The Software Frontier
Lorenzo Bradanini, Lorenzo TettamantiA newsletter to help you master software engineering, DevOps, data science, and emerging tech, empowering developers with useful tools.
| Platform |  | Pricing | Only free issues | Publishes | Twice weekly |
|---|---|---|---|---|---|
| Issues | 89 | Founded | a year ago | Last Issue | 14 days ago |
| Active | |||||
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How Systems Really Fail, Part I
Intro
There is a version of distributed systems that exists in textbooks, RFCs, and the architecture diagrams that get drawn during the first month of a new project.
In that version, failures are discrete events: a node dies, a networ...
We built the CUDA guide I wish I had three years ago
Intro
For the past few days we have been quiet here. Not because the newsletter slowed down, but because we were building something underneath it.
Today we are publishing what came out of that work: CUDA Mastery 2026, The Definitive En...
Mastering CUDA and High-Performance Computing, Part X
Where Part IX Left Us
Part IX ended with a provocation dressed as a summary. Training, we said, is a one-time cost. Inference is the workload that runs forever.
That sentence deserves to be interrogated before we accept it as a frame,...
Mastering CUDA and High-Performance Computing, Part IX
Where Part VIII Left Us
Part VIII ended at something close to a philosophical statement: the SMSP on a well-tuned Hopper GEMM kernel is a machine that does one thing. Everything else has been delegated.
That is true, and it is beautifu...
Mastering CUDA and High-Performance Computing, Part VIII
Where Part VII Left Us
Part VII ended with a promise and an architectural cliffhanger.
The promise: on Hopper, the compute-to-load instruction ratio in a GEMM inner loop approaches infinity from the SMSP’s perspective.
The cliffhange...
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Authors
The writers behind this newsletter.
Self-taught software engineer skilled in data science, software engineering, ML, and cryptography, focused on developing innovative solutions to complex challenges.
BSc Physics student at the University of Milan. Interested in Machine Learning | Computational Physics | Artificial Intelligence | Physics Simulations
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