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Super Computing

High Performance Computing

  • Super Computer
    • Entire cluster bought at same time
    • High end network, server and storage HW
    • Small number of scientists have access

MPI (Message Passing Interface) (downway)

  • MPI
    • Library standard defined by a committee of vendors, implementers, and parallel programmers
    • Used to create parallel programs based on message passing (tree)
    • Popular for scientific computation being performed on high performance compute cluster

Amdahl's Law

  • Parts of a program must be run sequentially and parts can be run in parallel.
  • Speedup = 1/((1-P) + P/N) N-#of processing entities, P fraction of program taht is parallel

Big Data Analytics

  • Volume: The amount of data companies want to analyze is growing tremendously. 40 trillion GB by 2020

  • Variety: Data is often unstructured and/or user generated. Tweets, videos

  • Velocity: Analysis must be fast to be useful.

Map Reduce & Hadoop

  • Map Reduce (google developed)

    • Large scale analytics
    • Uses commodity servers
    • Includes a distributed storage system
    • schedule task..
  • Hadoop is an open source version of Map Reduce

Map Reudce Flow

  • Input files -> Map -> Key-value -> Reudce -> Output

Storm

  • Like Spark
  • Hadoop is for batch, Storm is for stram

Edge Computing!!!

  • Latency
  • Bandwidth

Content Delivery Networks (CDN)

  • It is similar to Edge cloud:

    • Provide content close to users
    • Use less core bandwidth, low latency.
  • Akamai is the major CDN company

    • static and dynamic

Iot (Internet of things) need

  • Streaming data

Job

  • Amazon's cloud services
  • Hadoop, big data analysis
  • Network programming
  • Multi-threading, concurrency
  • Virtual machines, containers.