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Case studies with the measurement conditions attached. Where a number is missing, the work has not earned it yet.

4 projects · 2 with published numbers

active 2026

COLIDE

Custom CUDA kernels for a CNN-BiLSTM intrusion-detection model, with an on-device LLM that explains alerts without ever sitting in the detection path. A systems study — and an exercise in not overclaiming.

  • CUDA
  • HPC
  • IoT Security
  • LLM
  • Systems
Table 1 results
BoT-IoT macro-F1
0.9780 ± 0.0033
Sealed multi-seed test, n=5 (seeds 42–46)
Blocks 1/2/4 vs matched PyTorch
3.24×–6.55×
Operator-for-operator, RTX 3050
Block 3 kernel progression
7.55×–9.50×
Naive → FP16 half2 gate packing, five sessions
Alert dispatch
16.60 µs p99
Dispatch only — generation runs off the detection path
Sealed multi-seed test · full conditions in the case study