Metrics #### | ||
| | | DICOM Payload Processed | DICOM Payload Processed | Task Dispatched | Task Dispatched | Task Created | Task Created | Task Update | Task Update | Argo | Argo | End to End | | ||
| | ------------------------------------------------------------ | ----------------------- | ----------------------- | --------------- | --------------- | ------------- | ------------ | ------------- | ----------- | ------------- | --------- | ---------- | | ||
| | Modality | Average (sec) | Max (sec) | Average (sec) | Max (sec) | Average (sec) | Max (sec) | Average (sec) | Max (sec) | Average (min) | Max (min) | Indicative | | ||
| | CT ("{{ context.dicom.series.all('0008','0060') }} == 'CT'") | 34.4 | 36.2 | 11.6 | 12.5 | 1.1 | 1.2 | 0.4 | 0.9 | 01:54 | 02:07 | 02:30 | | ||
| | CT ("{{ context.dicom.series.any('0008','0060') }} == 'CT'") | 34.2 | 37.8 | 12.3 | 13.7 | 1.2 | 1.6 | 0.7 | 1 | 01:53 | 02:03 | N/A | | ||
| | MR | 1.1 | 1.4 | 0.7 | 1.1 | 1.2 | 1.5 | 0.6 | 0.8 | 01:06 | 01:10 | 01:18 | | ||
| | US | 1.7 | 2.3 | 1.1 | 1.3 | 0.9 | 1.6 | 0.6 | 1 | 01:10 | 01:17 | 01:07 | | ||
| | RF | 0.7 | 1.2 | 0.7 | 1.1 | 0.9 | 1.3 | 0.8 | 1 | 00:55 | 00:58 | 00:42 | | ||
| | CT (executing Small app & no conditional logic) | 34.9 | 37.9 | 10.6 | 10.8 | 2.08 | 6.3 | 0.9 | 1.9 | 01:06 | 01:13 | 01:47 | | ||
| | RF (no conditional logic) | 0.7 | 0.9 | 0.8 | 1.4 | 1.3 | 1.8 | 0.7 | 1.3 | 00:55 | 01:00 | 00:52 | | ||
|
|
||
| ### Baseline 2 ### | ||
| #### Description #### | ||
| Retest of the MIG following a change to how it was saving data to MinIO. | ||
|
|
||
| | | DICOM Payload Processed | DICOM Payload Processed | | ||
| | -------- | ----------------------- | ----------------------- | | ||
| | Modality | Average (sec) | Max (sec) | | ||
| | CT | 14 | 16.2 | | ||
|
|
||
| ### Load (Avg) ### | ||
| #### Description #### | ||
| #### Metrics #### | ||
|
|
||
| ### Load (Peak) ### | ||
| #### Description #### | ||
| #### Metrics #### | ||
|
|
||
| ### Stress ### | ||
| #### Description #### | ||
| #### Metrics #### |