A working understanding of the physical parts of a computer is important for making decisions about how to make code faster.

• Here’s a basic overview of the parts of a modern desktop computer If you’ve never built a computer, this might be helpful.
• How are supercomputers different?
• What is cache, and why does it speed things up?
• How big should a page file/swap partition be?

Why is my code slow?

• Profilers can help you identify code bottlenecks
• One developer’s story of how he used unit testing concepts to benchmark his code
• Big-O notation and algorithmic complexity–aka, maybe your algorithm is the problem
• A proof of Amdahl’s Law, which predicts how much a program can be sped up when parallelized

So you want to parallelize . . .

• A phenomenal introduction to parallel computing
• An intuitive explanation of race conditions: how many people does it take to turn off a light?
• Multithreading is an approach to parallelization, but doesn’t always result in parallelization
• An overview of cloud computing (not a how-to)
• MPI: tutorials for how to parallelize in hardcore mode, generally for compiled languages
• Map-Reduce, Spread-Gather - some sort of link to embarassingly parallel problem framings
• Difference between CPU and GPU computing
• GPU computing, it’s strengths and limitations