NSM Introduction to GPU Programming: L2: CUDA Memory

preview_player
Показать описание
  1. HPC Education
Рекомендации по теме
NSM Introduction to 1:32:42

NSM Introduction to GPU Programming: L1: CUDA Computation

NSM Introduction to 1:44:03

NSM Introduction to GPU Programming L3: CUDA Synchronization

NSM Introduction to 1:00:28

NSM Introduction to GPU Programming L5: C++ Programming for NVIDIA GPUs

NSM Introduction to 1:34:07

NSM Introduction to GPU Programming: L2: CUDA Memory

NSM Introduction to 1:31:09

NSM Introduction to GPU Programming L4: CUDA Topics

NSM Introduction to 0:51:44

NSM Introduction to GPU Programming L6: C++ Programming for Generic Accelerators

GPU Series: Introduction 1:07:23

GPU Series: Introduction to GPU and Accelerator Architectures

Intro to GPU: 0:28:14

Intro to GPU: 01 Why GPUs

Day 7: GPU 1:10:41

Day 7: GPU Architecture and CUDA Programming: Vishwesh Jatala

GPU L39: Thrust 0:53:25

GPU L39: Thrust Introduction

GPU Lecture 18.2: 0:20:47

GPU Lecture 18.2: Material Extraction in Unity (GPU Programming for Video Games, 2022-2023)

CPU-GPU Data 0:03:24

CPU-GPU Data

GPU L1: Introduction 0:51:05

GPU L1: Introduction

GPU Lecture 9: 0:13:59

GPU Lecture 9: Introduction to Textures (GPU Programming for Video Games, 2020-2023, Georgia Tech)

GPU programming with 0:14:48

GPU programming with OpenMP 5.0 on Google Colab (Basics)

[CUDA Programming Series] 0:10:54

[CUDA Programming Series] Setup CUDA in Google Colaboratory and an Intro Example

NSM HPC Workshop: 2:42:37

NSM HPC Workshop: OpenMP on GPU: Dr. Unnikrishnan C, IIT Palakkad

Lecture 07: Intro 0:32:28

Lecture 07: Intro to GPU architectures (Contd.)

IBM Training for 0:32:12

IBM Training for Bede - HPC Part 2 - GPU Programming

CUDA Programming Mastery 1:05:52

CUDA Programming Mastery | Day 2 (Part 1) with NVIDIA's Bharatkumar Sharma

PCI 2019: CUDA. 1:04:21

PCI 2019: CUDA. Part 2 (CUDA and OpenACC)

3. Threads, Synchronization, 0:08:41

3. Threads, Synchronization, and Memory

Introduction to High 4:17:55

Introduction to High Performance Computing: Applications and Systems -One day virtual workshop

Introduction to GPU 0:54:33

Introduction to GPU Architecture

Комментарии
Автор

At 50:00 timestamp, for coalescing in strided indexing, are you telling to launch a kernel with dkernel<<chunksize, no:of threads>>

I couldn't understand that part.

ajeethkumarm
Автор

So texture and constant memory can only be used to store instructions to be applied on transfered data from CPU to GPU memory and to store metas of the data available suring the time of GPU execution of instructions?

pronodbharatiya
Автор

L2 is shared among SMs so it means that if 1 sm needs say a particular chunk of L2, programmers have the liberty to asign that or is it so that the chunks are pre-fixed for each SMs and programmers can't asign values beyound that amont of space ?

pronodbharatiya
Автор

So the atomic instructions for L2 is stored in constant and or texture memory?

pronodbharatiya