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    <p>No. I never updated it, but I think taken with appropriate grains of salt, the general advice and most rules of thumb in the article still hold up well today.</p> <p>(That said, it would be interesting to repeat the experiment today to see how primitive times have changed, how the generated code has changed, and how microprocessors have changed.)</p> <p>The relative overheads of most primitives won't have changed much, but some will have changed dramatically. For example, the mediocre performance of non-static delegate invoke was dramatically improved (in .NET 2.0, if I recall correctly). I would hate to think that a practitioner today would go out of her way to avoid delegate invoke because I reported it as very expensive in 2003.</p> <p>Since .NET 1.1, I would expect many compiled code sequences to have changed; there would be new JIT compiler optimizations (which doesn't show up so well in microbenchmarks); different mixes of JIT'd and NGEN'd code (and NGEN was not explored in my article); and key subsystems like the garbage collector have been continually tuned over the years.</p> <p>I reiterate my cautionary advice about the potential of memory system effects to drown out the costs of any number of individual managed code primitive operations -- and again note that a lot has changed. For example, a great deal of CLR performance work in 03-04 went into better working set behavior (such as minimizing dirty private pages) of NGEN'd system assemblies.</p> <p>Of course the theme of the article is the imperative to thoughtfully and vigilantly measure the performance of your code, and that theme is timeless.</p> <p>By the way, I always wanted to do a follow up article on the expected/typical time and space costs of the top few hundred or so most used .NET BCL methods, and to showcase as cautionary tales a few of the horror stories we found working on the .NET performance. That led to some very interesting thinking about how to characterize the empirical performance of a class library / framework as actually used by real practitioners in the wild...</p> <p>Thanks for reading it back then, and thank you for your ongoing interest.</p> <p>p.s. I see Vance Morrison subsequently wrote a great two part MSDN series on this subject -- if you enjoyed my article you'll love these:</p> <p><a href="http://msdn.microsoft.com/en-us/magazine/cc500596.aspx">http://msdn.microsoft.com/en-us/magazine/cc500596.aspx</a></p> <p><a href="http://msdn.microsoft.com/en-us/magazine/cc507639.aspx">http://msdn.microsoft.com/en-us/magazine/cc507639.aspx</a></p>
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    1. POIs there an updated version of "Writing Faster Managed Code: Know What Things Cost"?
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    1. COI should add that microprocessors have also changed. Of course they offer multiple threads and/or cores. And CPU designers have been able to chew on execution traces of OOP and JVM/CLR apps to tune and tweak their microarchitectures. For example much better branch prediction in the context of virtual method calls and short method call/returns allow some of the code that the JIT can't optimize away to now execute out-of-order with fewer hazards, rollbacks, or stalls. Some overheads are optimized completely away. This makes microbenchmarking that much more problematic and perilous!
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    2. COAlthough some microprocessors have started to move in the opposite direction, back towards being more in-order and with literal registers (eg PPC, Larabee), which makes a lot of pipeline penalties more painful.
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    3. COSo true! I think as the trend of 'energy efficiency of a computation trumps speed of a computation' continues to gather momentum (assuming the mix of parallelized 'throughput software' becoming more economically interesting), we'll see more of these simpler microarchitectures, or perhaps even a mix of complex and simple in heterogeneous chip-multiprocessors. Interestingly, as the hardware pendulum swings back it could in time be reflected in changes in VM codegen and organization! Software shapes hardware and vice versa.
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