Since our society has entered a data-intensive era (that is, a big data era), we face larger and larger datasets. For this reason, companies and users are considering what kinds of tools they could use to speed up the process when dealing with data. One obvious solution is to increase their data storage capacity. Unfortunately, there is a huge cost associated with this. The other solutions include distributed computing and some ways to accelerate our process.
In this chapter, we'll cover the following topics:
- Introduction to distributed versus parallel computing
- Understanding MPI
- Parallel processing in Python
- Compute nodes
- Anaconda add-ons
- Introduction to HPCC
