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zaremba-density-cuda
cahlen/zaremba-density-cuda
zaremba-density-cuda is a machine learning model from cahlen. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for kernels. The card lists the license as mit.
Enumerates all CF denominators <= N with partial quotients from digit set A using persistent-thread DFS + bitset marking.
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Public
Updated Apr 14, 2026
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At a glance
- Library
- kernels
- License
- mit
- Access
- Public
- Created
- Apr 14, 2026
- Updated
- Apr 14, 2026
- SHA
- de49a8e0
Datasets
Model card
From the Hugging Face model README
Zaremba Density Enumeration
Enumerates all CF denominators <= N with partial quotients from digit set A using persistent-thread DFS + bitset marking.
Usage
import torch
from kernels import get_kernel
kernel = get_kernel("cahlen/zaremba-density-cuda")
result = zaremba.count_representable(max_d=1000000, digits=torch.tensor([1,2,3]))
Compile (standalone)
nvcc -O3 -arch=sm_90 -o zaremba_density zaremba_density/zaremba_density_gpu.cu -lm
Results
All computation results are open:
- Website: bigcompute.science
- Datasets: huggingface.co/cahlen
- Source: github.com/cahlen/idontknow
Citation
@misc{humphreys2026bigcompute,
author = {Humphreys, Cahlen},
title = {bigcompute.science: GPU-Accelerated Computational Mathematics},
year = {2026},
url = {https://bigcompute.science}
}
Human-AI collaborative. Not peer-reviewed. All code and data open.
- Library
- kernels
- License
- mit
- Created
- Apr 14, 2026
- Updated
- Apr 14, 2026