• AMD Ryzen 9 5950x Powerhouse Compiles Three Fourths Of A Million Lines

    From World90@21:1/5 to All on Thu Dec 17 15:13:39 2020

    AMD Ryzen 9 5950x Powerhouse Compiles Three Fourths Of A Million Lines
    Of Delphi Code In 12 Seconds

    Read more here:


    About Delphi and Rust and C++..

    Read the following:

    Speed – Delphi has this in spades: Speed of development, speed of compilation, and speed of execution. Sure, you may be able to find some situations where something is faster in one area, but over all Delphi is
    very well rounded in the speed department.

    Read more here:


    You have to understand correctly what the above means,
    it means that Delphi is "much" faster in compilation than C++
    or Rust, and it has a decent speed in execution and as
    a proof read my following writing to notice that Delphi is still great
    (this is why i am also programming in Delphi):

    I have just read the following article, i invite you to read it:

    The Rust Compilation Model Calamity


    So as you notice that the compile times of Rust are so bad.

    More about compile time and build time..

    Look here about Java it says:

    "Java Build Time Benchmarks

    I'm trying to get some benchmarks for builds and I'm coming up short via Google. Of course, build times will be super dependent on a million
    different things, but I'm having trouble finding anything comparable.

    Right now: We've got ~2 million lines of code and it takes about 2 hours
    for this portion to build (this excludes unit tests).

    What do your build times look like for similar sized projects and what
    did you do to make it that fast?"

    Read here to notice it:


    So 2 million lines of code of Java takes about 2 hours to build.

    And what do you think that 2 millions lines of code takes
    to Delphi ?

    Answer: Just about 20 seconds.

    Here is the proof from Embarcadero, read and look at the video to be
    convinced about Delphi:


    C++ also takes "much" more time to compile than Delphi.

    This is why i said previously the following:

    I think Delphi is a single pass compiler, it is very fast at compile
    time, and i think C++ and Java and C# are multi pass compilers that are
    much slower than Delphi in compile time, but i think that the generated executable code of Delphi is still fast and is faster than C#.

    And what about the Advantages and disadvantages of single and multi pass compiler?

    And From Automata Theory we get that any Turing Machine that does 2 (or
    more ) pass over the tape, can be replaced with an equivalent one that
    makes only 1 pass, with a more complicated state machine. At the
    theoretical level, they the same. At a practical level, all modern
    compilers make only one pass over the source code. It typically
    translated into an internal representation that the different phases
    analyze and update. During flow analysis basic blocks are identified.
    Common sub expression are found and precomputed and results reused.
    During loop analysis, invariant code will be moved out the loop. During
    code emission registers are assigned and peephole analysis and code
    reduction is applied.

    More about Delphi..

    As you have noticed i am also using Delphi and Freepascal,
    so read the following to know more about Delphi:

    Delphi for iOS and Android: The Natives are restless

    Delphi’s Strengths and Weaknesses

    So what does all this mean for developers? It means that Delphi has its strengths and weaknesses, and as long as you are aware of them, you can
    choose Delphi for the right jobs.

    If you need cross-platform compatibility and want to deal with only one
    code base (mostly), Delphi is an excellent choice. It provides nice abstractions of the OS and its services, a relatively pretty GUI
    library, and native (very fast) access to the CPU. Delphi also has
    excellent DB connectivity, web services connectivity, and networking in general. This means Delphi is a good choice for:

    - Enterprise developers, who want to provide mobile access and don’t
    really care about pixel-perfect look and feel

    - Scientific and number crunching developers, who need fast processing
    and a way to nicely display their results

    - Game developers, surprisingly enough, who want to develop
    cross-platform games which don’t have “native” interfaces anyway and where FMX can provide fast-enough graphics. (In other words, not Madden
    level graphics but Angry Birds).

    - “Light” Apps which don’t use a bazillion controls to interact with the user and don’t need “pixel-perfect” responsiveness

    - Compelling apps where the user will forgive some idiosyncrasies
    because the app is so good. I mention this because Delphi allows you to concentrate on the app. Delphi provides the RAD and the cross-platform compatibility, you can concentrate on making the killer app.

    Read more here:


    Pascal still an advantage for some iOS, Android developers

    Many developers wouldn't dream of developing in Delphi with iOS or
    Android in mind, but with cross-platform compilers, companies sitting on
    years of solid code may suddenly find themselves with a second wind.

    Read more here:


    NASA is also using Delphi, read about it here:


    The European Space Agency is also using Delphi, read about it here:


    More about Energy efficiency..

    You have to be aware that parallelization of the software
    can lower power consumption, and here is the formula
    that permits you to calculate the power consumption of
    "parallel" software programs:

    Power consumption of the total cores = (The number of cores) * (
    1/(Parallel speedup))^3) * (Power consumption of the single core).

    Also read the following about energy efficiency:

    Energy efficiency isn’t just a hardware problem. Your programming
    language choices can have serious effects on the efficiency of your
    energy consumption. We dive deep into what makes a programming language
    energy efficient.

    As the researchers discovered, the CPU-based energy consumption always represents the majority of the energy consumed.

    What Pereira et. al. found wasn’t entirely surprising: speed does not
    always equate energy efficiency. Compiled languages like C, C++, Rust,
    and Ada ranked as some of the most energy efficient languages out there,
    and Java and FreePascal are also good at Energy efficiency.

    Read more here:


    RAM is still expensive and slow, relative to CPUs

    And "memory" usage efficiency is important for mobile devices.

    So Delphi and FreePascal compilers are also still "useful" for mobile
    devices, because Delphi and FreePascal are good if you are considering
    time and memory or energy and memory, and the following pascal benchmark
    was done with FreePascal, and the benchmark shows that C, Go and Pascal
    do rather better if you’re considering languages based on time and
    memory or energy and memory.

    Read again here to notice it:


    Embarcadero Launches LearnDelphi.org ...

    As you have noticed , i am also programming in Delphi and Freepascal,
    and now i will invite you to read the following news about Delphi:

    Embarcadero Launches LearnDelphi.org, a Delphi-Centric Learning
    Ecosystem, to Promote Delphi Education

    Read more here:


    And here is the new website of LearnDelphi.org:


    What about garbage collection?

    Read what said this serious specialist called Chris Lattner:

    "One thing that I don’t think is debatable is that the heap compaction behavior of a GC (which is what provides the heap fragmentation win) is incredibly hostile for cache (because it cycles the entire memory space
    of the process) and performance predictability."

    "Not relying on GC enables Swift to be used in domains that don’t want
    it - think boot loaders, kernels, real time systems like audio
    processing, etc."

    "GC also has several *huge* disadvantages that are usually glossed over:
    while it is true that modern GC's can provide high performance, they can
    only do that when they are granted *much* more memory than the process
    is actually using. Generally, unless you give the GC 3-4x more memory
    than is needed, you’ll get thrashing and incredibly poor performance. Additionally, since the sweep pass touches almost all RAM in the
    process, they tend to be very power inefficient (leading to reduced
    battery life)."

    Read more here:


    Here is Chris Lattner's Homepage:


    And here is Chris Lattner's resume:


    This why i have invented the following scalable algorithm and its implementation that makes Delphi and FreePascal more powerful:

    My invention that is my scalable reference counting with efficient
    support for weak references version 1.38 is here..

    Here i am again, i have just updated my scalable reference counting with efficient support for weak references to version 1.37, I have just added
    a TAMInterfacedPersistent that is a scalable reference counted version,
    and now i think i have just made it complete and powerful.

    Because I have just read the following web page:


    But i don't agree with the writting of the guy of the above web page,
    because i think you have to understand the "spirit" of Delphi, here is why:

    A component is supposed to be owned and destroyed by something else, "typically" a form (and "typically" means in english: in "most" cases,
    and this is the most important thing to understand). In that scenario, reference count is not used.

    If you pass a component as an interface reference, it would be very
    unfortunate if it was destroyed when the method returns.

    Therefore, reference counting in TComponent has been removed.

    Also because i have just added TAMInterfacedPersistent to my invention.

    To use scalable reference counting with Delphi and FreePascal, just
    replace TInterfacedObject with my TAMInterfacedObject that is the
    scalable reference counted version, and just replace
    TInterfacedPersistent with my TAMInterfacedPersistent that is the
    scalable reference counted version, and you will find both my TAMInterfacedObject and my TAMInterfacedPersistent inside the AMInterfacedObject.pas file, and to know how to use weak references
    please take a look at the demo that i have included called example.dpr
    and look inside my zip file at the tutorial about weak references, and
    to know how to use delegation take a look at the demo that i have
    included called test_delegation.pas, and take a look inside my zip file
    at the tutorial about delegation that learns you how to use delegation.

    I think my Scalable reference counting with efficient support for weak references is stable and fast, and it works on both Windows and Linux,
    and my scalable reference counting scales on multicore and NUMA systems,
    and you will not find it in C++ or Rust, and i don't think you will find
    it anywhere, and you have to know that this invention of mine solves
    the problem of dangling pointers and it solves the problem of memory
    leaks and my scalable reference counting is "scalable".

    And please read the readme file inside the zip file that i have just
    extended to make you understand more.

    You can download my new scalable reference counting with efficient
    support for weak references version 1.38 from:


    Thank you,
    Amine Moulay Ramdane.

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