Update default Mongo credentials and documentation for GUI
Signed-off-by: colramos-amd <colramos@amd.com>
[ROCm/rocprofiler-compute commit: 45fb0b3a6f]
Šī revīzija ir iekļauta:
@@ -24,8 +24,8 @@ services:
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image: mongo
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restart: always
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environment:
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MONGO_INITDB_ROOT_USERNAME: amd
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MONGO_INITDB_ROOT_PASSWORD: amd123
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MONGO_INITDB_ROOT_USERNAME: temp
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MONGO_INITDB_ROOT_PASSWORD: temp123
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volumes:
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- grafana-mongo-db:/data/db
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ports:
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Bināro failu nav iespējams attēlot.
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Pēc Platums: | Augstums: | Izmērs: 47 KiB |
Bināro failu nav iespējams attēlot.
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Pēc Platums: | Augstums: | Izmērs: 113 KiB |
Bināro failu nav iespējams attēlot.
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Pēc Platums: | Augstums: | Izmērs: 272 KiB |
Bināro failu nav iespējams attēlot.
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Pēc Platums: | Augstums: | Izmērs: 57 KiB |
Bināro failu nav iespējams attēlot.
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Pēc Platums: | Augstums: | Izmērs: 253 KiB |
@@ -11,6 +11,7 @@
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installation
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getting_started
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performance_analysis
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standalone_gui_analyzer
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grafana_analyzer
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faq
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```
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@@ -157,10 +157,10 @@ use the provided Docker file to build the Grafana and MongoDB
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instance.
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### Install MongoDB Utils
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Omniperf uses [mongoimport](https://www.mongodb.com/docs/database-tools/mongoimport/) to upload data to Grafana's backend database
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Omniperf uses [mongoimport](https://www.mongodb.com/docs/database-tools/mongoimport/) to upload data to Grafana's backend database. Install for Ubuntu 20.04 is as follows:
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```bash
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$ wget https://fastdl.mongodb.org/tools/db/mongodb-database-tools-ubuntu2004-x86_64-100.6.1.deb
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$ sudo apt intall ./mongodb-database-tools-ubuntu2004-x86_64-100.6.1.deb
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$ sudo apt install ./mongodb-database-tools-ubuntu2004-x86_64-100.6.1.deb
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```
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> Find install for alternative distros [here](https://www.mongodb.com/download-center/database-tools/releases/archive)
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@@ -177,3 +177,38 @@ $ sudo docker volume create --driver local --opt type=none --opt device=/usr/loc
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$ sudo docker-compose build
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$ sudo docker-compose up -d
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```
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> Note that TCP ports for Grafana (4000) and MongoDB (27017) in the docker container are mapped to 14000 and 27018, respectively, on the host side.
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### Setup Grafana Instance
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Once you've launced your docker container you should be able to reach Grafana at **http://\<host-ip>:1400**. The default login credentials for the first-time Grafana setup are:
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- Username: **admin**
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- Password: **admin**
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MongoDB Datasource Configuration
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The MongoDB Datasource shall be configured prior to the first-time use. Navigate to Grafana's Configuration page (shown below) to add the **Omniperf Data** connection.
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Configure the following fields in the datasource:
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- HTTP URL: set to *http://localhost:3333*
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- MongoDB URL: set to *mongodb://temp:temp123@\<host-ip>:27018/admin?authSource=admin*
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- Database Name: set to *admin*
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After properly configuring these fields click **Save & Test** to make sure your connection is successful.
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> Note to avoid potential DNS issue, one may need to use the actual IP address for the host node in the MongoDB URL.
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Omniperf Dashboard Import
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From *Create* → *Import*, (as seen below) upload the dashboard file, `/dashboards/Omniperf_v{__VERSION__}_pub.json`, from the Omniperf tarball.
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Edit both the Dashboard Name and the Unique Identifier (UID) to uniquely identify the dashboard he/she will use. Click Import to finish the process.
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@@ -374,9 +374,9 @@ omniperf database <interaction type> [connection options]
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Examples:
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omniperf database --import -H pavii1 -u amd -t asw -w workloads/vcopy/mi200/
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omniperf database --import -H pavii1 -u temp -t asw -w workloads/vcopy/mi200/
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omniperf database --remove -H pavii1 -u amd -w omniperf_asw_sample_mi200
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omniperf database --remove -H pavii1 -u temp -w omniperf_asw_sample_mi200
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-------------------------------------------------------------------------------
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@@ -406,7 +406,7 @@ Connection Options:
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**omniperf import for vcopy:**
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```shell
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$ omniperf database --import -H pavii1 -u amd -t asw -w workloads/vcopy/mi200/
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$ omniperf database --import -H pavii1 -u temp -t asw -w workloads/vcopy/mi200/
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ROC Profiler: /usr/bin/rocprof
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--------
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@@ -0,0 +1,60 @@
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# Standalone GUI Analyzer
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```eval_rst
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.. toctree::
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:glob:
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:maxdepth: 4
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```
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## Features
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Omniperf's standalone GUI analyzer is a lightweight web page that can be generated straight from the command-line. This option is great for users who want immediate access to graphical results without the server-side overhead of the Omniperf's detailed [Grafana interface](https://amdresearch.github.io/omniperf/grafana_analyzer.html#)
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The standalone GUI analyzer is a simple Flask web application that uses port forwarding (DEFAULT: 8050) to allow users to view results from their web browser.
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> Because the standalone GUI analyzer uses port forwarding we reccomend users who profile on shared clusters **scp** their results to their personal workstation for analysis.
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## Useage
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To launch the standalone GUI, users will include the `--gui` flag in their analysis command.
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```{tip}
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To launch the web application on a port other than 8050 (default)
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use --gui <desired port>
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```
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```bash
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$ omniperf analyze -p workloads/vcopy/mi200/ --gui
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--------
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Analyze
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--------
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Dash is running on http://0.0.0.0:8050/
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* Serving Flask app 'omniperf_cli.omniperf_cli' (lazy loading)
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* Environment: production
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WARNING: This is a development server. Do not use it in a production deployment.
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Use a production WSGI server instead.
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* Debug mode: off
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* Running on all addresses (0.0.0.0)
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WARNING: This is a development server. Do not use it in a production deployment.
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* Running on http://127.0.0.1:8050
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* Running on http://10.228.32.139:8050 (Press CTRL+C to quit)
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```
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Users can then lauch their web browser of choice and go to http://localhost:8050/ (substituting port if overridden).
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When no filters are applied users will see 5 basic section derived from their application's profiling data:
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1. Memory Chart Analysis
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2. Empirical Roofline Analysis
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3. Top Stats (Top Kernal Statistics)
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4. System Info
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5. System Speed-of-Light
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To dive deeper, use the top drop down menus to isolate a particular kernel(s) or dispatch(s). You'll then see the webpage updates with metrics specific to the filter you've applied.
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Once you've applied a filter you'll also see several additional sections become availible with detailed metrics specific to that area of AMD hardware. These detailed sections mirror the data we display in Omniperf's [Grafana interface](https://amdresearch.github.io/omniperf/grafana_analyzer.html#)
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@@ -211,8 +211,8 @@ def parse(my_parser):
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\n\n-------------------------------------------------------------------------------
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\nExamples:
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\n\tomniperf database --import -H pavii1 -u amd -t asw -w workloads/vcopy/mi200/
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\n\tomniperf database --remove -H pavii1 -u amd -w omniperf_asw_sample_mi200
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\n\tomniperf database --import -H pavii1 -u temp -t asw -w workloads/vcopy/mi200/
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\n\tomniperf database --remove -H pavii1 -u temp -w omniperf_asw_sample_mi200
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\n-------------------------------------------------------------------------------\n
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""",
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prog="tool",
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@@ -35,7 +35,7 @@ if __name__ == "__main__":
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test = (
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"\n\ndef test_import_"
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+ workload_name
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+ "_mi100():\n with patch('sys.argv',['omniperf', 'database', '--import', '-H', 'localhost', '-u', 'amd', '-p', 'amd123', '-t', 'asw', '-w', '"
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+ "_mi100():\n with patch('sys.argv',['omniperf', 'database', '--import', '-H', 'localhost', '-u', 'temp', '-p', 'temp123', '-t', 'asw', '-w', '"
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+ workload
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+ "/mi100']): omniperf.main()"
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)
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@@ -65,7 +65,7 @@ if __name__ == "__main__":
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test = (
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"\n\ndef test_"
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+ workload_name
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+ "_mi100():\n with patch('sys.argv',['omniperf', 'database', '--import', '-H', 'localhost', '-u', '-p', 'amd123', 'amd', '-t', 'asw', '-w', '"
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+ "_mi100():\n with patch('sys.argv',['omniperf', 'database', '--import', '-H', 'localhost', '-u', 'temp', '-p', 'temp123', '-t', 'asw', '-w', '"
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+ workload
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+ "/mi100']): omniperf.main()"
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)
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