6 Memory hierarchy, storage, and networking
This chapter covers
- Making efficient use of CPU cache and main memory
- Using Blosc to access compressed array data
- Using NumExpr to accelerate NumPy expressions
- Designing client/server architectures for very fast networks
It goes without saying that hardware affects performance. But how hardware interacts with performance is not always so obvious. The goal of this chapter is to help you get a better grasp of how, exactly, your machinery can affect your speed and what you can do on the hardware end to improve performance. To that end, we will take a close look at the effects of modern hardware and network architectures on efficient data processing with Python.
There are many counterintuitive implications ...
Get Fast Python now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
