Lanerra/DWARF
O(N) attention with a bounded inference KV cache. D4 Daubechies wavelet field + content-gated Q·K gather at dyadic offsets.
What's novel
O(N) attention with a bounded inference KV cache. D4 Daubechies wavelet field + content-gated Q·K gather at dyadic offsets.
Code Analysis
0 files read · 4 roundsAn experimental PyTorch project implementing Dyadic Sparse Q-K Gather (DSQG) attention mechanisms with CUDA kernels for O(1) memory inference in transformer models
Strengths
Highly novel architecture combining sparse attention with physics-inspired signal processing concepts; extensive CUDA kernel development showing deep implementation effort; clear versioning of DSQG variants indicating active research iteration
Weaknesses
Cannot verify code quality without reading actual source files; limited test coverage visible in file structure; heavy reliance on external dependencies (PyTorch, CUDA) with unclear error handling patterns
Score Breakdown
Signal breakdown
Innovation
Craft
Traction
Scope
Evidence
Commits
139
Contributors
1
Files
3502
Active weeks
3
Repository
Language
Python
Stars
3
Forks
0
License
Apache-2.0