Главная
Study mode:
on
1
Introduction
2
Exascale Computing
3
US Exascale Computing
4
Quantum Computing
5
HPC architectures
6
Shared memory architectures
7
OpenMP
8
OpenMP Parallelization
9
Shared vs Distributed Models
10
Shared vs Distributed Memory
11
Shared Memory Programming Model
12
GPU Computing
13
GPU Architecture
14
Peak Performance
15
CPU vs GPU
16
GPU popularity
17
GPU programming
18
OpenCL
Description:
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore the cutting-edge world of exascale computing in this comprehensive lecture delivered by Dr. Meifeng Lin from Brookhaven National Laboratory. Delve into the intricacies of US exascale computing initiatives and gain insights into quantum computing advancements. Examine various high-performance computing (HPC) architectures, focusing on shared memory systems and the OpenMP programming model. Compare shared and distributed memory models, understanding their unique characteristics and applications. Discover the power of GPU computing, analyzing its architecture, peak performance, and growing popularity in comparison to traditional CPUs. Learn about GPU programming techniques and explore OpenCL as a framework for heterogeneous computing. This in-depth presentation covers essential topics in advanced computing, providing a solid foundation for understanding the future of computational power and its applications in scientific research and technological innovation.

Exascale Computing: From Shared Memory to GPU Architecture

Advanced Cyberinfrastructure Training at RPI
Add to list