ZenithTune

ZenithTune is a library that brings out the full potential of applications and tunes their performance to the zenith. By using the tuners provided by ZenithTune according to your needs, you can achieve the best performance while minimizing user coding.

Features

ZenithTune offers a variety of optimization methods aimed at improving overall application performance, including reducing execution time and optimizing command output. In contrast to common tools that primarily focus on improving model accuracy, it takes a more comprehensive approach.

It is also designed to run seamlessly in a wide variety of distributed environments. While many existing tools are designed for use on a single computer, ZenithTune supports performance improvements in distributed environments.

ZenithTune is a library specialized in improving application performance and has the ability to fine-tune hardware behavior such as CPU core allocation. This is a feature not found in other similar tools.

Finally, users can focus solely on optimization strategies. While many existing tools require users to write non-essential code outside of optimization themselves, ZenithTune is designed with the goal of minimizing the effort required from users.

Quick Start Guide

• Setup
• Basic Usage

Tuning Tips

ZenithTune has other useful features.

• Switch to Maximize
• Exclude Trial from Tuning
• Resume and Analyze from Existing Tuning Results
• Set Initial Values for Tuning Parameters
• Receive Metadata from Objective Function
• Tune Environment Variables
• Tune Scripts and Configuration Files

Advanced Tuning

You can expect further performance improvements by using more advanced tuning features.

• Parallel Execution of Tuning Scripts
• CPU Affinity Tuning
• Limiting Training Data Sample Count

Tuning for Distributed Learning Frameworks

With ZenithTune, you can easily tune applications using widely used distributed learning frameworks.

• DeepSpeed
• Megatron-LM
• MMEngine