腾讯微信-并行计算高级工程师
社招全职微信技术地点:深圳状态:招聘
任职要求
1.本科以上学历,计算机相关专业; 2.优秀的 C++ 编程经验,熟练掌握常用数据结构与算法,有一定的软件工程能力、良好的编程能力、逻辑思维和快速学习能力; 3.良好的团队合作意识,优秀的沟通和学习能力; 4.熟悉常见深度学习算法和视觉、LLM、图像视频生成 等模型,熟悉主流-ML平台框架(如 TensorFlow/PyTorch); 5.热爱技术,致力用技术为大量用户带来价值,为知名开源项目作出贡献或长期维护个人开源项目。 加分项 1.有以下一种或多种高性能计算、编译框架深入的研究和实践经验,或者基础扎实,有热心和毅力去学习钻研以下内容的,优先:; 2.A.精通现代 ARM/x64 体系结构与ISA/微架构以及 SIMD 指令集。能够从指令流水线/存储器层次结构 等级别量化分析性能瓶颈,并做出极致的优化; 3.B.精通 Nvidia/AMD/Adreno/Mali/PowerVR 等现代 GPU 体系结构与微架构;精通 CUDA/OpenCL/ROCm/Metal;熟悉现代 GPU 驱动的行为;能够从指令流水线/存储器层次结构/驱动调度 等级别量化分析性能瓶颈,并做出极致的优化。熟悉现代 GPU 渲染管线; 4.C.精通 Hexagon/Movidius 等 DSP 或 NPU 的体系结构与指令集,有 VLIW 指令集的优化经验,熟悉常用模拟器,能做到 cycle 级别的性能分析,熟悉 DMA/RPC 操作; 5.D.对常用计算/带宽密集型算子(如:GEMM/Conv/MultiheadAttention)实现做过面向 延迟/吞吐/功耗 的极致优化,性能超过开源或商业高性能计算库(如:TensorRT(LLM)/CoreML/MKL/OpenVINO 等); 6.E.有 AI 相关编译器(如:TVM/XLA/MLIR)开发经验;熟悉现代编译器框架(如:LLVM/gcc)。
工作职责
1.负责 AI 异构计算平台研发,打造 NLP/视觉/语音 等算法模型跨平台部署全流程优化,实现 AI 算力在微信生态(视频号、小程序、企业微信、微信读书、微信输入法等)的通用化和普惠; 2.分析 CNN、Transformer 等常用结构在微信实际业务场景中的性能瓶颈,在 CPU/GPU/NPU 上完成高性能实现与软硬件协同调优,实现性能极致的跨平台推理引擎; 3.引导算法团队设计性能/功耗兼顾的算法。
包括英文材料
学历+
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
数据结构+
https://www.youtube.com/watch?v=8hly31xKli0
In this course you will learn about algorithms and data structures, two of the fundamental topics in computer science.
https://www.youtube.com/watch?v=B31LgI4Y4DQ
Learn about data structures in this comprehensive course. We will be implementing these data structures in C or C++.
https://www.youtube.com/watch?v=CBYHwZcbD-s
Data Structures and Algorithms full course tutorial java
算法+
https://roadmap.sh/datastructures-and-algorithms
Step by step guide to learn Data Structures and Algorithms in 2025
https://www.hellointerview.com/learn/code
A visual guide to the most important patterns and approaches for the coding interview.
https://www.w3schools.com/dsa/
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
大模型+
https://www.youtube.com/watch?v=xZDB1naRUlk
You will build projects with LLMs that will enable you to create dynamic interfaces, interact with vast amounts of text data, and even empower LLMs with the capability to browse the internet for research papers.
https://www.youtube.com/watch?v=zjkBMFhNj_g
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.
PyTorch+
https://datawhalechina.github.io/thorough-pytorch/
PyTorch是利用深度学习进行数据科学研究的重要工具,在灵活性、可读性和性能上都具备相当的优势,近年来已成为学术界实现深度学习算法最常用的框架。
https://www.youtube.com/watch?v=V_xro1bcAuA
Learn PyTorch for deep learning in this comprehensive course for beginners. PyTorch is a machine learning framework written in Python.
CUDA+
https://developer.nvidia.com/blog/even-easier-introduction-cuda/
This post is a super simple introduction to CUDA, the popular parallel computing platform and programming model from NVIDIA.
https://www.youtube.com/watch?v=86FAWCzIe_4
Lean how to program with Nvidia CUDA and leverage GPUs for high-performance computing and deep learning.
OpenCL+
https://developer.nvidia.com/opencl
OpenCL™ (Open Computing Language) is a low-level API for heterogeneous computing that runs on CUDA-powered GPUs.
https://engineering.purdue.edu/~smidkiff/ece563/NVidiaGPUTeachingToolkit/Mod20OpenCL/3rd-Edition-AppendixA-intro-to-OpenCL.pdf
we will give a brief overview of OpenCL for CUDA programers.
[英文] Hands On OpenCL
https://handsonopencl.github.io/
An open source two-day lecture course for teaching and learning OpenCL
https://leonardoaraujosantos.gitbook.io/opencl/chapter1
Open Computing Language is a framework for writing programs that execute across heterogeneous platforms.
https://ulhpc-tutorials.readthedocs.io/en/latest/gpu/opencl/
OpenCL came as a standard for heterogeneous programming that enables a code to run in different platforms.
https://www.youtube.com/watch?v=4q9fPOI-x80
This presentation will show how to make use of the GPU from Java using OpenCL.
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.
RPC+
https://javaguide.cn/distributed-system/rpc/rpc-intro.html
为什么要 RPC ? 因为,两个不同的服务器上的服务提供的方法不在一个内存空间,所以,需要通过网络编程才能传递方法调用所需要的参数。并且,方法调用的结果也需要通过网络编程来接收。
https://www.youtube.com/watch?v=S2osKiqQG9s
This video is part of an 8-lecture series on distributed systems, given as part of the undergraduate computer science course at the University of Cambridge.
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.
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.
GCC+
https://gcc.gnu.org/onlinedocs/gcc-15.2.0/gcc/
This file documents the use of the GNU compilers.
https://www.seas.upenn.edu/~ese5320/fall2022/handouts/_downloads/788d972ffe62083c2f1e3f86b7c03f5d/gccintro.pdf
The purpose of this book is to explain the use of the GNU C and C++ compilers, gcc and g++.
https://www3.ntu.edu.sg/home/ehchua/programming/cpp/gcc_make.html
The original GNU C Compiler (GCC) is developed by Richard Stallman, the founder of the GNU Project.
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