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【Nvidia官方课程】CUDA入门课【中英字幕】

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2024-05-23 22:05:35

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【Nvidia官方课程】CUDA入门课【中英字幕】

高性能计算

加加的公开课小屋发消息

公开课、计算机、人文历史、数学、英语、医学、职业...｜中英字幕

【2024】【TinyML和高性能深度学习计算 6.5940】麻省理工学院—中英字幕

Lecture 1 - Introduction (MIT 6.5940, Fall 2024, Zoom Recording)

01:06:00

Lecture 2 - Basics of Neural Networks (MIT 6.5940, Fall 2024, Zoom recording)

51:25

Lecture 3 - Pruning and Sparsity Part I (MIT 6.5940, Fall 2024)

57:57

Lecture 4 - Pruning and Sparsity Part II (MIT 6.5940, Fall 2024, Zoom recording

01:09:20

Lecture 5 - Quantization Part I (MIT 6.5940, Fall 2024, Zoom recording)

01:06:32

Lecture 6 - Quantization Part II (MIT 6.5940, Fall 2024, Zoom recording)

01:08:37

Lecture 7 - Neural Architecture Search Part I (MIT 6.5940, Fall 2024, Zoom recor

01:06:28

Lecture 8 - Neural Architecture Search Part II(MIT 6.5940, Fall 2024, Zoom recor

01:16:18

Lecture 9 - Knowledge Distillation (MIT 6.5940, Fall 2024, Zoom recording)

58:30

Lecture 10 - MCUNet and TinyML (MIT 6.5940, Fall 2024, Zoom Recording)

01:07:02

Lecture 11 - TinyEngine (MIT 6.5940, Fall 2024, Zoom Recording)

01:11:43

Lecture 12 - Transformer and LLM (MIT 6.5940, Fall 2024, Zoom Recording)

01:17:23

Lecture 13 - LLM Deployment Techniques (MIT 6.5940, Fall 2024, Zo

01:16:43

Lecture 14 - LLM Post-Training (MIT 6.5940, Fall 2024, Zoom Recor

01:18:40

Lecture 15 - Long-Context LLM (MIT 6.5940, Fall 2024, Zoom Record

01:13:53

Lecture 16 - Vision Transformer (Zoom Recording) (MIT 6.5940, Fall 2024)

01:01:37

Lecture 17 - GAN, Video, Point Cloud (MIT 6.5940, Fall 2024)

01:10:24

Lecture 18 - Diffusion Models (Zoom Recording) (MIT 6.5940, Fall 2024)

01:11:24

Lecture 19 - Distributed Training Part 1 (Zoom Recording) (MIT 6.5940, Fall 2024

01:09:57

Lecture 20 - Distributed Training Part 2 (Zoom Recording) (MIT 6.5940, Fall 2024

59:15

Lecture 21 - On-device Training (Zoom Recording) (MIT 6.5940, Fall 2024)

01:05:12

Lecture 22： Quantum Machine Learning Part 1 (Zoom Recording) (MIT 6.5940, Fall 2

01:18:41

Lecture 23： Quantum Machine Learning Part 2 (Zoom Recording) (MIT 6.5940, Fall 2

01:13:11

2024 ｜ Introduction to Deep Compression Autoencoder

06:54

2024 ｜ Introduction to SVDQuant for 4-bit Diffusion Models

06:39

【TinyML和高性能深度学习计算 6.5940 2023】麻省理工学院—中英字幕

【GPU 计算 CMPS224 2021】贝鲁特美国大学—中英字幕

【CUDA Mode 2024】中英字幕

【CUDA 编程 elliotarledge】

【Nvidia官方课程】CUDA入门课【中英字幕】

【OpenCL编程 RayiYanuTara】

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【机器学习硬件与系统 ECE5545 2022】康奈尔大学—中英字幕

Cornell ECE 5545： ML HW & Systems. Lecture 0： Introduction [66HCPAcimGY]

01:09:19

Cornell ECE 5545： ML HW & Systems. Lecture 1： DNN Computations [ANg8jZ1qFRg]

01:15:59

Cornell ECE 5545： ML HW & Systems. Lecture 2： ML Hardware I (metrics and rooflin

01:11:16

Cornell ECE 5545： ML HW & Systems. Lecture 3： ML Hardware II (efficiency) [wAxGB

01:08:02

Cornell ECE 5545： ML HW & Systems. Lecture 4： ML Hardware III (case studies) [Mt

01:06:53

Cornell ECE 5545： ML HW & Systems. Lecture 5： Microarchitecture [Y-dFytEPSw8]

01:02:36

Cornell ECE 5545： ML HW & Systems. Lecture 6： TinyML [f6EvylheMmI]

58:31

Cornell ECE 5545： ML HW & Systems. Lecture 7： Quantization [Nvox0Q0ohlw]

01:09:20

Cornell ECE 5545： ML HW & Systems. Lecture 8： Pruning [CDHdn44fF2Y]

48:14

Cornell ECE 5545： Guest Lecture： Cerebras Sean Lie [5_qVob2Vwf8]

52:16

Cornell ECE 5545： ML HW & Systems. Lecture 9： Knowledge Distillation [62PFfavUcS

41:34

Cornell ECE 5545： ML HW & Systems. Lecture 10： Neural Architecture Search [_nkPW

01:03:13

Cornell ECE 5545： ML HW & Systems. Lecture 11： Kernel Computation [vQY61UPRob8]

54:27

Cornell ECE 5545： ML HW & Systems. Lecture 12： Mapping [YxIAVDnD8oo]

41:02

Cornell ECE 5545： Guest Lecture： TVM Thierry Moreau [RMdQRSGKMaI]

54:43

Cornell ECE 5545： ML HW & Systems. Lecture 13： Pre-and-Post-Processing in ML Sys

01:04:24

Cornell ECE 5545： ML HW & Systems. Lecture 14： Distributed Training [RK-N0RunWMA

56:30

Cornell ECE 5545： ML HW & Systems. Lecture 15： Federated Learning [G8YKB3TSA7I]

01:02:50

Cornell ECE 5545： ML HW & Systems. Lecture 16： Environmental⧸Ethical System Issu

01:05:17

Cornell ECE 5545： Guest Lecture： Databricks Jonathan Frankle [OLZrgth_mQA]

01:13:24

【深度学习硬件系统 2020】巴伊兰大学—中英字幕

【并行计算和科学机器学习 18.337 2021】麻省理工—中英字幕

p0 Parallel Computing and Scientific Machine Learning Course： Syllabus

43:01

p1 Getting Started with Julia (for Experienced Programmers)

34:11

p2 Optimizing Serial Code in Julia 1： Memory Models, Mutation, and Vectorization

01:20:57

p3 Optimizing Serial Code in Julia 2： Type inference, function specialization, a

01:25:00

p4 Introduction to Scientific Machine Learning 1： Deep Learning as Function Appr

28:22

p5 Introduction to Scientific Machine Learning 2： Physics-Informed Neural Networ

29:00

p6 How Loops Work 1： An Introduction to the Theory of Discrete Dynamical System

01:03:51

p7 How Loops Work 2： Computationally-Efficient Discrete Dynamics

48:37

p8 The Basics of Single Node Parallel Computing

01:32:54

p9 The Different Flavors of Parallelism： Parallel Programming Models

01:51:31

p10 Ordinary Differential Equations 1： Applications and Solution Characteristics

39:50

p11 Ordinary Differential Equations 2： Discretizations and Stability

01:31:35

p12 Forward-Mode Automatic Differentiation (AD) via High Dimensional Algebras

01:51:05

p13 Solving Stiff Ordinary Differential Equations

02:21:02

p14 Basic Parameter Estimation, Reverse-Mode AD, and Inverse Problems

02:16:20

p15 Differentiable Programming Part 1： Reverse-Mode AD Implementation

47:58

p16 Differentiable Programming Part 2： Adjoint Derivation for (Neural) ODEs and

01:36:11

p17 Partial Differential Equations (PDEs), Convolutions, and the Mathematics of

01:38:29

p18 Parallel Computing： From SIMD to SIMT

28:09

p19 GPU Programming in Julia

33:43

p20 Code Profiling and Optimization (in Julia)

01:15:44

p21 From Optimization to Probabilistic Programming

01:46:50

p22 Global Sensitivity Analysis

01:19:43

p23 Uncertainty Programming： Differentiable Programming Extended to Uncertainty

47:16

p24 Mixing Differential Equations and Neural Networks for Physics-Informed Learn

58:59

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【并行编程导论 CS194 2020】伯克利—中英字幕

【并行计算 CS267 2022】伯克利—中英字幕

【并行计算 CS267 2021】伯克利—中英字幕

【并行计算架构与编程 15-418 2016】卡耐基梅隆—中英字幕

【并发编程 cs431 2020】韩国科学技术院—中英字幕

【软件系统性能工程 6.172 2018】麻省理工学院—中英字幕

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