Computer scientists are a varied bunch, but there is perhaps at least one common thread we share: the inherent desire to 'optimize' our latest result. Theorists make their proofs shorter, more elegant. Empiricists may tune parameters. What of those persons concerned with deterministic algorithms? It is this question I am interested in exploring.

In the first half of the talk we will discuss, through an example, the obvious strategy available to algorithm designers: design better algorithms. The second half will focus on strategies available to algorithm practitioners for crafting more efficient implementations.

To justify the topic to the intended audience, all examples have been drawn from the bioinformatics domain. No preparation or advanced reading is required, or suggested.

Alternative titles for this talk may include:
- What do you mean it won't fit in memory?
- How to save $100K in equipment costs.
- Have we become lazy as practitioners?
- Do you really need to buy a new cluster?