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GC Lingua Franca(s)

Feb-15-2011
Science doesn’t always proceed at the speed of thought. It often proceeds at sociological or even demographic speed. — John Tooby

Open Letter to the Linux Kernel Mailing List (LKML);

If we were already talking to our computers, etc. as we should be, I wouldn’t feel a need to write this to you. Given current rates of adoption, Linux still seems a generation away from being the priceless piece of free software useful to every child and PhD. This army your kernel enables has millions of people, but they often lose to smaller proprietary armies, because they are working inefficiently. My mail one year ago (http://keithcu.com/wordpress/?p=272) listed the biggest workitems, but I realize now I should have focused on one. In a sentence, I have discovered that we need garbage-collected (GC) lingua franca(s). (http://www.merriam-webster.com/dictionary/lingua%20franca)

Every Linux success builds momentum, but the desktop serves as a powerful daily reminder of the scientific tradition. Many software PhDs publish papers but not source, like Microsoft. I attended a human genomics conference and found that the biotech world is filled with proprietary software. IBM’s Jeopardy-playing Watson is proprietary, like Deep Blue was. This topic is not discussed in any of the news articles, as if the license does not matter. I find widespread fear of having ideas stolen in the software industry, and proprietary licenses encourage this. We need to get these paranoid programmers, hunched in the shadows, scribbled secrets clutched in their fists, working together, for any of them to succeed. Windows is not the biggest problem, it is the proprietary licensing model that has infected computing, and science. Desktop world domination is not necessary, but it is sufficient to get robotic chaffeurs and butlers.

There is, unsurprisingly, a consensus among kernel programmers that usermode is “a mess” today, which suggests there is a flaw in the Linux desktop programming paradigm. Consider the vast cosmic expanse of XML libraries in a Linux distribution. Like computer vision (http://www.cs.cmu.edu/~cil/v-source.html), there are not yet clear places for knowledge to accumulate. It is a shame that the kernel is so far ahead of most of the rest of user mode.

The most popular free computer vision codebase is OpenCV, but it is time-consuming to integrate because it defines an entire world in C++ down to the matrix class. Because C/C++ didn’t define a matrix, nor provide code, countless groups have created their own. It is easier to build your own computer vision library using standard classes that do math, I/O, and graphics, than to integrate OpenCV. Getting productive in that codebase is months of work and people want to see results before then. Building it is a chore, and they have lost users because of that. Progress in the OpenCV core is very slow because the barriers to entry are high. OpenCV has some machine learning code, but they would be better delegating that out to others. They are now doing CUDA optimizations they could get from elsewhere. They also have 3 Python wrappers and several other wrappers as well; many groups spend more time working on wrappers than the underlying code. Using wrappers is fine if you only want to call the software, but if you want to improve the underlying code, then the programming environment instantly becomes radically different and more complicated.

There is a team working on Strong AI called OpenCog, a C++ codebase created in 2001. They are evolving slowly as they do not have a constant stream of demos. They don’t consider their codebase is a small amount of world-changing ideas buried in engineering baggage like STL. Their GC language for small pieces is Scheme, an unpopular GC language in the FOSS community. Some in their group recommend Erlang. The OpenCog team looks at their core of C++, and over to OpenCV’s core of C++, and concludes the situation is fine. One of the biggest features of the ROS (Robot OS), according to its documentation, is a re-implementation of RPC in C++, not what robotics was missing. I’ve emailed various groups and all know of GC, but they are afraid of any decrease in performance, and they do not think they will ever save time. The transition from brooms to vacuum cleaners was disruptive, but we managed.

C/C++ makes it harder to share code amongst disparate scientists than a GC language. It doesn’t matter if there are lots of XML parsers or RSS readers, but it does matter if we don’t have an official computer vision codebase. This is not against any codebase or language, only for free software lingua franca(s) in certain places to enable faster knowledge accumulation. Even language researchers can improve and create variants of a common language, and tools can output it from other domains like math. Agreeing on a standard still gives us an uncountably infinite number of things to disagree over.

Because the kernel is written in C, you’ve strongly influenced the rest of community. C is fully acceptable for a mature kernel like Linux, but many concepts aren’t so clear in user mode. What is the UI of OpenOffice when speech input is the primary means of control? Many scientists don’t understand the difference between the stack and the heap. Software isn’t buildable if those with the necessary expertise can’t use the tools they are given.

C is a flawed language for user mode because it is missing GC, invented a decade earlier, and C++ added as much as it took away as each feature came with an added cost of complexity. C++ compilers converting to C was a good idea, but being a superset was not. C/C++ never died in user mode because there are now so many GC replacements, it created a situation paralyzing many to inaction, as there seems no clear place to go. Microsoft doesn’t have this confusion as their language, as of 2001, is C#. Microsoft is steadily moving to C#, but it is 10x easier to port a codebase like MySQL than SQL Server, which has an operating system inside. C# is taking over at the edges first, where innovation happens anyway. There is a competitive aspect to this.

Lots of free software technologies have multiple C/C++ implementations, because it is often easier to re-write than share, and an implementation in each GC language. We all might not agree on the solution, so let’s start by agreeing on the problem. A good example for GC is how a Mac port can go from weeks to hours. GC also prevents code from being able to use memory after freeing, free twice, etc. and therefore that user code is less likely to corrupt your memory hardware. If everyone in user mode were still writing in assembly language, you would obviously be concerned. If Git had been built in 98% Python and 2% C, it would have become easier to use faster, found ways to speed up Python, and set a good example. It doesn’t matter now, but it was an opportunity in 2005.

You can “leak” memory in GC, but that just means that you are still holding a reference. GC requires the system to have a fuller understanding of the code, which enables features like reflection. It is helpful to consider that GC is a step-up for programming like C was to assembly language. In Lisp, first GC language, the binary was the source code — Lisp is free by default. The Baby Boomer generation didn’t bring the tradition of science to computers, and the biggest legacy of this generation is if we remember it. Boomers gave us proprietary software, C, C++, Java, and the bankrupt welfare state. Lisp and GC were created / discovered by John McCarthy, a mathematician of the WW II greatest generation. He wrote that computers of 1974 were fast enough to do Strong AI. There were plenty of people working on it back then, but not in a group big enough to achieve critical mass. If they had, we’d know their names. If our scientists had been working together in free software and Lisp in 1959, the technology we would have developed by today would seem magical to us. The good news is that we have more scientists than we need.

There are a number of good languages, and it doesn’t matter too much what one is chosen, but it seems the Python family (Cython / PyPy) require the least amount of work to get what we need as it has the most extensive libraries: http://scipy.org/Topical_Software. I don’t argue the Python language and implementation is perfect, only good enough, like how the shape of the letters of the English language are good enough. Choosing and agreeing on a lingua franca will increase the results for the same amount of effort. No one has to understand the big picture, they just have to do their work in a place where knowledge can easily accumulate. A GC lingua franca isn’t a silver bullet, but it is the bottom piece of a solid science foundation and a powerful form of social engineering.

The most important thing is to get lingua franca(s) in key fields like computer vision and Strong AI. However, we should also consider a lingua franca for the Linux desktop. This will help, but not solve, the situation of the mass of Linux apps feeling dis-integrated. The Linux desktop is a lot harder because code here is 100x bigger than computer vision, and there is a lot of C/C++ in FOSS user mode today. In fact it seems hopeless to me, and I’m an optimist. It doesn’t matter; every team can move at a different pace. Many groups might not be able to finish a port for 5 years, but agreeing on a goal is more than half of the battle. The little groups can adopt it most quickly.

There are a lot of lurkers around codebases who want to contribute but don’t want to spend months getting up to speed on countless tedious things like learning a new error handling scheme. They would be happy to jump into a port as a way to get into a codebase. Unfortunately, many groups don’t encourage these efforts as they feel so busy. Many think today’s hardware is too slow, and that running any slower would doom the effort; they do not appreciate the steady doublings and forget that algorithm performance matters most. A GC system may add a one-time cost of 5-20%, but it has the potential to be faster, and it gives people more time to work on performance. There are also real-time, incremental, and NUMA-aware collectors. The ultimate in performance is taking advantage of parallelism in specialized hardware like GPUs, and a GC language can handle that because it supports arbitrary bitfields.

Science moves at demographic speed when knowledge is not being reused among the existing scientists. A lingua franca makes more sense as more adopt it. That is why I send this message to the main address of the free software mothership. The kernel provides code and leadership, you have influence and the responsibility to lead the rest, who are like wandering ants. If I were Linus, I would threaten to quit Linux and get people going on AI ;-) There are many things you could do. I mostly want to bring this to your attention. Thank you for reading this.

I am posting a copy of this open letter on my blog as well (http://keithcu.com/wordpress/?p=1691). Reading the LKML for more than one week could be classified as torture under the Geneva conventions.

In liberty,

-Keith

7 comments to GC Lingua Franca(s)

  • Sam

    There is this Internet-ism called ‘tl;dnr’,
    http://www.urbandictionary.com/define.php?term=tl%3Bdnr

    That is, at the end of your post you type ‘tl;dnr:’ and add a succinct summary of your ramblings.
    If it is impossible to to summarize any more what you wrote, then there is something wrong with the ideas.

    • Hi Sam;

      That is a good rule and I am familiar with it.

      Not only is it possible to summarize in one sentence, I have done that in the first paragraph. In fact, it is better to put it towards the beginning.

      • Zan Lynx

        In my opinion, your first paragraph doesn’t correctly summarize the rest of it. It isn’t clear what you are asking the LKML community to do. It isn’t clear what a GC lingua franca means to you.

        Also, what you seem to be asking for isn’t realistic. You seem to be asking for everyone to standardize on one single garbage collected language and you seem to be asking the Linux Kernel to lead the way. Are you asking for the kernel to use a GC language? Or are you asking for kernel programmers to get involved with user-space programming?

        Open source programmers are never going to standardize on anything. Every programmer believes he or she can do a better job or wants to experiment with using a new language. Writing new code is more fun than learning and modifying existing code. It just is. So if open source programmers are not being paid to work on existing code, it is far more likely that they will write their own new code.

        It seems to me that what you want is already happening in the Apache project. Most of their newer software is being written with Java. And as you mentioned, much of Linux desktop software is being written in Python. The problem is that Python quickly becomes too slow to be useful.

        In my opinion, your open letter seems to be mainly a complaint about the OpenCV project and its management. Perhaps you should focus your effort on refactoring it in order to reduce the amount of code duplication. You could get involved with the Boost project and get utilities like Matrix classes moved out of OpenCV and into Boost. As a matter of fact, matrix and vectors are already included in Boost. Boost is probably the closest thing C++ has to a standard library other than the included C++ standard library.

        • Hi Zan;

          I am asking the LKML community to provide leadership in the transition to GC languages, especially for certain communities.

          The kernel is fine in C as I say in the post.

          We need standards mostly in a few places: computer vision, strong AI, and the Linux desktop. I think Java should be killed, I have a chapter in my book describing why. There is plenty of fast Python code including games. People can do what Mercurial did which is 99% Python and 1% C. There is also Pyrex, PyPy, etc.

          It isn’t about the OpenCV project because it happens in other groups as well. The “consensus” in OpenCV that Python is too slow is the same one that you have. That is why I go to the LKML.

          I propose to abandon C++ as quickly as possible. Have you seen this? http://yosefk.com/c++fqa/

          • >I am asking the LKML community to provide leadership in the transition to GC languages, especially for certain communities.

            Why do you think anyone is going to listen to the LKML community, even assuming that the LKML community could come to enough of a consensus to speak with a single voice?

            And just because we happen to be really going at Linux kernel development, does not suddenly make us an expert on garbage collected languages, so there’s not even any reason why anyone _should_ listen to us.

            — Ted

  • Hi Ted;

    I’m a fan of your filesystem work ;-)

    User mode is not just some abstraction. Strong AI will be implemented in user mode, etc.

    People listen to the LKML community. If Git had been written in Python in 2005, I can envision additional places Python would be used by now. I try to bring this message to other people, but I feel certain that you guys have so much power to improve Linux user mode that I tell you first.

    You do not need to be an expert in garbage collected languages to see their utility. I summarize it in 25 pages, and I’ll bet you know most everything in there already.

    It is okay that different people speak in different voices. I’m not exactly sure what is best to be done. I do believe it is an issue that even the kernel people should be aware of. To be honest, I am satisfied to send this email and hope some people read it. Maybe a consensus can be built in the future. Although I don’t know what you are waiting on. GC was invented in 1959.

    -Keith

  • Dear Keith,

    you have forgot an important detail: we need to sip champagne in the back seats of an automatically driven car running on electrical power from (a) batteries, (b) hydrogen fuel cells or (c) from a small Mr. Fusion (mobile thermonuclear fusion conversion device).

    This thing http://www.iter.org does not work because the lack of an appropriate simulation and automatic code generation software like http://www.scicos.org, http://www.scicoslab.org.

    Unfortunately, too many people in the scientific community see the close source model as the only way to protect their legitimate rights to be honestly recognised as the primary sources of their ideas, prototypes and usable implementations.

    Why?

    Because some open source project are leaded by people with not very honest intentions and scopes.

    Thanks for your fantastic book !

    Simone Mannori
    ENEA Brasimone Data Acquisition and Control System Team
    ScicosLab Development Team

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