Performance

Data Management and Performance

ChartGPT’s performance is closely tied to how it manages and loads data. Understanding these processes can help you optimize your experience with the tool.

Initial Data Loading

When you first use ChartGPT with a new instrument or time frame, the initial loading process may take some time. This is because:

1. ChartGPT needs to download historical data if it’s not already available locally.
2. ChartGPT processes this data to prepare it for analysis.

Note

The duration of the initial load depends on factors such as the amount of data required and your internet connection speed.

For more detailed information about data management, including how to ensure you have all necessary historical data, please refer to our Data Management guide:

Data Management Guide Learn how to manage historical data for optimal ChartGPT performance

Optimized Performance After Initial Load

Once ChartGPT has loaded, it’s designed to be light on system resources. We’ve implemented several optimizations to ensure smooth performance:

1. Sequential Loading: When you have multiple charts with ChartGPT, we load instances sequentially rather than simultaneously. This approach helps manage CPU load, although it may slightly increase overall loading time.

2. Tab-Based Loading: ChartGPT only loads the data for the currently displayed tab. This means:

   • You may experience a brief waiting period when switching to a new tab for the first time.
   • Once a tab has loaded, there will be no more waiting time when you return to it.

Tip

This tab-based loading system optimizes memory usage and improves overall performance, especially when working with multiple charts or tabs.

Performance Considerations

• Multiple Charts: While ChartGPT is designed to handle multiple instances, be aware that opening many charts simultaneously may increase initial loading times due to the sequential loading process.
• Switching Tabs: Expect a brief delay when switching to a new tab for the first time, as ChartGPT loads the necessary data for that specific analysis.
• System Resources: Although ChartGPT is optimized for efficiency, running multiple instances or working with large datasets may still impact system performance, especially on less powerful machines.

Note

Trading software, including ChartGPT, is resource-intensive due to real-time data processing and complex analyses. Unlike casual applications:

• It requires significant computational power, especially when handling multiple charts or large datasets.
• Performance can be impacted by the number of open charts, data volume, and analysis complexity.
• A high-performance computer is often necessary for smooth operation with multiple charts.

If you’re experiencing slowdowns, consider reducing the number of open charts or upgrading your hardware. Remember, efficient trading requires balancing analysis capabilities with system resources.