Using a Raspberry Pi Cluster and SLURM for Parallel Backtest Research
Summary
The document describes building a small distributed computer cluster to run independent parameter variations for systematic trading backtests in parallel. It presents four Raspberry Pi computers connected by Ethernet, with SLURM as the workload manager, and explains how parallel jobs can shorten a parameter sweep compared with running simulations one after another. The example workflow is aimed at QSTrader research.
It compares this low power, compact setup with a desktop workstation or cloud compute, noting tradeoffs in processor performance, ARM compatibility, expansion, and shared resource scheduling. Hardware, networking, storage, power, and enclosure choices are described, along with assembly guidance. The article is primarily a build overview: it does not report measured backtest speedups, benchmark results, or a completed performance comparison. Its listed prices and components reflect the time of writing, and later articles in the series cover software configuration and strategy runs.
Key ideas
- Parameter sweeps can be parallelized because each tested parameter combination requires an independent backtest.
- SLURM schedules compute jobs and allocates cluster resources among users.
- A multi-node Raspberry Pi setup offers compact, low power compute for research experiments.
- ARM architecture and lower per-cost CPU performance are important tradeoffs against desktop systems.
- The article outlines hardware assembly but does not benchmark actual backtest speed.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.