Book Image

Delphi High Performance

By : Primož Gabrijelčič
Book Image

Delphi High Performance

By: Primož Gabrijelčič

Overview of this book

Delphi is a cross-platform Integrated Development Environment (IDE) that supports rapid application development for Microsoft Windows, Apple Mac OS X, Google Android, iOS, and now Linux with RAD Studio 10.2. This book will be your guide to build efficient high performance applications with Delphi. The book begins by explaining how to find performance bottlenecks and apply the correct algorithm to fix them. It will teach you how to improve your algorithms before taking you through parallel programming. You’ll then explore various tools to build highly concurrent applications. After that, you’ll delve into improving the performance of your code and master cross-platform RTL improvements. Finally, we’ll go through memory management with Delphi and you’ll see how to leverage several external libraries to write better performing programs. By the end of the book, you’ll have the knowledge to create high performance applications with Delphi.
Table of Contents (16 chapters)
Title Page
Copyright and Credits
Packt Upsell

Fine-tuning SlowCode

We are near the end of the chapter. Let's step back a little and take a breath.

This chapter is packed with information, but if I would have to pick the most important lesson, it would be: don't enlarge strings (arrays, lists) element by element. If you know how much space some data will take, allocate the space at the beginning.

As all recommendations go, this too must be taken with a grain of salt. Most of the time such optimizations will not matter. You should always have the following checklist in mind:

  1. Measure. Find where the problem actually is.
  2. See if you can improve the algorithm. This will give the best results.
  3. Fine-tune the code.

In the previous chapter, we have optimized the heart out of our old friend, SlowCode. Just to remind you, the latest version SlowCode_Sieve_v2_opt processes 10 million elements in a mere 529 ms. Still, there is a little room for improvement that I've neglected so far.

The problem lies in the function, Filter which expands the Result array...