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Tag - SynScaleMM

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2011, Thursday December 8

Avoiding Garbage Collector: Delphi and Apple side by side

Among all trolling subject in forums, you'll find out the great Garbage Collection theme.

Fashion languages rely on it. At the core of the .Net and Java framework, and all scripting languages (like JavaScript, Perl, Python or Ruby), you'll find a Garbage Collector. New developers, just released from schools, do learn about handling memory only in theory, and just can't understand how is memory allocated - we all have seen such rookies involved in Delphi code maintenance, leaking memory as much as they type. In fact, most of them did not understood how a computer works. I warned you this will be a trolling subject.

And, in Delphi, there is no such collector. We handle memory in several ways:

  • Creating static variables - e.g. on the stack, inside a class or globally;
  • Creating objects with class instances allocated on heap - in at least three ways: with a try..finally Free block, with a TComponent ownership model in the VCL, or by using an interface (which creates an hidden try..finally Free block);
  • Creating reference-counted variables, i.e. string, array of, interface or variant kind of variables.

It is a bit complex, but it is also deadly powerful. You have several memory allocation models at hand, which can be very handy if you want to tune your performance and let program scale. Just like manual recycling at home will save the planet. Some programmers will tell you that it's a waste of cell brain, typing and time. Linux kernel gurus would not say so, I'm afraid.

Then came the big Apple company, which presented its new ARC model (introduced in Mac OS X 10.7 Lion) as a huge benefit for Objective-C in comparison with the Garbage Collection model. And let's face it: this ARC just sounds like the Delphi memory model.

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2011, Sunday August 28

Multi-threading and Delphi

Writing working multi-threaded code is not easy - it's even hard, as as a Delphi expert just wrote in his blog.

In fact, the first step into multi-thread application development could be:

"protect your shared variables with locks (aka critical sections), because you are not sure that the data you read/write is the same for all threads".

The CPU per-core cache is just one of the possible issues, which will lead into reading wrong values. Another issue which may lead into race condition is two threads writing to a resource at the same time: it's impossible to know which value will be stored afterward.

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2010, Saturday December 4

SynScaleMM - a multi-thread scaling Memory Manager

We just released a new unit to the source code repository.

It's a simple, small and compact MM, built on top of the main Memory Manager(FastMM4 is a good candidate, standard since Delphi 2007), architectured in order to scale on multi core CPU's (which is what FastMM4 is lacking).

Original code is ScaleMM - Fast scaling memory manager for Delphi by André Mussche.

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When inlining works

It was told on this Blog that the Delphi memory manager (FastMM4 since Borland 2006 - but it was even worse with the previous "Borland's" MM), doesn't scale well on multi-code CPU. That is, if you have a multi-threaded application with a lot of memory handling (e.g. aString := aString+someString), the Delphi MM won't scale with multi cores. When I mean "don't scale", I mean that the optimistic though of "my CPU has 4 cores, therefore the same work run in 4 threads will be 4 times faster than with 1 thread" is false. It performs even worse with multiple threads than with 1 thread...

So we went into forking a nice project, named ScaleMM, and created our scalable optimized MM, named SynScaleMM. Our forked modifications were even included in the main ScaleMM branch.

During my profiling of our SynScaleMM, I discovered some very nice results with Delphi compiler inlining features.

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