How do I learn enough about CLR to make educated guesses about performance problems?

Yes, I am using a profiler (ANTS). But at the micro-level it cannot tell you how to fix your problem. And I'm at a microoptimization stage right now. For example, I was profiling this:

for (int x = 0; x < Width; x++)
{
    for (int y = 0; y < Height; y++)
    {
        packedCells.Add(Data[x, y].HasCar);
        packedCells.Add(Data[x, y].RoadState);
        packedCells.Add(Data[x, y].Population);
    }
}

ANTS showed that the y-loop-line was taking a lot of time. I tho开发者_运维技巧ught it was because it has to constantly call the Height getter. So I created a local int height = Height; before the loops, and made the inner loop check for y < height. That actually made the performance worse! ANTS now told me the x-loop-line was a problem. Huh? That's supposed to be insignificant, it's the outer loop!

Eventually I had a revelation - maybe using a property for the outer-loop-bound and a local for the inner-loop-bound made CLR jump often between a "locals" cache and a "this-pointer" cache (I'm used to thinking in terms of CPU cache). So I made a local for Width as well, and that fixed it.

From there, it was clear that I should make a local for Data as well - even though Data was not even a property (it was a field). And indeed that bought me some more performance.

Bafflingly, though, reordering the x and y loops (to improve cache usage) made zero difference, even though the array is huge (3000x3000).

Now, I want to learn why the stuff I did improved the performance. What book do you suggest I read?

CLR via C# by Jeffrey Richter.

It is such a great book that someone stolen it in my library together with C# in depth.

The CLR is not involved at all here, this should all be translated to straight machine code without calls into the CLR. The JIT compiler is responsible for generating that machine code, it has an optimizer that tries to come up with the most efficient code. It has limitations, it cannot spend a large amount of time on it.

One of the important things it does is figuring out what local variables should be stored in the CPU registers. That's something that changed when you put the Height property in a local variable. It possibly decided to store that variable in a register. But now there's one less available to store another variable. Like the x or y variable, one that's critical for speed. Yes, that will slow it down.

You got a bad diagnostic about the outer loop. That could possibly be caused by the JIT optimizer re-arranging the loop code, giving the profiler a harder time mapping the machine code back to the corresponding C# statement.

Similarly, the optimizer might have decided that you were using the array inefficiently and switched the indexing order back. Not so sure it actually does that, but not impossible.

Anyhoo, the only way you can get some insight here is by looking at the generated machine code. There are many decent books about x86 assembly code, although they might be a bit hard to find these days. Your starting point is Debug + Windows + Disassembly.

Keep in mind however that even the machine code is not a very good predictor of how efficient code is going to run. Modern CPU cores are enormously complicated and the machine code is no longer representative for what actually happens inside the core. The only tried and true way is what you've already been doing: trial and error.

Albin - no. Honestly I didn't think that running outside a profiler would change the performance difference, so I didn't bother. You think I should have? Has that been a problem for you before? (I am compiling with optimizations on though)

Running under a debugger changes the performance: when it's being run under a debugger, the just-in-time compiler automatically disables optimizations (to make it easier to debug)!

If you must, use the debugger to attach to an already-running already-JITted process.

One thing you should know about working with Arrays is that the CLR will always make sure that array-indices are not out-of-bounds. It has an optimization for 1-dimensional arrays but not for 2+ dimensions.

Knowing this, you may want to benchmark MyCell Data[][] instead of MyCell Data[,]

Hm, I don't think that the loop enrolling is the real problem. 1. I'd try to avoid accessing the array Data three times per inner loop. 2. I'd also recommend, to re-think the three Add statements: you are apparently accessing a collection three times to add trivial some data. Make it only one access per iteration and add a data type containing three entries:

for (int y = 0; ... {
 tTemp = Data[x, y];
 packedCells.Add(new {
  tTemp.HasCar, tTemp.RoadState, tTemp.Population 
 });
}

Another look reveals, that you are basically vectorizing a matrix by copying it into an array (or some other sequential collection)... Is that necessary at all? Why don't you just define a specialized indexer which simulates that linear access? Even better, if you only need to enumerate the entries (in that example you do, no random access required), why don't you use an adequate LINQ expression?

Point 1) Educated guesses are not the way to do performance tuning. In this case I can guess about as well as most, but guessing is the wrong way to do it.

Point 2) Profilers need to be well understood before you know what they're actually telling you. Here's a discussion of the issues. For example, what many profilers do is tell you "where the program spends its time", i.e. where the program counter spends its time, so they are almost absolutely blind to time requested by function calls, which is what your inner loop seems to consist of.

I do a lot of performance tuning, and here is what I do. I cycle between two activities:

• Overall time measurement. This doesn't require special tools. I'm not trying to measure individual routines.

• "Bottleneck" location. This does not require running the code at any kind of speed, because I'm not measuring. What I'm doing is locating lines of code that are responsible for a significant percent of time. I know which lines they are because they are on the stack for that percent, and stack samples easily find them.

Once I find a "bottleneck" and fix it, I go back to the first step, measure what percent of time I saved, and do it all again on the next "bottleneck", typically from 2 to 6 times. I am helped by the "magnification effect", in which a fixed problem magnifies the percentage used by remaining problems. It works for both macro and micro optimization.

(Sorry if I can't write "bottleneck" without quotes, because I don't think I've ever found a performance problem that resembled the neck of a bottle. Rather they were all simply doing things that didn't really need to be done.)

Since the comment might be overseen, I repeat myself: it is quite cumbersome to optimize code which is per se overfluous. You do not really need to explicitely linearize your matrix at all, see the comment above: Define a linearizing adapter which implements IEnumerable<MyCell> and feed it into the formatter.

I am getting a warning when I try to add another answer, so I am going to recycle this one.. :) After reading Steve's comments and thinking about it for a while, I suggest the following: If serializing a multi-dimensional array is too slow (haven't tryied, I just believe you...) don't use it at all! It appears, that your matrix is not sparse and has fixed dimensions. So define the structure holding your cells as simple linear array with indexer:

[Serializable()]
class CellMatrix {
 Cell [] mCells;

 public int Rows { get; }
 public int Columns { get; }

 public Cell this (int i, int j) {
  get {
   return mCells[i + Rows * j];    
  }   
  // setter...
 }

 // constructor taking rows/cols...
}

A thing like this should serialize as fast as native Array does... I don't recommend hard coding the layout of Cell in order to save few bytes there...

Cheers, Paul