현장 노트
하드웨어가 헤드라인을 장식하지만, 락인은 소프트웨어에서 발생한다. 여기의 한 플랫폼은 생긴 지 투표할 나이가 됐는데도 여전히 사람들이 구매하는 칩을 결정하고, 가장 최신 항목들은 생긴 지 2년도 안 됐지만 이미 에이전트 시대의 핵심 기반이 되고 있다.
이 세 가지부터 시작하세요
CU
CUDA
20년에 걸쳐 쌓은 라이브러리 — 기술 업계에서 가장 깊은 해자.
VL
vLLM
세계 토큰의 상당 부분을 처리하는 오픈 엔진.
MC
Model Context Protocol (MCP)
에이전트 시대의 범용 포트, 1년 만에 업계 전반에 채택됨.
Compute platforms & kernels
5
CU
CUDA
NVIDIA's programming platform — the deepest moat in the industry.
NC
NCCL
The collective-communications library every distributed training run calls.
RO
ROCm
AMD's open-source answer to CUDA — the gap that narrowed at last.
T(
Triton (OpenAI)
Python-level GPU kernels — the community's crowbar under the CUDA moat.
X/
XLA / OpenXLA
The compiler that makes TPUs programmable — now an open project.
학습 프레임워크
5
PY
PyTorch
The framework nearly every modern model is written in.
DE
DeepSpeed
Microsoft's scaling toolkit — ZeRO sharding made huge models trainable.
JAX
Composable function transforms — the framework Gemini is built with.
MC
Megatron-Core
NVIDIA's reference recipe for trillion-parameter training.
TensorFlow
The 2015 giant that industrialized deep learning — now in JAX's shadow.
JAX
Composable function transforms — the framework Gemini is built with.
MC
Megatron-Core
NVIDIA's reference recipe for trillion-parameter training.
TensorFlow
The 2015 giant that industrialized deep learning — now in JAX's shadow.
Inference & serving
6
VL
vLLM
The open-source serving engine that made GPU inference efficient.
OR
ONNX Runtime
The portable format for shipping models across hardware.
OL
Ollama
One command to run an open model locally.
SG
SGLang
The high-performance serving runtime born from RadixAttention research.
TL
TensorRT-LLM & Dynamo
NVIDIA's tuned inference stack — peak tokens from its own silicon.
LL
llama.cpp
The C++ project that put LLMs on laptops — and invented GGUF.
Orchestration & cluster management
3
Kubernetes
The cloud's operating system, retrofitted for GPUs.
RA
Ray
Distributed Python for the whole ML pipeline — Anyscale's engine.
SL
Slurm
The HPC batch scheduler most big training runs still queue through.
Libraries, tooling & the agent layer
4
MC
Model Context Protocol (MCP)
The open standard connecting AI models to tools and data — USB-C for agents.
HF
Hugging Face Transformers
The library that standardized how models are shared and loaded.
L&
LangChain & LangGraph
The scaffolding layer of the agent era.
W&
Weights & Biases
Experiment tracking for the training runs on this site — now CoreWeave-owned.