Using Valgrind To Analyze Code For Bottlenecks Makes Faster, Less Power-Hungry Programs

What is the right time to optimize code? This is a very good question, which usually comes down to two answers. The first answer is to have a good design for the code to begin with, because ‘optimization’ does not mean ‘fixing bad design decisions’. The second answer is that it should happen after the application has been sufficiently debugged and its developers are at risk of getting bored.

There should also be a goal for the optimization, based on what makes sense for the application. Does it need to process data faster? Should it send less data over the network or to disk? Shouldn’t one really have a look at that memory usage? And just what is going on inside those CPU caches that makes performance sometimes drop off a cliff on a single core?

All of this and more can be analyzed using tools from the Valgrind suite, including Cachegrind, Callgrind, DHAT and Massif.

Keeping Those Cores Cool

Modern day processors are designed with low power usage in mind, regardless of whether they are aimed at servers, desktop systems or embedded applications. This essentially means that they are in a low power state when not doing any work (idle loop), with some CPUs and microcontrollers turning off power to parts of the chip which are not being used. Consequently, the more the processor has to do, the more power it will use and the hotter it will get.

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Using Valgrind To Track Down Known And Unknown Bugs In Your Code

We all know what bugs in code are. We don’t like them when they are in programs we use, and they’re even worse when they are in code which we have written. Clearly, the best code is bug-free, but how do we get there?

This isn’t a new question, of course, just one that has become ever more important as the total number of lines of code (LoC) that run modern day society keeps increasing and which is affecting even hobbyists more and more often now that everything has a microcontroller inside.

Although many of us know the smug satisfaction of watching a full row of green result markers light up across the board after running the unit tests for a project, the painful reality is that you don’t know whether the code really is functionally correct until it runs in an environment that is akin to the production environment.ย  Yet how can one test an application in this situation?

This is where tools like those contained in the Valgrind suite come into play, allowing us to profile, analyze and otherwise nitpick every single opcode and memory read or write. Let’s take a look, shall we?

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