Faster Chips Are Leaving Programmers in Their Dust

mlimber writes "The New York Times is running a story about multicore computing and the efforts of Microsoft et al. to try to switch to the new paradigm: "The challenges [of parallel programming] have not dented the enthusiasm for the potential of the new parallel chips at Microsoft, where executives are betting that the arrival of manycore chips — processors with more than eight cores, possible as soon as 2010 — will transform the world of personal computing.... Engineers and computer scientists acknowledge that despite advances in recent decades, the computer industry is still lagging in its ability to write parallel programs." It mirrors what C++ guru and now Microsoft architect Herb Sutter has been saying in articles such as his "The Free Lunch Is Over: A Fundamental Turn Toward Concurrency in Software." Sutter is part of the C++ standards committee that is working hard to make multithreading standard in C++."

Comments

2005 Called

[brunes69]

....it wants it's article back.

Seriously - any developer writing modern desktop or server applications that doesn't know how to do multi-threaded programming effectively deserves to be on EI anyway. It is not that difficult.

Re:2005 Called

[CastrTroy]

It's not just making your app multithreaded, it's completely changing your algorithms so they they take advantage of multiple processors. I took a parallel programming course in University, so I'm by no means an expert, but I'll give what insight I have. You can't just take a standard sort algorithm and run in multithreaded. You have to change the entire algorithm. In the end, you end up with something that sorts faster than n log (n). However, doing this type of programming where you break up the dataset, sort each set, and then gather the results can be very difficult. Many debuggers don't deal well with multiple threads, so that adds an extra layer of difficulty to the whole problem. Granted, I don't think that we really need this level of multithreadedness, but I think that's what the article is referring to. I think that 10+ core CPUs will only really help for those of us who like to do multiple things at the same time. I think it would even be beneficial to keep most apps tied to a single CPU so that a run-away app wouldn't take over the entire computer.

Re:2005 Called

[gazbo]

In the end, you end up with something that sorts faster than n log (n).

Not without an infinite number of processors you don't.

Re:2005 Called

[ZeroFactorial]

This sounds to me like a great example of passing the buck.

EE Guy #1: We can't seem to build faster chips.
EE Guy #2: No problem. We'll just put tons of processor cores in instead.
EE Guy #1: But people have spent the past 30 years creating algorithms for single core machines. Almost none of the programmers have any experience writing multi-core algorithms!
EE Guy #2: Exactly! We'll be able to blame the programmers for being lazy and not wanting to learn new complicated algorithms that require an additional 4 years of university.
EE Guy #1: Brilliant! We should come up with a catchy headline like "The Free Lunch is Over" or something like that.
EE Guy #2: Yeah, and we could get Slashdot to post a link to the article. Slashdot users are sure to sympathize with our devious plans...

Re:2005 Called

[caerwyn]

As you know, multiple threads in a program do not actually execute concurrently - processing is still serial, it's just so fast that threads can appear to execute simultaneously - and it's not just about queuing execution either.

That holds only for multithreaded programming on a single core. As soon as there are multiple cores available, processing does, in fact, happen simultaneously.

Re:2005 Called

[chaboud]

Well, 2005 called...

it wants its reply back.

The parent is exactly how I would have replied a couple of years ago. I was doing lots of threading work, and I found it easy to the point of being frustrated with other programmers who weren't thinking about threading all of the time.

I was wrong in two ways:

1. It's not that easy to do threading in the most efficient way possible. There's almost always room for improvement in real-world software.

2. There are plenty of programmers who don't write thread-safe/parallel code well (or at all) that are still quite useful in a product development context. Some haven't bothered to learn and some just don't have the head for it. Both types are still useful for getting your work finished, and, if you're responsible for the architecture, you need to think about presenting threading to them in a way that makes it obvious while protecting the ability to reach in and mess with the internals.

The first point is probably the most important. There are several things that programmers will go through on their way to being decent at parallelization. This is in no strict order and this is definitely not a complete list:

- OpenMP: "Okay, I've put a loop in OpenMP, and it's faster. I'm using multiple processors!!! Oh.. wait, there's more?"
Now, to be fair, OpenMP is enough to catch the low-hanging fruit in a lot of software. It's also really easy to try out on your code (and can be controlled at run-time).

- OpenMP 2: "Wait... why isn't it any faster? Wait.. is it slower?"
Are you locking on some object? Did you kill an in-loop stateful optimization to break out into multiple threads? Are you memory bound? Blowing cache? It's time to crack out VTune/CodeAnalyst.

- Traditional threading constructs (mutices, semaphores): "Hey, sweet. I just lock around this important data and we're threadsafe."
This is also often enough in current software. A critical section (or mutex) protecting some critical data solves the crashing problem, but it injects the lock-contention problem. It can also add the cost of round-tripping to the kernel, thus making some code slower.

- Transactional data structures: "Awesome. I've cracked the concurrency problem completely."
Transactional mechanisms are great, and they solve the larger data problem with the skill and cleanliness of an interlocked pointer exchange. Still, there are some issues. Does the naive approach cleanly handle overlapping threads stomping on each-others' write-changes? If so, does it do it without making life hell for the code changing the data? Does the copy/allocation/write strategy save you enough time through parallelism to make back its overhead?

Should you just go back to a critical section for this code? Should you just go back to OpenMP? Should you just go back to single-threading for this section of code? (not a joke)

Perhaps as processors get faster by core-scaling instead of clock-scaling this will become less of a dilemma, but to say that "[to do multi-threaded programming effectively] is not that difficult" is akin to writing your first ray-tracer and saying that 3D is "not that difficult." Somtimes it is. At least at this point there are places where threading effectively is a delicate dance that not every developer need think about for a team to produce solid multi-threaded software.

That doesn't mean that I object to threading being a more tightly-integrated part of the language, of course.

Re:2005 Called

[bfields]

Oh, good grief--since the original poster didn't specify units, and since it's highly unlikely the running time would be exactly n log n for any choice of units, and since it's pretty common to leave out the O() in casual conversation, the only sensible interpretation is that the O() was implied....

Re:2005 Called

[AuMatar]

Yes it is something the app developer needs to deal with. The problem isn't creating threads- the OS does that. The problem is in protecting data from concurrent unsynchronized access (this needs to be done by the app, as the OS has no clue what can/can't be accessed synchronously, that's an application detail) and parallelizing algorithms (again, not something the OS can do).

Eventually, good parallel algorithm libraries will pop up. That will help some subset of problems. I'd expect frameworks to pop up as well, helping another. But in many cases it just comes down to changing how we write programs.

And you're right, this isn't really a desktop issue- its mainly a server one. Desktops really don't need all the power they have now, perhaps one percent of users outside of gamers actually use it. That doesn't make it any less important of a problem to solve. Although I expect in the end people will still end up disappointed- parallelization is not magic pixie dust, you can only get so much of a speedup. I wouldn't be surprised if those 8 corse only give a 2x speedup over a single core on many apps.

Re:2005 Called

[chaboud]

It's not quite like that.

On modern systems, threads are themselves first-class constructs, and it runs somewhat like this:

A process has things like memory-tables for virtual memory, handles for objects, files, socket connections, etc. A process always contains at least one thread (this isn't always true while a process is being set up or torn down, but it's true when most anyone's code is running).

A thread generally has a stack (in the host-process's virtual address space, so everyone can read it), some thread-local storage to make life easier for some api's (you don't need to care about this in most cases), and lives in a process. This means that threads can use virtual addresses for memory interchangeably with other threads in the same process.

Additionally, some operating systems support fibers. A fiber is like a thread except that it has to be explicitly or cooperatively (not quite the same thing) multi-tasked. Fibers use even less memory than threads, and you really don't have to care about them.

When you're in, say, Visual Studio, there's a "threads" window for all of the threads of the process that you are debugging. You can end up stepping through code on one thread while other threads are running.

The modern hardware designs lead to interesting performance side-effects from cache location and memory location. It's not quite as hard as systems that have asymmetric access to resources (e.g. Playstation 2), but it makes for fun work.

Re:2005 Called

[EatHam]

pretty common to leave out the O() in casual conversation

I would say that it is *extremely* common for casual conversation to not have anything whatsoever to do with O().

Re:2005 Called

[Darinbob]

There's a wide variance in what "parallel computing" means. For multicore, you've essentially just got a cheaper version of SMP (symmetric multiprocessing). This is worlds away from what occurs in a parallel computer and what most parallel programming algorithms deal with. With multicore and SMP you program mostly like you're doing multithreading on a single CPU.

The algorithms programmers have to deal with here involve concurrency, and have been in use for decades by anyone writing an OS or device driver. Dining Philosopher problem, readers and writers synchronization, etc. These are used on what most people think of as single processor computers and are essential. So I don't really think of these as "parallel programming", but as "parallel-light".

Parallel programming to me means dealing with SIMD or MIMD machines. MIMD has multiple processors each with its own memory and data, not multiple processors all sharing the same memory like SMP does. They may have high speed connections to a subset of other processors, such as being arranged in a grid or cube. SIMD has multiple processors all with their own data space but executing the same instruction sequences; the simplest form of which might be vector processors. The algorithms for these machines have very little in common with multithreading types of algorithms.

The parallel algorithms that require lots of sharing between processors will hit a bottleneck on the RAM with these multicore CPUs.

M$ programmers should be already capable

[scafuz]

just start a multithread process: 1 core for the program itself, the remaining 7 for the bugs...

hhooppee tthheeyy ffiixx tthhiiss ssoooonn

[Chordonblue]

II hhaavvee aann XX22 pprrocceessssoor? Ii ccaann ggooeess TTWWIICCEE aass ffaasstt nnooww?

Re:hhooppee tthheeyy ffiixx tthhiiss ssoooonn

[ByOhTek]

my eyes, they bleed.

Re:hhooppee tthheeyy ffiixx tthhiiss ssoooonn

[Nova1313]

When the first AMD x2 chips came out the linux kernel had issues with the clock on those chips. The clock would be several times (presumably 2 times?) faster then it should be, the cores clocks were not synchronized for some reason or the kernel would lose track... When you typed a letter it would repeat multiple times as you described. :)

OS/2?

[SCHecklerX]

I remember learning to write software for OS/2 back in the early 90's. Multi-threaded programming was *the* model there, and had it been more popular, it would be pretty much standard practice today, making scaling to multiple cores pretty effortless, I'd think. It's a shame that the single-threaded model became so ingrained in everything, including linux. For an example that comes to mind, why do I need to wait for my mail program to download all headers from the IMAP server before I can compose a new message on initial startup? Same with a lot of things in firefox.

Does anybody remember DeScribe?

Re:OS/2?

[eMartin]

Neither does Microsoft's Outlook Express, but I don't think that was his point.

Re:OS/2?

[pthisis]

It's a shame that the single-threaded model became so ingrained in everything, including linux. For an example that comes to mind, why do I need to wait for my mail program to download all headers from the IMAP server before I can compose a new message on initial startup?

I'm of the opposite opinion; it's a shame that so many people equate parallel processing with threads. When there's not much shared data, using multiple processes keeps memory protection between your parallel "things", decreasing coupling, increasing isolation, and generally resulting in a more stable system (and for certain things where you can avoid some cache coherency problems, a faster system). Your example is perfect; there's really no good reason to use a thread for such lookups. Another process would do, or even better just use select() and avoid all the pain (and bugs) of a multithreaded solution.

OS developers spent a lot of engineering time implementing protected memory. Threads throw out a huge portion of that; a good programmer won't do that without very good reasons. Some tasks, where there really are tons of complicated data structures to be shared, are good candidates for threading. More commonly, though, threads are used either because the programmer doesn't know any better or because they allow you to be a slacker about defining exactly what is shared and mediating access to it. The latter is especially dangerous; defining exactly what (and how) things are shared goes most of the way toward eliminating multiprocessing bugs, and threads make it easy to slack off on that and get a "mostly working" solution that occasionally deadlocks, fails to scale, etc.

Use processes or state machines when you can, and threads when you must.

Re:OS/2?

[TheRaven64]

I'm of the opposite opinion; it's a shame that so many people equate parallel processing with threads. I read that and wished I had mod points. Anyone who has programmed with a language designed for concurrency, like Erlang, Termite, or a few Haskell dialects hates using threads. Threads are something that two kinds of people should use; operating system designers and compiler writers. Everyone else should be using a higher-level abstraction.

The big problem is not the operating system designers, it's the CPU designers. They integrated two orthogonal concepts, protection and translation, into the same mechanism (page tables, segment tables, etc). The operating system wants to do translation so it can implement virtual memory. The userspace program wants to do protection so it can use parallel contexts efficiently. Mondrian memory protection would fix this, but no one has implemented it in a commercial microprocessor (to my knowledge).

Thank god

[Fizzl]

Thank god that Java, C# and other piles of shit I hate do this quite intuitively and easily.
Guess I had it coming.
/me closes his eyes and embraces C++ for the last time before the inevitable doom

Re:Thank god

[zifn4b]

The only significant thing that managed languages make easier with regard to multithreading other than a more intuitive API is garbage collection so that you don't have to worry about using reference counting when passing pointers between multiple threads.

All of the same challenges that exist in C/C++ such as deadly embrace and dining philosophers still exist in managed languages and require the developer to be trained in multi-threaded programming.

Some things can be more difficult to implement like semaphores. You also have to be careful about what asynchronous methods and events you invoke because those get queued up on the thread pool and it has a max count.

I would say managed languages are "easier" to use but to be used effectively you still have to understand the fundamental concepts of multithreaded programming and what's going on underneath the hood of your runtime environment.

The basic problem

[ucblockhead]

Some algorithms are inherently not amenable to parallelization. If you have eight cores instead of one, then the performance boost you can get can be anywhere from eight times faster to none at all.

So far, multiple cores have boosted performance mostly because the typical user has multiple applications running at a time. But as the number of cores increases, the beneficial effects diminish dramatically.

In addition, most applications these days are not CPU bound. Having eight cores doesn't help you much when three are waiting on socket calls, four are waiting on disk access calls and the last is waiting for the graphics card.

Re:The basic problem

[savuporo]

So far, multiple cores have boosted performance mostly because the typical user has multiple applications running at a time. But as the number of cores increases, the beneficial effects diminish dramatically.
They diminish, but they never disappear. Even in algorithms where you completely have to wait the results of previous computation to go on, you can still get a speedup with branch prediction. In essence, while your one core is cracking the numbers, other cores do the what if work, and even if you mispredict in lots of cases, you can still get speedups with large datasets, because in some cases, when your first core comes up with a result, you will discover that the what if computation started out with a right guess.
Hey, i hear they are doing essentially the same stuff with all those newfangled multiscalar processors and branch prediction anyway.

Personal computing?

[Dan East]

"processors with more than eight cores, possible as soon as 2010 -- will transform the world of personal computing"

Exactly what areas of "personal computing" are requiring this horsepower? The only two that come to mind are games and encoding video. The video encoding part is already covered - that scales nicely to multiple threads, and even free encoders will use the extra cores to their full potential. That leaves gaming, which is basically proprietary. The game engine must be designed so that AI, physics, and other CPU-bound algorithms can be executed in parallel. This has already been addressed.

So this begs the question, exactly how will average consumer benefit from an OS and software that can make optimum use of multiple cores, when the performance issues users complain about are not even CPU-bound in the first place?

Dan East

Sameless Plug: Qt 4.4

[scorp1us]

Full disclosure: I am a Qt Developer (user) I do not work for TrollTech

The new Qt4.4 (due 1Q2008) has QtConcurrent, a set of classes that make multi-core processing trivial.

From the docs:

The QtConcurrent namespace provides high-level APIs that make it possible to write multi-threaded programs without using low-level threading primitives such as mutexes, read-write locks, wait conditions, or semaphores. Programs written with QtConcurrent automaticallly adjust the number of threads used according to the number of processor cores available. This means that applications written today will continue to scale when deployed on multi-core systems in the future.

QtConcurrent includes functional programming style APIs for parallel list prosessing, including a MapReduce and FilterReduce implementation for shared-memory (non-distributed) systems, and classes for managing asynchronous computations in GUI applications:

        * QtConcurrent::map() applies a function to every item in a container, modifying the items in-place.
        * QtConcurrent::mapped() is like map(), except that it returns a new container with the modifications.
        * QtConcurrent::mappedReduced() is like mapped(), except that the modified results are reduced or folded into a single result.
        * QtConcurrent::filter() removes all items from a container based on the result of a filter function.
        * QtConcurrent::filtered() is like filter(), except that it returns a new container with the filtered results.
        * QtConcurrent::filteredReduced() is like filtered(), except that the filtered results are reduced or folded into a single result.
        * QtConcurrent::run() runs a function in another thread.
        * QFuture represents the result of an asynchronous computation.
        * QFutureIterator allows iterating through results available via QFuture.
        * QFutureWatcher allows monitoring a QFuture using signals-and-slots.
        * QFutureSynchronizer is a convenience class that automatically synchronizes several QFutures.
        * QRunnable is an abstract class representing a runnable object.
        * QThreadPool manages a pool of threads that run QRunnable objects.

This makes multi-core programming almost a no-brainer.

And so it goes......

[Nonillion]

processors with more than eight cores, possible as soon as 2010 -- will transform the world of personal computing....

Translation:

Code will get even more inefficient / bloated and require faster hardware to do the same thing you are doing now. While I'm all for better / faster computer hardware, most if not all Jane and Joe Sixpack users never need Super Computer power to surf the net, read e-mail and watch videos.

Erlang

[Niten]

Oddly enough, I just watched a presentation about this very topic, with an emphasis on Erlang's model for concurrency. The slides are available here:

http://www.algorithm.com.au/downloads/talks/Concurrency-and-Erlang-LCA2007-andrep.pdf

The presentation itself (OGG Theora video available here) included an interesting quote from Tim Sweeney, creator of the Unreal Engine: "Shared state concurrency is hopelessly intractable."

The point expounded upon in the presentation is that when you have thousands of mutable objects, say in a video game, that are updated many times per second, and each of which touches 5-10 other objects, manual synchronization is hopelessly useless. And if Tim Sweeney thinks it's an intractable problem, what hope is there for us mere mortals?

The rest of this presentation served as an introduction to the Erlang model of concurrency, wherein lightweight threads have no shared state between them. Rather, thread communication is performed by an asynchronous, nothing-shared message passing system. Erlang was created by Ericsson and has been used to create a variety of highly scalable industrial applications, as well as more familiar programs such as the ejabberd Jabber daemon.

This type of concurrency really looks to be the way forward to efficient utilization of multi-core systems, and I encourage everyone to at least play with Erlang a little to gain some perspective on this style of programming.

For a stylish introduction to the language from our Swedish friends, be sure to check out Erlang: The Movie.

Re:Oh, wow

[bladesjester]

A guy who's on the C++ standards committee AND works for Microsoft.

Actually, according to the latest Dr Dobbs, Herb is the *chair* of the ISO C++ Standards committee. (He had an article on lock hierarchies being used to avoid deadlock)

He's really going to know what he's talking about, then.

As chair of the committee, I'd say there's a pretty fair chance that he *does*.

I really love people who bash things just because Microsoft is involved. Contrary to what seems to be a popular belief here, they have some incredibly intelligent people who are very good at what they do there.

Threads considered harmful

[richieb]

Check out this article on O'Reilly's site. Threads are actually very low level construts (like pointers and manual memory management). Accordingly the future belongs to languages that eliminate threads as a basis for concurrency. See Erlang and Haskell.

Re:Threads Are Not the Answer

[caerwyn]

This is very, very wrong. Data-set partitioning is certainly one way of achieving parallelism in programming, but it is hardly the only way- nor is it applicable to all domains, as many problems have solutions with too many inter-cell data dependencies. In addition, threads provide a wealth of benefits to application developers by allowing multiple unrelated tasks to be performed simultaneously.

There is, and will always be, overhead associated with parallelization. It may sound great to say "oh, we can farm out parts of this data set to other cores!", but that requires a lot of start-up and tear-down synchronization. It's not at all uncommon for overall performance to be improved by doing something *unrelated* at the same time, requiring less synchronization overhead.

Are threads perfect for everything? No. But calling them the second worse thing to happen to computing is, as best, disingenuous.

Re:Evolution that halted at 4 ghz....

[Animats]

I have for over 6 years been thinking..of a 3d-dimmension processor that cross communicates over a diagonal matrix instead of the traditional serial and parallel communication model.

Six years, and you haven't discovered all the machines built to try that? This was a hot idea in the 1980s. Hypercubes, connection machines, and even perfect shuffle machines work something like that. There's a long history of multidimensional interconnect schemes. Some of them even work.

This has been coming for a while.

[jskline]

The fact is that programming by and large has gotten lazy, shiftless and sloppy over time and not any better or faster. They really did rely on processing and memory architectures getting faster to overcome their coding bottlenecks. The words; "optimized code" have little or no significance in todays programming shops because of budgets. Because of the push to get stuff out the door as quickly as possible, corners are cut all over the place on many things.

There once was time when debugging was part of your job. Now; someone else does that and at most, the better coders do some unit testing to ensure their code snippet does what it is supposed to. There generally isn't any "standard" with regard to processes except in some houses that follow *recommended coding guidelines* but these are few and far between. Old school coders had a process in mind to fit a project as a whole and could see the end running program. Many times now, you are to code an algorithm without any regard or concept as to how it might be used. A lot of strange stuff going on out there in the business world with this!

If there is a fundamental change in the base for C++, et al., this is going to possibly have a detrimental effect on the employment market as there will be many who cannot conceptualize multi-threading methodologies much less modeling some existing processing in this paradigm; and leave the markets.

I left the programming markets because of the clash of bean counters vs quality, and maybe this will have a telling change in that curve. I always did enjoy some coding over the years and maybe this would make an interesting re-introduction. I have personally not coded in a multi-threading project but have the concepts down. Might be fun!

There's not much hope for the C++ committee

[Animats]

I have little hope for the C++ standards committee. It's dominated by people who think really l33t templates are really cool. Everything has to be a template feature. They're fooling around with a proposal for declaring variables atomic through something like atomic<int> n; This allows really l33t programmers to write really l33t code using really l33t lockless programming. But without the proofs of correctness needed to make that actually work reliably.

It's also long been Strostrup's position that concurrency is a library problem. As long as the OS provides threads and locking, it's not a language problem. This isn't good enough.

The fundamental problem is that, as currently defined, a C++ compiler has no idea which variables are shared between threads, and which are never shared. The compiler has no notion of critical sections. Fixing this requires some fundamental changes to the language. It's known what to do; Modula, Ada, and Java all have synchronization and isolation built into the language. But there's nothing like that in C++, and the designers of C++ don't want to admit their mistakes.

It's not just a C++ problem. Python has a similar issue. Python as a language doesn't deal with concurrency adequately. The main implementation, CPython, has a "global interpreter lock" that slows the thing down to single-CPU speed.

Re:Evolution that halted at 4 ghz....

[Skrynkelberg]

You may want to switch of the rapid fire-mode for your "."-key.

Re:Wait for the new C++ standard before you switch

[mariuszbi]

Wait a second! Have you ever coded in C++ ? Even if threads are not in the standard library, you have boost, you have Intel's TBB(threading building blocks), besides the native threading library. Do you trust you library in Java? What if the VM screws everything up. As for the compiler "optimizing" everything there is a little keyword : volatile that just tells the compiler not to optimize memory access for that varible. A think the real problem is working in a new programming paradigm : have a problem with sharing variables : code everything using pure functions.

Microsofts view on cores

[bjb_admin]

No need for parallel computing all cores are already used.

Core one: For the OS
Core two: Anti-virus
Core three: Anti-Spyware / Windows Defender
Core four: Firewall
Core five: Windows update notifications and installations
Core six: Windows Genuine advantage checks
Core seven: Eye Candy (Vista) with XP you get a bonus CPU
Core eight: What ever the user wants to run, except when you get a virus, then
you have to share it with the SPAM bot.

Guess we will be waiting for 16 core CPU's.

Oh and don't start me on memory requirements :-)

Re:Diaspora

[Chirs]

For many large-scale software projects (I work in industry so I have some experience with this) it is far easier to find more cpu power than more programmers.

Making code easy to read and maintain is critical to maximizing the efficiency of the programmer. The efficiency of the code is generally a secondary issue, and is only a factor if the code in question is found to be a bottleneck.

Brian Kernighan once said,

"Everyone knows that debugging is twice as hard as writing a program in the first place. So if you're as clever as you can be when you write it, how will you ever debug it?"

Re:C++?

[Yetihehe]

...while all the clever folks have already started writing their scalable applications in something reasonable, like Erlang?

From erlang site:

1.4. What sort of problems is Erlang not particularly suitable for?

People use Erlang for all sorts of surprising things, for instance to communicate with X11 at the protocol level, but, there are some common situations where Erlang is not likely to be the language of choice.

The most common class of 'less suitable' problems is characterised by performance being a prime requirement and constant-factors having a large effect on performance. Typical examples are image processing, signal processing, sorting large volumes of data and low-level protocol termination.

That's why most applications are still in c/c++