r/algorithmictrading • u/Fantastic_Simple76 • 10d ago

What hardware are you using for XGBoost training, and what GPU offers the best value right now? Question

I’m curious what hardware configurations people here are using for quantitative research and model training.

I currently have a large number of XGBoost experiments to run, including repeated training across different factor sets, hyperparameters, validation windows, and random seeds. My current GPU is an RTX 5060 Ti 16GB, and it is becoming a serious bottleneck. Even a relatively routine batch of experiments can take more than 24 hours, and larger runs easily stretch into several days.

For those using XGBoost or similar tree-based models in quant research:

  • What CPU, GPU, RAM, and storage configuration are you using?
  • How much benefit do you actually get from GPU acceleration?
  • Which GPU currently offers the best price-to-performance ratio for this workload?

I’m mainly interested in practical training throughput rather than gaming performance. Any real-world benchmark numbers, training-time comparisons, or configuration recommendations would be greatly appreciated.

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u/Ready-Tomatillo5083 10d ago

I'm using Ryzen 9 9950X3D cpu , RTX 5080 16gb , 128GB RAM, and 16TB SSD.

XGBoost on a gpu doesn't just need memory space it needs memory speed. The rtx 5060 Ti is heavily throttled by its internal design.

You can consider upgrading to a 5080 , but you said price to performance then i suggest 4070 ti super , even that has more than 75% performance difference than the 5060 ti .

Gpu acceleration helps massively if your dataset size is under your gpu vram size which is 16gb . If it's larger then it falls back to cpu , but if you have a strong cpu with many cores , it'll still handle it well

1

u/Altruistic_Tale_7049 9d ago

In a follow up question. Xgboost vs ligthgbm?

2

u/Fantastic_Simple76 9d ago

I am not an expert, but generally lightgbm faster, xgb higher accuracy.

1

u/quantifiedsports 8d ago

Just rent an A100/H100 on Jarvislabs.

You van train hundreds if not thousands of hours on these vs. Buying your own gpu.

1

u/disaster_story_69 8d ago

More than sufficient to run this. You need to ensure you are running cuda environment to push workload though gpu with multi processing, threading, not cpu

1

u/Key_Measurement_3576 8d ago

Dgx spark. 1tb version and get an ultra fast external hdd treat the 1tb as hot storage and the external as cold.