Kunpeng AutoTuner Functions
Based on the 10 supported big data and database applications, the tool leverages built-in AI algorithms to obtain parameter settings that deliver superior performance, and then applies these settings in actual applications to improve performance.
When Kunpeng 920 series processors are used, Kunpeng register parameters are automatically tuned. The kernel version must be 4.19.90-2012.4.0.0053.oe1.aarch64 or 5.10.0-182.0.0.95.oe2203sp3.aarch64.
Figure 1 Automatic tuning process
Command Function
Automatically tunes application parameters to improve application performance metrics in different scenarios.
Syntax
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devkit kat [-h | --help] TASK [ARGS] |
An RPM package is used as an example.
- Complete the following settings before starting a task:
- Task parameters: parameter name, value range, and setting mode.
- Application scenario: application name, benchmark (if any), and performance metrics. Ensure that the application and performance test tool work properly.
- Automatic tuning is supported in database and big data scenarios.
- Databases: MySQL, openGauss, Vastbase, RocksDB, PostgreSQL, and Redis
- Big data: Hive, Spark, Flink, and Kafka
- Adjust the task parameters and application scenario based on the actual service scenario and the parameters to be tuned.
Example
Run the following command to view the information about the functions supported by the AutoTuner:
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devkit kat -h |
Command output:
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Usage: devkit kat [-h | --help] TASK [ARGS] The most commonly used devkit kat sub tasks are: help Get help information train Run the auto tuner train task template Run the auto tuner template task use Run the auto tuner use task See 'devkit kat TASK --help' for more information on a specific task. |
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Function |
Description |
|---|---|
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help |
Obtains help information. |
|
train |
Enables automatic tuning. |
|
template |
Generates a template file. |
|
use |
Uses the tuning result. |
Parent topic: Kunpeng AutoTuner