From GPU-accelerated charts to Dashboard platform

Pasi Tuomainen — Thu, 04 Jun 2026 14:22:07 +0000

I've been developing GPU-accelerated charting technology from year 2007, and I'd like to share my path from biomedical software engineering to extreme dashboard platform builder.

GPU-accelerated charts for .NET and Windows

LightningChart .NET was a new breakthrough, that enabled building applications with super-fast charts for demanding industries, such as medical monitoring, telemetry systems, instrumentation, signal intelligence and for science in general. We pioneered the DirectX / Direct3D data visualization domain, and released the super-fast charts first for Windows Forms, and then for WPF. The first version was licensed to limited amount of customers in 2009.

Applying GPU-acceleration back in the day was very difficult - GPU drivers had differences and they same standards were interpreted differently by the GPU manufacturers, and we even had to develop GPU model-specific processing paths. The existing chart controls in the market were built on GDI and GDI+ rendering. Some limited 3D charts were in the market using OpenGL or Direct3D - nobody had GPU-accelerated 2D charting engine. Our in-house data viz engine enabled monitoring real-time data with over 1 Million data points coming each second, smoothly on screen, which was a giant leap of < 1000 data points the other charts provided.

A few years after, were able to visualize 1 Billion data points in real-time applications. And few years after, 1 Trillion data points in a specific cases, accumulated over time (not every second).

GPU-accelerated JavaScript charts

In 2017, our team started implementing GPU-accelerated charts for JavaScript, a pure cross-platform charting technology, which runs anywhere, with any operating systems or software development stack. LightningChart JS was released to market in 2019. We focused in extreme use cases, similar to what we did in .NET - data intensive real-time applications.

Python charts

While I can't say I'm a Python specialist, I was following our team when they implemented LightningChart for Python, enabling masses of data being visualized in real-time. It clearly exceeds the performance of free alternatives.

Dashboarding and data visualization platform

While working with the customers, time and effort needed to create an advanced dashboard or application, was not small, no matter how easy we made the examples and documentation. And in common, people don't code, or don't want to code (which is obviously not the case within Dev.to forum users!). Teams need easier approaches.

Dashtera platform was born, which has been just launched, which enables creating advanced dashboards without any coding, as it relies on pre-made database, data warehouse and streaming data connectors, file imports, and ability to create custom data connectors. Interactive dashboard editor enables adding 2D and 3D charts in the projects, and mapping the data from data sources to the charts. The dashboards show live data right away in the editor, and created projects can be shared to viewers with a URL link. Users can use the Dashtera Cloud platform directly in the Dashtera.com web site, or get an on-premises system for with dedicated database and total control of cyber security.

Here's just one dashboard I created with Dashtera. LightningChart is being used in space operations, but the Dashtera demo here, is using simulated data

Have you struggled with slow charts? Please reach out, if you have a project I can help with! Happy Dev!

DEV Community: Pasi Tuomainen

From GPU-accelerated charts to Dashboard platform

GPU-accelerated charts for .NET and Windows

GPU-accelerated JavaScript charts

Python charts

Dashboarding and data visualization platform