This demonstration shows how Transwarp GPU-Native Cognitive Database uses GPU acceleration to power quantitative analysis in Amazon QuickSight.

We evaluate a Bitcoin High-Frequency Trading (BTC HFT) strategy—one of the most demanding and speed-critical scenarios in quantitative trading. As a GPU-Native Cognitive Database designed for AI Agents, Cognitive Database handles the underlying data querying and computation, scanning, extracting, and aggregating 25,000 steps of backtest data in milliseconds.

Key highlights:

1、GPU-Native Performance: The end-to-end Cognitive Database pipeline completes in 0.626 seconds, including just 0.143 seconds to transfer data to PyTorch tensors；

2、Days-to-Minutes Backtesting: GPU acceleration delivers 12.2× to 5,881× speedups across quantitative workloads, reducing backtest cycles from days to minutes；

3、Seamless BI Integration: Cognitive Database connects with Amazon QuickSight, Power BI, Tableau, and other mainstream BI tools, bringing GPU-accelerated data processing into existing analytics workflows.