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💭
getting my hands dirty
💭
getting my hands dirty

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titoatwork/README.md

Fourth-year CS undergrad. I work on making models cheaper to run and measurements harder to fake.

Mostly GPU kernels, low-precision inference, and evaluation harnesses that don't flatter their author.

Things that exist

qgemm-mx · C++ / CUDA
Block-scaled FP4 on GPUs with no native FP4. MXFP4 moves 1.88x fewer bytes per weight than FP8 and currently delivers roughly none of the speedup. Measuring where it goes.

lfx-firstanalysis · Python
Every published figure re-derives offline from a committed artifact, or the build fails. ./verify.sh, two dependencies, no API key.

COLIDE · Python / CUDA
CNN-BiLSTM intrusion detection over network flow, with the inference path moved to GPU.

riscv/riscv-unified-db · Ruby / YAML
12 patches merged, none rejected. Most of them closed a defect my own measurement had surfaced.

Earlier

Transformer inference on DGX H100 clusters. Fused Triton kernels at 3.5x PyTorch on a T4. A hedging agent that beats Black-Scholes mainly by trading less.

Currently reading about

Ternary quantization, wave quantization on small batch sizes, and why nobody agrees on what a benchmark measured.

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