Cloud
3 minute read
Part III Cloud {#sec:534-week3}
A. Summary of Course
B. Defining Clouds I
In this lecture we discuss the basic definition of cloud and two very simple examples of why virtualization is important.
In this lecture we discuss how clouds are situated wrt HPC and supercomputers, why multicore chips are important in a typical data center.
C. Defining Clouds II
In this lecture we discuss service-oriented architectures, Software services as Message-linked computing capabilities.
In this lecture we discuss different aaS’s: Network, Infrastructure, Platform, Software. The amazing services that Amazon AWS and Microsoft Azure have Initial Gartner comments on clouds (they are now the norm) and evolution of servers; serverless and microservices Gartner hypecycle and priority matrix on Infrastructure Strategies.
D. Defining Clouds III: Cloud Market Share
In this lecture we discuss on how important the cloud market shares are and how much money do they make.
E. Virtualization: Virtualization Technologies,
In this lecture we discuss hypervisors and the different approaches KVM, Xen, Docker and Openstack.
F. Cloud Infrastructure I
In this lecture we comment on trends in the data center and its technologies. Clouds physically spread across the world Green computing Fraction of world’s computing ecosystem. In clouds and associated sizes an analysis from Cisco of size of cloud computing is discussed in this lecture.
G. Cloud Infrastructure II
In this lecture, we discuss Gartner hypecycle and priority matrix on Compute Infrastructure Containers compared to virtual machines The emergence of artificial intelligence as a dominant force.
H. Cloud Software:
In this lecture we discuss, HPC-ABDS with over 350 software packages and how to use each of 21 layers Google’s software innovations MapReduce in pictures Cloud and HPC software stacks compared Components need to support cloud/distributed system programming.
I. Cloud Applications I: Clouds in science where area called
In this lecture we discuss cyberinfrastructure; the science usage pattern from NIST Artificial Intelligence from Gartner.
J. Cloud Applications II: Characterize Applications using NIST
In this lecture we discuss the approach Internet of Things with different types of MapReduce.
K. Parallel Computing
In this lecture we discuss analogies, parallel computing in pictures and some useful analogies and principles.
L. Real Parallel Computing: Single Program/Instruction Multiple Data SIMD SPMD
In this lecture, we discuss Big Data and Simulations compared and we furthermore discusses what is hard to do.
M. Storage: Cloud data
In this lecture we discuss about the approaches, repositories, file systems, data lakes.
N. HPC and Clouds
In this lecture we discuss the Branscomb Pyramid Supercomputers versus clouds Science Computing Environments.
O. Comparison of Data Analytics with Simulation:
In this lecture we discuss the structure of different applications for simulations and Big Data Software implications Languages.
P. The Future I
In this lecture we discuss Gartner cloud computing hypecycle and priority matrix 2017 and 2019 Hyperscale computing Serverless and FaaS Cloud Native Microservices Update to 2019 Hypecycle.
Q. other Issues II
In this lecture we discuss on Security Blockchain.
R. The Future and other Issues III
In this lecture we discuss on Fault Tolerance.