小红书深度学习推理优化-AI编译器方向
社招全职3年以上引擎地点：北京 | 上海状态：招聘
工作描述
任职要求 1. 计算机及相关专业本科以上学历，3年以上AI编译器研发经验。 2. 精通C/C++，具备扎实的系统底层能力（内存、并发、网络）。 3. 熟悉XLA/LLVM/MLIR/TVM/IREE/Triton/Torch Inductor/TileLang等AI编译基础设施和相关工具链。 4. 熟悉TensorFlow Serving、TensorRT、OpenXLA、ONNX Runtime等推理后端。 5. 熟悉深度学习模型结构和计算图优化方法。 6. 有GPU/NPU集群建设与性能调优经验…
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包括英文材料
学历+
C+
https://www.freecodecamp.org/chinese/news/the-c-beginners-handbook/
本手册遵循二八定律。你将在 20% 的时间内学习 80% 的 C 编程语言。
https://www.youtube.com/watch?v=87SH2Cn0s9A
https://www.youtube.com/watch?v=KJgsSFOSQv0
This course will give you a full introduction into all of the core concepts in the C programming language.
https://www.youtube.com/watch?v=PaPN51Mm5qQ
In this complete C programming course, Dr. Charles Severance (aka Dr. Chuck) will help you understand computer architecture and low-level programming with the help of the classic C Programming language book written by Brian Kernighan and Dennis Ritchie.
C+++
https://www.learncpp.com/
LearnCpp.com is a free website devoted to teaching you how to program in modern C++.
https://www.youtube.com/watch?v=ZzaPdXTrSb8
LLVM+
https://llvm.org/docs/GettingStarted.html
Welcome to the LLVM project!
https://llvm.org/docs/tutorial/
This is the “Kaleidoscope” Language tutorial, showing how to implement a simple language using LLVM components in C++.
https://mcyoung.xyz/2023/08/01/llvm-ir/
“LLVM” is an umbrella name for a number of software components that can be used to build compilers.
https://www.youtube.com/watch?v=Lvc8qx8ukOI
This is the first lecture from the "Programming Language with LLVM" course where we build a full programming language similar to JavaScript from scratch, using LLVM compiler infrastructure.
Triton Inference Server+
https://docs.nvidia.com/deeplearning/triton-inference-server/user-guide/docs/index.html
Triton Inference Server is an open source inference serving software that streamlines AI inferencing.
TensorFlow+
https://www.youtube.com/watch?v=tpCFfeUEGs8
Ready to learn the fundamentals of TensorFlow and deep learning with Python? Well, you’ve come to the right place.
https://www.youtube.com/watch?v=ZUKz4125WNI
This part continues right where part one left off so get that Google Colab window open and get ready to write plenty more TensorFlow code.
TensorRT+
https://docs.nvidia.com/deeplearning/tensorrt/latest/getting-started/quick-start-guide.html
This TensorRT Quick Start Guide is a starting point for developers who want to try out the TensorRT SDK; specifically, it demonstrates how to quickly construct an application to run inference on a TensorRT engine.
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