I write Python and PyTorch every day, and I care a lot about what happens underneath a
forwardpass.Model engines — attention kernels, fused operators, memory planning, and the scheduler that keeps the GPU busy.
Quantization — GPTQ, AWQ, SmoothQuant, W8A8 / INT4 / FP8, trading a little accuracy for a lot of memory and latency.
Deployment — serving with vLLM and TensorRT-LLM, continuous batching, then Docker and Kubernetes once it has to survive production traffic.
Python |
C++ |
Java |
Git |
PyTorch |
vLLM |
⭐️ From Fenlyin0420(mks)
