Day 20 - Symbolic Shapes: One Graph for Every Batch Size
2026-08-14
Day 19 - The Full Graph Break Machinery: Where It Splits, How It Reconnects
2026-08-12
Day 18 - PyCodegen: How Dynamo Writes New Bytecode Back to CPython
2026-08-10
Day 17 - OutputGraph: Gathering the Scattered Output Into One Graph
Day 16 - SideEffects: How Mutating Python Passes Through a Pure Graph
2026-08-09
Day 15 - Guards: When a Compiled Result Can Be Reused
2026-08-08
Day 14 - VariableTracker and Source: Every Python Value Through Dynamo's Eyes
2026-08-06
Day 13 - The Symbolic Interpreter InstructionTranslator: One Handler Per Instruction
2026-08-05
Day 12 - What TorchDynamo Intercepts: CPython's Frame Eval Hook
2026-08-04
Day 11 - The Four Stages of torch.compile: What Happens Inside One Line
2026-07-24
Day 10 - The Map Unfolded: torch.compile, TVM, XLA, and TensorRT
2026-07-19
Day 9 - Quantization: Shrink the Bytes Themselves
2026-07-18
Day 8 - Dynamic Shapes: When Sizes Stop Holding Still
2026-07-17
Day 7 - Auto-tuning: Let the Machine Find the Schedule
2026-07-16
Day 6 - Loop Scheduling: Same Math, Different Speed
2026-07-15
Day 5 - Fusion in Depth: Vertical, Horizontal, and the Boundary
2026-07-14
Day 4 - Where to Aim: Arithmetic Intensity and the Roofline
2026-07-13
Day 3 - The Four Core Optimizations
2026-07-12
Day 2 - IR, Multi-Level Lowering, and Codegen
2026-07-11
Day 1 - Why Do We Need an ML Compiler?
2026-07-10
Open Source Journey - Apache Airflow Committer
2025-10-18