Everybody likes to think that what they’re working on is important so this is why I think performance (and measuring performance) matters and why it matters now more than ever.
In the past chip manufacturers like Intel and AMD did a lot of the performance work for us software guys by consistently delivering faster chips that often made performance issues just disappear. This has meant that many developers treat performance issues as secondary concerns that will get better all by themselves if they wait long enough. Unfortunately free lunches don’t last forever as Herb Sutter discusses.
Chip manufacturers can no longer keep increasing the clock speeds of their chips to boost performance so they are reducing the clock speed and increasing the number of cores to take computing to new levels of energy-efficient performance. The result, which is discussed on one of Intel’s blog’s, is that some applications will actually run less quickly on newer multicore hardware. This will surely shock some software consumers when they upgrade to a better machine and find it running software slower than before.
Clearly we need to change our applications to allow them to take advantage of multiple cores. Unfortunately this introduces a lot of complexity and there are many competing opinions about how we should do this. Some seasoned developers are pretty negative about using multithreaded development in any application. Some academics suggest that we use different language constructs altogether to avoid the inherent nondeterminism associated with developing using threads.
Consider also that the types of applications we are developing are also changing. Sure, the traditional rich-client applications are still very popular, but there is also a demand for light-weight web-based clients that communicate with a central server (or servers). The software running on the servers must cater for many users and will have very strict performance requirements.
So how does all this fit in with performance measurement? Well now developers have to write concurrent applications that are difficult to understand and develop. They write web-delivered applications that must respond promptly to many concurrent users and it is unlikely that just upgrading hardware is going to fix any performance problems that crop up. The free lunch is basically over, so now we have to pay. One way to minimize the cost of our lunches is to be able to ‘debug’ or resolve dynamic software issues using a profiler just like you would use a debugger to fix issues with program correctness.
One of the main benefits of using a profiler instead of manually inspecting the code is that it avoids the ‘gut feel’ approach to performance optimization that is common. For example, a developer sees a loop like:
for (int i=0; i < some_vector.size(); ++i)
So they decide to optimize by making a temporary so that the size() function doesn’t get called for every iteration of the loop:
const int some_vector_length = some_vec.size();
for (int i=0; i < some_vector_length; ++i)
The number of lines of code has now increased by 1. If the length of the vector is always small, it is unlikely this buys much in the way of performance. Even worse, a developer may start to do things like loop unrolling when the real cause of the performance problems is something they don’t notice. As the complexity of the code goes up the maintenance costs increase. If a profiler were used, it would be much easier to isolate the cause of a performance problem without wasting time optimizing code that is barely impacting the performance of an application.
Before I get too carried away, I should clarify that performance matters, but only if the performance is poor. For example, if you’re working on a User Interface (UI), according to Jakob Nielsen if the response time to a user action is less than 0.1 seconds, the user will feel that the system is reacting immediately to their action. If you’re working on a computer game the performance requirement might be that the frame rate must be at least 30 Hz. In both of these cases the user will notice if the performance requirement isn’t met, but they will probably not notice or care about performance if the performance requirement is met.
If you haven’t used a profiler before, go and try out a Community Technology Preview (CTP) of Orcas which will be the next version of Visual Studio. For the full experience you should avoid using the VPC images which have reduced profiler functionality. Some day, maybe soon if not already, you’ll have to fix a performance problem with your code and using a profiler might help.