Show HN: ChartGPU – WebGPU-powered charting library (1M points at 60fps)

Post by dapperdrake » Thu, Jan 22, 2026, 1:43 PM UTC

vlovich123 wrote: post #115

leeoniya wrote: post #104

uPlot maintainer here. this looks interesting, i'll do a deeper dive soon :) some notes from a very brief look at the 1M demo: - sampling has a risk of eliminating important peaks, uPlot does not do it, so for apples-to-apples perf comparison you have to turn that off. see https://github.com/leeoniya/uPlot/pull/1025 for more details on the drawbacks of LTTB - when doing nothing / idle, there is significant cpu being…

Is there any techniques using wavelet decomposition to decimate the high frequency component while retaining peaks? I feel like that's a more principled approach than sampling but I haven't seen any literature on it describing the specific techniques (unless the idea is fundamentally unsound which is not obvious to me).

Post by dapperdrake » Thu, Jan 22, 2026, 1:45 PM UTC

vlovich123 wrote: post #152

huntergemmer wrote: post #120

Earlier quoted context omitted.

Interesting idea - I haven't explored wavelet-based approaches but the intuition makes sense: decompose into frequency bands, keep the low-frequency trend, and selectively preserve high-frequency peaks that exceed some threshold. My concern would be computational cost for real-time/streaming use cases. LTTB is O(n) and pretty cache-friendly. Wavelet transforms are more expensive, though maybe a GPU compute shader cou…

I don't. I just remember watching a presentation on it and it always struck me that wavelets are an incredibly powerful and underutilized technique for data reduction while preserving quality in a quantifiable and mathematically justifiable way. I don't have any papers in mind, but I do think that the critique around visual shape vs signal reconstruction may not be accurate given that wavelets are starting to see a l…

Post by dapperdrake » Thu, Jan 22, 2026, 1:47 PM UTC

Bengalilol wrote: post #180

leeoniya wrote: post #104

uPlot maintainer here. this looks interesting, i'll do a deeper dive soon :) some notes from a very brief look at the 1M demo: - sampling has a risk of eliminating important peaks, uPlot does not do it, so for apples-to-apples perf comparison you have to turn that off. see https://github.com/leeoniya/uPlot/pull/1025 for more details on the drawbacks of LTTB - when doing nothing / idle, there is significant cpu being…

One small thing I noticed: when you zoom in or out (or change the time span), the y-axis stays the same instead of adapting to the visible data.

Post by dapperdrake » Thu, Jan 22, 2026, 1:49 PM UTC

akomtu wrote: post #127

MindSpunk wrote: post #118

Earlier quoted context omitted.

Drawing lots of single pixels with alpha blending is probably one of the least efficient ways to use the rasterizer though. A good compute shader implementation would be substantially faster.

At 1M points it hardly makes a difference. Besides, 1 point -> 1 pixel mapping is good enough for a demo, but in practice it will produce nasty aliasing artifacts because real datasets aren't aligned with pixel coordinates. So you have to draw each point as a 2x2 square at least with precise shading, and we are back to the rasterizer pipeline. Edit: what actually needs to be computed is the integral of the points dat…

Post by dapperdrake » Thu, Jan 22, 2026, 1:59 PM UTC

mikepurvis wrote: post #34

I've always been a bit skeptical of JS charting libs that want to bring the entire data to the client and do the rendering there, vs at least having the option to render image tiles on the server and then stream back tooltips and other interactive elements interactively. However, this is pretty great; there really aren't that many use cases that require more than a million points. You might finally unseat dygraphs as…