cahlen/zaremba-density
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How to use cahlen/zaremba-density-cuda with Kernels:
# !pip install kernels
from kernels import get_kernel
kernel = get_kernel("cahlen/zaremba-density-cuda")Enumerates all CF denominators <= N with partial quotients from digit set A using persistent-thread DFS + bitset marking.
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]))
nvcc -O3 -arch=sm_90 -o zaremba_density zaremba_density/zaremba_density_gpu.cu -lm
All computation results are open:
@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 Not peer-reviewed.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.