Coming from PyTorch, the first thing JAX does is offend you. You write a simple function with an if statement, wrap it in jax.jit, and call it. Instead of running, it throws a TracerBoolConversion...

The TPU has less public hardware documentation than a GPU. There is no vendor ISA manual, no die-level memory-model spec; you get peak FLOPs, HBM capacity, and a block diagram. But if you write JAX...

Here is a small function and the entire program XLA compiled it into: def simp(x): y = (x + 0.0) * 1.0 return jnp.transpose(jnp.transpose(y)) ENTRY %main (x: f32[3,3]) -> f32[3,3] { ...

If you train or serve models, XLA is probably compiling them, whether or not you have ever named it. It is the compiler behind JAX, behind TensorFlow, and — through PyTorch/XLA — behind much of PyT...

The first time I put torch.compile in front of an LLM inference server, it spent the better part of a minute compiling and handed back a 6% speedup. I nearly wrote the feature off. The next morning...

Triton is a compiler with a Python frontend. The @triton.jit decorator does not decorate a function. It parses the function’s AST, runs it through an MLIR pipeline, and emits a GPU binary. The Pyth...

When you compile a CUDA kernel, the final artifact is a cubin — a CUDA binary. It is a standard ELF64 file with NVIDIA-specific sections that encode everything the CUDA driver needs to load and lau...

A survey of code repository hosting in 2026 Most developers do not think about where their Git repository lives until something goes wrong. An account gets suspended. A DMCA notice takes down a pr...

A review and critical analysis of Niklaus Wirth’s foundational text Over the past decade, I have been thinking about how programming languages evolve and what survives the churn. Languages rise an...

A case study of the B200 pipeline model A note on methodology: Everything in this article is based on my analysis of microbenchmarks executed directly on B200 silicon. Nvidia does not publish i...